Summer Program for Undergraduate Research Projects for 2026

The CU Summer Program for Undergraduate Research (CU SPUR) program takes place over 10 weeks each summer. There is funding for up to 100 undergraduate engineering students to work in research labs and only available to CU Boulder Engineering students. Students will work for ten weeks, up to 30 hours per week over the summer.

CEAS students in good academic standing will receive an email in mid-February with a link to apply.

Timeline

  • Project list released: mid-February
  • Application sent to students: mid-late February
  • Watch "Preparing to Apply for SPUR/DLA"
  • Deadline to apply: mid-March
  • Students notified of decision: mid-April
  • Summer 2026 program dates: May 26th - July 31st

Projects are listed by department or program. Review the "desired major" section of each project for eligibility to apply.

Project Description

The RF & SatNav Laboratory has extensive experience in working with the GPS/GNSS within Android phones and with Google and working to improve the capabilities. Furthering that effort, this project will use crowdsourced measurements from Android phone sensors to detect and locate various threats, including GPS/WiFi/cellular jammers and gunshot sounds. For example: https://www.washingtonpost.com/technology/2025/12/31/gps-jamming-spoofing-economy-threats/

Requirements: 

  • Participating students should have a background in Linux and coding (Matlab, C++, Python, Java), but GPS/GNSS knowledge is not required. 
  • Development in Java with Android studio and C++ are desired.

Website:https://www.colorado.edu/lab/rf-satnav/

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Dennis Akos, Faculty
Email: akos@colorado.edu

Ben Gattis, Graduate Student
Email: Benon.Gattis@colorado.edu

Project Description

The Compact Spaceborne Magnetic Observatory (COSMO) CubeSat mission is a 6U CubeSat expected to launch in April 2026. Designed for low-Earth orbit, COSMO will provide critical measurements of the Earth’s magnetic field to support the next-generation World Magnetic Model (WMM). The CubeSat is equipped with two optical rubidium scalar magnetometers housed within a wire-coiled cube. Modulation fields applied to the cube along all three axes enable the extraction of vector components of the Earth’s magnetic field. The collected magnetic field data will be downlinked, processed, and calibrated before publication and dissemination to communities of interest. The data will also include star tracker quaternion information to provide the attitude reference for each measurement.
 
YOUR ROLE:
After commissioning, the science data will be collected every day. The data needs to be processed and packetized into NetCDF (Network Common Data Form). Your role will be assisting the graduate mentor in finalizing the data pipeline (from Level 0 to Levels 1a and 1b) and further developing Level 2 data. Students interested in space mission data analysis and/or spacecraft attitude dynamics are especially encouraged; this is a rare opportunity to work with science and attitude data from a new mission!
 
Tzu-Hsun Kao, a Ph.D. student, will provide guidance and support for any issues, while Dr. Robert Marshall will oversee the entire project.

Requirements:

  • Students must be familiar with either MATLAB or Python. 
  • Knowledge of orbits, spacecraft attitude, coordinate transformations, and geomagnetic data is a plus.

Website:https://culair.weebly.com/cosmo.html

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Robert Marshall, Faculty
Email: Robert.Marshall@colorado.edu

TzuHsun Kao, Graduate Student
Email: Tzu-Hsun.Kao@colorado.edu

Project Description

Future crewed landings on the moon have a risk that astronaut may become disoriented, due to the unique lander vehicle motions and their rapid exposure to lunar gravity after having adapted to microgravity during transit. We are developing and validating countermeasures in a series of ground-based studies. Our experiments involve human subject testing in our human-rated motion devices. Subjects report orientation perception during lunar landing-like motions, their level of spatial disorientation, or perform a manual control piloting task with or without our intervention. The SPUR student will help recruit study participants, assist in performing tests, including operating our motion devices, and help analyze data.

Requirements: None

Desired Majors: Aerospace Engineering Sciences, Biomedical Engineering

Contact

Torin Clark, Faculty
Email: torin.clark@colorado.edu

 

Project Description

At the RF & SatNav Laboratory we have an interest in how to use low-cost widely available sensor platforms, such as smartphones, to solve emerging problems.
 
One such problem is the growing prevalence of small drones which can be dangerous and difficult to localize. Students will work to continue to develop current Android tools within the RF and SatNav Lab to help solve this problem.

Requirements:

  • Participating students should have a background in Linux and coding (Matlab, C++, Python, Java), but GPS/GNSS knowledge is not required.
  • Development in Java with Android studio and C++ are desired.

Website:https://www.colorado.edu/lab/rf-satnav/

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Dennis Akos, Faculty
Email: akos@colorado.edu

Trey Taylor, Graduate Student
Email: Fred.TaylorIii@Colorado.EDU

Project Description

Are you interested in learning more about how humans and autonomous systems interact? Contribute to understanding how humans can best use autonomy in search and rescue! We'll be conducting a human subject study into how users' sense of control, performance, and workload change across different means of input to an autonomous system, grounded in a search and rescue task. As a part of this project you have the opportunity to gain experience in and contribute to: refining the study design, facilitating in-person experiment sessions, and analyzing results.

Requirements:

  • Student must be available to help run study sessions in-person (2-3 hour blocks).
  • Experience with statistics and coding languages (R, Python, Julia, Matlab, etc.) is strongly preferred.
  • Attention to detail and communication skills are essential for this role.
  • Prior experience in research, especially human subjects studies, is preferred.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Biological Engineering, Biomedical Engineering, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Zachary Sunberg, Faculty
Email: Zachary.Sunberg@colorado.edu

Ben Kraske, Graduate Student
Email: benjamin.kraske@colorado.edu

Project Description

This project is motivated by understanding how wildfires spread through isolating the generation and transport of individual firebrands (or embers) in a controlled wind tunnel cross-flow in the Experimental Aerodynamics Laboratory. More specifically, the selected student will be responsible for designing an experiment under the advisement of the identified PhD Student and Faculty Mentors, to ignite wooden dowel segments from a controlled methane burner (or torch) in a low speed wind tunnel cross flow. The primary goal is to understand what wooden dowel configuration (i.e., size, position, etc.) repeatably generates a firebrand that can be lofted and transported in the wind tunnel flow. Data analysis for this project will focus around high-speed imaging and flow visualization.

Requirements:

  • Students should have ideally completed coursework in:
    • 1) Fluid mechanics (i.e., MCEN 3021 ), Aerodynamics (i.e., ASEN 3711), or equivalent courses.
    • 2) Thermodynamics (i.e., MCEN 3012 or ASEN 3713) or equivalent courses.
    • However demonstrated prior experience in these areas from other activities (i.e., research, independent study, etc.) would also be acceptable.
  • Students should be in good academic standing (i.e., GPA of 3.0 or greater) and should also be interested and willing to work with their hands in the physical experimental laboratory and machine shop settings. Demonstrated prior experience working independently in a machine shop is preferred.

Website: https://www.colorado.edu/today/2025/12/05/wind-tunnel-research-could-help-predict-how-wildfires-spread

Desired Majors: Aerospace Engineering Sciences, Architectural Engineering, Civil Engineering, Engineering Physics, Environmental Engineering, Mechanical Engineering

Contact

John Farnsworth, Faculty
Email: john.farnsworth@colorado.edu

Laura Shannon, Graduate Student
Email: laura.shannon@colorado.edu

Project Description

The RF & SatNav Laboratory leverages software defined radios for a variety of tasks including harmful emitter geo-location.
 
With a focus on estimating angle of arrival measurements between a radio and an emitter, work for this effort would seek to further the understanding and potential currently held within the RF and SatNav Lab. This may include exploration of the capabilities of different radio platforms, an assessment of available angle of arrival estimation algorithms, and/or the integration of existing tools with new hardware.

Requirements:

  • Participating students would preferably have a background in Linux and should have coding experience (Matlab, C++, Python). 
  • GPS/GNSS knowledge is not required.

Website:https://www.colorado.edu/lab/rf-satnav/

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Dennis Akos, Faculty
Email: akos@colorado.edu

Trey Taylor, Graduate Student
Email: Fred.TaylorIii@Colorado.EDU

Project Description

In this project, we are using Python to implement a machine learning approach for modeling G-induced loss of consciousness (G-LOC) in pilots. G-LOC is a dangerous condition that occurs when pilots in high performance aircraft pull high G-levels.
 
Physiological data has been collected from participants in a centrifuge (e.g., Electrocardiogram, Electroencephalogram, Eye-tracking, Respiration, etc.) and is being used to predict G-LOC in advance. Machine Learning approaches being implemented include traditional machine learning approaches, such as Random Forest, Linear Discriminant Analysis, K-Nearest Neighbors, Support Vector Machine, and more. More advanced approaches are also being explored, such as neural networks and other deep learning classifiers. Over the summer, we will be exploring the forecasting time (time in advance we can predict G-LOC before it occurs) we can achieve, while retaining model accuracy. We may also be exploring the importance of each individual biosignal (e.g., Electrocardiogram or eye-tracking) in predicting G-LOC.
 
This project will involve a lot of coding in Python and working with physiological data.

Requirements:

  • Students should have experience with Python or another object-oriented programming language
  • Ideally student has experience with machine learning and deep learning methods or experience with physiological data streams

Website: https://www.colorado.edu/faculty/anderson/research-projects

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Biomedical Engineering, Computer Science, Electrical & Computer Engineering, Mechanical Engineering

Contact

Allison Hayman, Faculty
Email: allison.p.anderson@colorado.edu

Aaron Allred, Post-Doc
Email: aaron.allred@colorado.edu

Project Description

We are seeking a student to assist with running and supporting a human-robot teaming research study. The project uses a Unity-based virtual environment in which humans and robots collaborate to complete warehouse tasks. The primary responsibilities will involve preparing study sessions, testing the system, running human subjects, monitoring data collection, and helping ensure data quality across experimental trials. There may be occasional opportunities to contribute to small updates or improvements in Unity, but software development is not the main focus of this role.
 
Commitment: 10 hours per week

Requirements:

  • It is desirable, but not required, to have previous research experience or familiarity with Unity.

Desired Majors: Aerospace Engineering Sciences, Biomedical Engineering, Computer Science, Electrical & Computer Engineering, Mechanical Engineering

Contact

Allison Hayman, Faculty
Email: allison.p.anderson@colorado.edu

Prachi Dutta, Post-Doc
Email: prachi.dutta@colorado.edu

Project Description

The objective of this study is to collect data needed to characterize the dynamic nature of longitudinal trust and develop models that can infer and predict trust across longer periods of interaction with autonomous systems. In this research, we will collect measures of human participant signals from their body such as psychophysiological responses, as well as measures of the actions that participants take while they complete simulated tasks. The task that our human testing subjects will perform in this research is flying in a cockpit simulator with an autonomous co-pilot in a contested environment. These psychophysiological measures will then be compared to traditional, validated measures of trust to verify their accuracy and subsequently used to create dynamic trust models that are transferable between tasks and can be used by systems in real-time. SPUR participants will help with running the experiment, data collection from on-body sensors, data analysis, and developing new experiments.

Requirements:

  • Must have previous coding experience

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Allison Hayman, Faculty
Email: allison.p.anderson@colorado.edu

Lisa Ventura, Graduate Student
Email: lisa.ventura@colorado.edu

Project Description

For centuries, engineers have drawn inspiration from natural forms to refine mechanical components and engineered materials. In contemporary practice, existing engineering designs often serve as reference points for further optimization efforts. While a vast array of shapes with notable mechanical properties exists in nature and engineering, there remains a lack of systematic and efficient methodologies for extracting insights from these forms to address specific design challenges.
 
This project aims to investigate the application of Machine Learning (ML) techniques to synthesize shapes observed in both natural environments and engineered systems. ML will be employed to interpolate between various shapes, defining a continuous design space that can be rigorously explored through computational design optimization methods such as shape and topology optimization.
 
The SPUR student will develop a computational framework that integrates ML algorithms with MORIS, an in-house design optimization code, to enhance the structural and fluid dynamic performance of component shapes.

Requirements:

  • The student should have basic knowledge of Python and C++ programming. 
  • A fundamental understanding of statics, structures, and fluid mechanics is needed for this project. 
  • Prior knowledge of machine learning and libraries, such as PyTorch or TensorFlow, is beneficial but not required.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Biomedical Engineering, Civil Engineering, Computer Science, Engineering Physics, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Kurt Maute, Faculty
Email: maute@colorado.edu

Conor Rowan, Graduate Student
Email: Conor.Rowan@colorado.edu

Project Description

Rubble-pile asteroids are loose collections of rocks held together by their weak gravity. Missions to these smaller asteroids have shown that their granular surfaces can behave unexpectedly after disturbances. For example, when the OSIRIS-REx spacecraft touched asteroid (101955) Bennu's surface, the entire local region of rubble was disturbed (look up pictures/videos online for reference). Understanding these spacecraft-regolith interactions is important for future exploration, sampling, and even planetary defense efforts.
 
In this project, we will use LMGC90, an open-source simulation platform for modeling large collections of interacting particles, to simulate a spacecraft interacting with an asteroid's surface. The student will build on existing simulation setups to explore how a lander or sampling device interacts with surface regolith. They will design, run, and adjust simulations, then use LMGC90's visualization tools to analyze results like particle movements and contact forces.
Since simulations can take many hours to run, there is also an opportunity to contribute work on rubble-pile asteroid interiors. Using code that has already been developed, the student can apply our asteroid analysis methods to another asteroid with available data, computing internal heterogeneous structures. Analysis of mission data suggest Bennu's interior is less dense than the rest of the body, and similar techniques can be used to reveal if other asteroids share this trait.
The student will be guided by the graduate researcher throughout the summer to get accustomed to the existing projects, code, theory, and context of the work. The student may have the chance to explore interesting ideas that arise throughout the summer relating to spacecraft-regolith interaction and/or rubble-pile interiors.

Requirements:

  • Good understanding of calculus, linear algebra, and differential equations.
  • Good understanding of rigid-body dynamics, frictional forces, and inelastic/elastic collisions.
  • Basic understanding of numerical methods (integrating equations of motion, the effect of the time step on results, etc.).
  • Strong programming skills: basic/intermediate understanding of Python and good understanding of MATLAB.
  • Able to understand existing code in MATLAB and Python and build off it.
  • Interest in planetary science and past, ongoing, and future missions to asteroids.
  • Responsible usage of AI tools for coding, reading papers, etc.
     
    Optional:
  • Version control with Git.
  • A general understanding of orbits.

Website: https://ccar.colorado.edu/scheeres/

Desired Majors: Aerospace Engineering Sciences, Chemical Engineering, Civil Engineering, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Mechanical Engineering

Contact

Daniel Scheeres, Faculty
Email: daniel.scheeres@colorado.edu

Ashish Cavale, Graduate Student
Email: ashish.cavale@colorado.edu

Project Description

This spring and summer I will be conducting an experiment of Human-Autonomy Teaming with explainable AI in a demanding spaceflight task. This project is the second experiment that will utilize the ARES cockpit as a full-scale simulator of a Mars rover driving task, but we'll be implementing a new AI teammate. The SPUR student will help me develop the newest AI teammate and display, develop protocols for running the experiment, run participants through data collection, and assist in data analysis (depending on how quickly we progress). Ideal skills include experience in Unity (C# language) or some video game design, strong organizational skills, and some basic statistical background.

Requirements:

  • Student must be available in person at the aerospace engineering building for running the experiment during the workday (9am-5pm).

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Zachary Sunberg, Faculty
Email: Zachary.Sunberg@colorado.edu

Mark Boyer, Graduate Student
Email: mark.boyer@colorado.edu

Project Description

The RF & SatNav Laboratory has extensive experience in working with the GPS/GNSS. The GPS/GNSS is becoming increasingly frail with signal jamming and spoofing (https://www.washingtonpost.com/technology/2025/12/31/gps-jamming-spoofing-economy-threats/). GPS/GNSS is a primary means of navigation for UAVs. This project will explore using open source autopiloting software for navigating UAVs when GPS is not available.

Requirements:

  • This is a complex topic required strong software development skills, particularly under Linux. 
  • Experience with either of the popular open source autopilots (https://ardupilot.org/ or https://px4.io/) would be extremely useful. 
  • An understand of GPS/GNSS is useful but not required. 
  • Experience with UAS/UAV in terms of piloting and control would be useful, but not required.

Website: https://www.colorado.edu/lab/rf-satnav/

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Dennis Akos, Faculty
Email: akos@colorado.edu

Project Description

Optimization is used throughout science and engineering for diverse tasks such as solving partial differential equations, designing control laws, and training machine learning models. To solve real-world optimization problems, mathematical rules must be specified for how to traverse the surface defined by an "objective function" in search of a minimum. Think of it this way: you are in a hilly landscape at night with a small flashlight. How do you use the information provided by your immediate surroundings (for example, east=steep uphill, west=downhill, north and south=flat) to eventually locate the bottom of a valley? Each optimization algorithm provides its own unique answer to this question. However, in practice, these landscapes may be defined in hundreds of thousands of dimensions, which renders intuition from our three-dimensional world ineffective in understanding the behavior of different algorithms. This project will explore techniques to visualize high-dimensional surfaces from optimization problems in machine learning in order to better understand differences in the performance of popular optimization algorithms such as gradient descent, ADAM, Newton's method, and more. Better visualizations of the objective function not only provide insight into optimization algorithms, but also into the machine learning model itself. Central to this project is the probably philosophical question of what it means to "see" in high dimensions, which naturally arises alongside mathematical techniques to do this.

Requirements:

  • Interest in math and coding, the student will implement methods themself
  • Some experience using Python (machine learning experience is a plus)
  • Curiosity, creativity, and independence more important than past course work

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Civil Engineering, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Mechanical Engineering

Contact

Alireza Doostan, Faculty
Email: alireza.doostan@colorado.edu

Conor Rowan, Graduate Student
Email: coro3440@colorado.edu

Project Description

This project looks to compress large scale unstructured PDE CFD simulation datasets by analyzing time dependent snapshots of solution data. Focus is on modifying existing software used for image and video compression to perform compression on data on an unstructured grid.
 
The student will work with a graduate applied mathematics student on integrating code in Python and C to efficiently handle time dependent data on unstructured grids. The student will gain experience with techniques for predicting image/video frames on unstructured grids along with compressing this data using mathematical techniques.

Requirements: 

  • Strong programming background in both C or C++ and Python

    Recommended skills:
  • Python programming
  • familiarity with image/video compression
  • familiarity with differential equations and scientific simulation
  • familiarity with the discrete Fourier Transform and variants
  • having taken APPM 4600 Numerical Analysis.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Computer Science, Electrical & Computer Engineering

Contact

Alireza Doostan, Faculty
Email: doostan@colorado.edu

Mohit Garg, Graduate student 
Email: mohitgarg@colorado.edu

Project Description

Mechanobiology is the study of how cells sense and respond to their physical environment to maintain homeostasis. To investigate how mechanical cues are transmitted to the nucleus and influence gene expression, Dr. Corey Neu's laboratory has developed a CRISPR-Cas12 based live-cell imaging tool that enables tracking of specific genomic loci in response to mechanical stimulation. To apply this imaging platform, guide RNAs for mechano-responsive genes must be engineered, and quantitative analysis of cellular biomechanical imaging data must be performed. In this summer research project, the student will take a quantitative systems approach to biological engineering, integrating concepts from engineering and biology to understand how mechanical cues regulate genomic organization. The student will participate in plasmid engineering for mechanically activated gene reporters, live-cell imaging of genomic locus dynamics, and downstream data analysis. Over the course of the summer, the student will gain hands-on experience in cloning, cell culture, fluorescence imaging, and MATLAB-based image and statistical analysis. Basic knowledge of molecular biology and familiarity with CRISPR-Cas systems are recommended.

Requirements:

  • Basic knowledge of molecular biology along with the CRISPR-Cas12a editing system are highly recommended.
  • As stated in the description, this project involves techniques related to cloning, imaging, and data analysis with MATLAB, having experience with some or all of these would be highly desirable.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Corey Neu, Faculty
Email: cpneu@colorado.edu

Stephanie Schneider, Graduate Student
Email: stephanie.schneider@colorado.edu

Project Description

High-grade serous carcinoma (HGSC) is one of the most prevalent and aggressive types of ovarian cancer. Standard treatment typically involves surgical removal of tumor tissue followed by platinum-based chemotherapy, often combined with drugs such as paclitaxel. In some patients, additional maintenance therapies are used to delay recurrence. While these approaches can be effective initially, they are associated with significant side effects like bone marrow suppression, nerve damage, and gastrointestinal toxicity. Many tumors also eventually recur and become resistant to treatment. This is because HGSC lacks well-defined targets that would allow drugs to selectively act on tumor cells while sparing healthy tissue.
 
An emerging strategy to improve treatment specificity is targeted drug delivery using immune cells. Macrophages naturally migrate into ovarian tumors, particularly within the omentum and peritoneal cavity, making them attractive carriers for therapeutic agents. In this work, macrophages will be equipped with surface-attached polymeric “backpack” particles that transport drugs to the tumor microenvironment without being internalized by the cell. The backpacks are fabricated from a photocrosslinkable poly(β-amino ester) (PBAE) polymer synthesized by reacting 1,4-butanediol diacrylate with benzhydrazide. This chemistry produces a polymer that can be crosslinked using ultraviolet light to form particles. Discoidal particles are then created using a lithography-based fabrication process, similar to techniques used in semiconductor manufacturing, which allows for control over particle size, shape, and stiffness.
However, a major challenge in current macrophage-based delivery systems is that many effective cancer drugs are also toxic to macrophages, limiting how much drug can be loaded without damaging the carrier cell.
 
To address this, we will design drug-loaded particles that covalently retain cytotoxic drugs within a polymer network rather than exposing the macrophage directly to free drugs, such as what occurs during diffusion-based drug-loading. By decoupling drug payload from acute macrophage exposure while preserving controlled release at the target site, we hope to obtain substantially higher effective drug loading without inducing macrophage apoptosis or impairing migratory capacity. Ultimately, findings from this project could enhance the efficacy of macrophage-backpacks in treating HGSC by expanding therapeutic options beyond those currently compatible with non-tumor cells.

Requirements:

  • The student will be expected to have taken organic chemistry and have experience with basic lab equipment including pipettes, fume hoods, scales, UV-Vis spectroscopy, and chemical safety training.
  • The student will be responsible for the synthesis of the PBAE polymer after the instruction period and will aid in the design and running of studies looking at drug loading efficacy, drug release, polymer composition, and polymer degradation.
  • Techniques and instrumentation may include NMR, UV-Vis, MestReNova, HPLC, stylus profilometry, and cell culture.

Website: https://www.colorado.edu/faculty/shields

Desired Majors: Biological Engineering, Biomedical Engineering, Chemical Engineering, Engineering Physics, Mechanical Engineering

Contact

Wyatt Shields, Faculty
Email: Charles.Shields@colorado.edu

Courtney Bailey, Graduate Student
Email: Courtney.Bailey@colorado.edu

Project Description

Weak, low-frequency electromagnetic radiation below the thermal noise floor has demonstrated the ability to influence biological systems significantly, from cellular processes to organ-level functions. However, the mechanisms underlying these interactions remain poorly understood, requiring interdisciplinary expertise spanning quantum physics, biochemistry, and clinical medicine. The Barnes Research Group is dedicated to unraveling these mechanisms to explore how weak electromagnetic fields alter bioenergetics and stress responses in cancer and other cell types. This research holds potential for developing innovative therapeutics and establishing safety guidelines.
 
This summer project will investigate the effects of weak, low-frequency electromagnetic fields on oxidative stress responses and metabolism in HT1080 fibrosarcoma cells -- a well-characterized connective tissue cancer cell line, and PC3 prostate cancer cells. The selected SPUR student will work closely with graduate researchers, contributing primarily to laboratory tasks such as cell culture, media changes, assay processing, imaging, and setting up electromagnetic field exposure systems. As the summer progresses, the student will gain hands-on experience in experiment design and research planning, fostering a deeper understanding of both the scientific process and the impact of this emerging field of study. This opportunity is ideal for motivated students with a strong interest in biomedical research and a desire to engage in interdisciplinary exploration.

Requirements:

  • Lab work and imaging session may require students to be available for 2-6 hours block of in-person time.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, , Biological Engineering, Biomedical Engineering, Chemical Engineering, , Computer Science, , Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Frank Barnes, Faculty
Email: barnes@colorado.edu

Nhat Dang, Graduate Student
Email: nhda8697@colorado.edu

Project Description

Fatty acid synthesis in bacteria and plants operates as an enzyme cascade, where 10+ proteins work together to build fatty acids of varying carbon chain length (anywhere from C4 - C18). These fatty acids are very energy dense, and have applications in oleochemical and biofuel production as feedstocks. The first step of this enzymatic pathway is acetyl-CoA carboxylase. Regulation (and subsequent activity/speed) of this step is key in determining how much carbon is pushed through the pathway and in turn, how many fatty acids are produced.
 
In E. coli, this step does not have very complex regulation systems. In plants, however, this is not the case. Plants have many interacting proteins that can stabilize or destabilize, and activate or inactivate the complex causing changes in activity and impacting fatty acid production. The activities and role of these interacting proteins is not well characterized or documented.
 
For this project, the student will be tasked with building a bacterial system that is capable of testing and characterizing regulation mechanisms of acetyl-CoA carboxylase. This will involve, CRISPR genome editing of E. coli, cloning of target interactor proteins into vectors suitable for in vivo expression, and performing FAS assays to measure lipid profiles after titrating expression of interactor proteins.

Requirements:

  • Applying students are recommended to have taken biochemistry and understand the basics of protein synthesis.
  • This project is in the topic of synthetic biology and applied enzymology which will require a large amount of cell culture. Since this is a time dependent process, students should expect to have a fluid lab schedule (requiring some shorter days (~1-2 hours) and some longer days (~8-10 hours)).

Desired Majors: Biological Engineering, Chemical Engineering

Contact

Jerome Fox, Faculty
Email: jerome.fox@colorado.edu

Sam Andrzejewski, Graduate Student
Email: saan3304@colorado.edu

Project Description

Polymer films are used widely in packaging materials and as protective barriers for electronics and devices. Polymer materials are known for their strong mechanical properties, making their applications broad. At smaller scales, however, ultrathin polymer films exhibit weaker mechanical properties that limit their uses. It is generally unclear how polymers interact with surfaces and other polymers at these scales, and understanding these mechanisms can allow for implementation of ultrathin polymer materials for broader applications.
 
Handling ultrathin films often requires the transfer to a liquid surface, where lifting without a substrate can cause irreversible crumpling and self-adhesion of a film. Preliminary observations suggest that liquid barriers formed at the polymer–liquid interface can prevent permanent crumpling. Part of this project will investigate the interfacial design principles that govern reversible unfolding of ultrathin crumpled films on liquid surfaces. Understanding this can allow for easier manufacturing of thin films.
 
There is also evidence to suggest that the thin interfacial layer present between two polymers is higher in mechanical strength than the bulk materials. The second part of this project will explore how polymer bilayers form and how they can be analyzed through a uniaxial tensile tester, one of five in the world that can measure these scales for an entire stress response. Understanding this can allow for progress towards improving the mechanical properties of ultrathin polymer films.
 
Students that join this project will get hands-on skills in making and testing ultrathin polymer films in two different ways that have the same overall goal of understanding how ultrathin polymers behave at the film interface. Students will gain understanding of the effects that scale has on these materials. Students will collaborate with two graduate students and aid in data collection and analysis and will leave this project as stronger scientists that can understand the relevant literature and make connections between experiments and theory.

Requirements:

  • Be available to work in person 4-5 days a week (max 30 hours a week) for the whole duration of the program (10 weeks)
  • Completed the General Chemistry series
  • Courses in Materials science/engineering preferred but not required
  • Experience with MATLAB preferred but not required

Desired Majors: Applied Mathematics, Biological Engineering, Chemical Engineering, Civil Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Konane Bay, Faculty
Email: konane.bay@colorado.edu

Dylan Barton, Graduate Student
Email: dyba9373@colorado.edu

Project Description

Adoptive cell transfers are an emerging technology in cancer immunotherapy that harness the natural capabilities of immune cells, such as macrophages, for a desired therapeutic effect. Macrophages are able to bind engineered particles known as “cellular backpacks” to their surfaces, which can be used to deliver various cargo to the tumor site. In this project, we are investigating the use of Laponite, a 2D nanosilicate clay, as a carrier for therapeutic proteins in cellular backpacks. We hypothesize that increasing Laponite concentration within our particles will slow the release of proteins due to electrostatic interactions. We are also interested in exploring the use of Laponite as a stimuli-responsive material, for example, to facilitate controlled release in the acidic pH of the tumor microenvironment. The role of the SPUR student will be to assist with particle formulation and characterization, assess the effect of Laponite concentration and pH on protein release from particles, and investigate macrophage-particle interactions in vitro.

Requirements:

  • The student should have an interest in the fields of drug delivery, biomaterials, and/or immunology.
  • Students in Chemical & Biological Engineering or Biomedical Engineering are preferred, but all engineering majors will be considered.

Project Website: https://www.colorado.edu/faculty/shields/

Desired Majors: 

Contact

Charles Shields, Faculty
Email: Charles.Shields@colorado.edu

Caroline Rucker, Graduate Student
Email: Caroline.Rucker@colorado.edu

Project Description

Programmable microrobots are microscale devices that can perform repeatable actuation cycles to modify and interact with their environment. Such devices have applications in biomedicine and materials science, promising advancements in microsurgery, minimally invasive drug delivery, metamaterials, self-healing materials, and smart surfaces. Previous work in this field involves the fabrication and characterization of two-dimensional microscale actuators, but extrapolation to three-dimensional control remains elusive. For this project, we apply ferromagnetic patches to fabricated particles and use magnetic fields for actuation, toggling the field to induce conformational changes. Our microrobots consist of multiple patchy units connected by lithographic hinges, which comprises a novel design that introduces nontrivial degrees of freedom as we change the orientation of individual hinges and their corresponding patch pairs. Such a system enables 3D conformational changes, expanding the scope of potential applications and bringing microrobotics closer to practical implementation. The goals of this project are to 1) optimize the fabrication of the magnetic microrobots, 2) characterize the actuation of the microrobots in magnetic fields to display both two-and three-dimensional control, and 3) to validate simulation predictions with experimental results. Alongside general laboratory skills and experimental design, the SPUR student will learn clean room microfabrication techniques such as two-photon lithography and electron beam deposition, as well as imaging techniques like scanning electron microscopy. Their work will be crucial to the progress of an exciting new research field.

Requirements:

  • Student must demonstrate interest in materials science or engineering - particularly clean room fabrication - and they must be enthusiastic about research.
  • No prior research experience is expected and applications from all backgrounds are welcome, but preference may be given to students who have displayed particular interest in relevant subjects.

Project Website: https://www.colorado.edu/faculty/shields

Desired Majors: Biological Engineering, Biomedical Engineering, Chemical Engineering, Engineering Physics, Mechanical Engineering

Contact

Charles Shields, Faculty
Email: Charles.Shields@colorado.edu

Dylan McCuskey, Graduate Student
Email: Dylan.McCuskey@colorado.edu

Project Description

This project focuses on the experimental characterization and computational analysis of engineered protein-based biosensors for detecting biologically relevant small molecules. These biosensors are designed to change activity in response to ligand binding and have potential applications in diagnostics and metabolic monitoring.
 
The undergraduate researcher will assist in collecting and analyzing titration data to quantify biosensor performance, including sensitivity, dynamic range, and binding affinity. Experimental work will include preparing protein samples, performing ligand titration assays, measuring signal responses, and organizing experimental datasets. The student will learn to generate and interpret dose response curves and extract key parameters such as EC and Hill coefficients.
 
In parallel, the student will use computational tools to analyze and model structure–function relationships in biosensors. This will include basic data processing in Python or Excel, visualization of experimental results, and comparison with computational protein design predictions. The student will also assist in evaluating how molecular structure and mutations influence biosensor performance.
 
By the end of the project, the student will have contributed to generating high-quality quantitative datasets and developing predictive models to guide future biosensor engineering. The project provides hands-on training in biochemical experimentation, data science, and protein engineering research.

Requirements:

  • Completed or currently enrolled in at least one upper-division course in biochemistry, molecular biology, chemical engineering, or a related field
  • Basic laboratory experience (pipetting, solution preparation, sterile technique)
  • Interest in quantitative data analysis and computational tools
  • Willingness to learn Python, MATLAB, or spreadsheet-based data analysis (prior experience preferred but not required)
  • Strong attention to detail and ability to maintain organized experimental records

Desired Majors: Biological Engineering, Biomedical Engineering, Chemical Engineering

Contact

Timothy Whitehead, Faculty
Email: timothy.whitehead@colorado.edu

Ryan Delaney, Graduate Student
Email: ryde3462@colorado.edu

Project Description

Membrane-based separations are critical to addressing global sustainability challenges, ranging from energy efficient water purification to the recovery of high-value minerals from aqueous sources. To improve membrane performance, we need new ways to increase their selectivity towards solutes of interest beyond what conventional polymers can achieve. Recent advances in 2D polymerization have introduce a first-of-its-kind, solution-phase 2D polyaramid that may present a solution.
This project will explore the fabrication and testing of ultrathin membranes from 2D polyaramids for aqueous separations.
This project entails synthesizing 2D polyaramids, characterizing their structural properties, and measuring their response to aqueous environments (e.g., swelling). Lab work will involve glove box synthesis, characterization via Nuclear Magnetic Resonance (NMR) spectroscopy, spin coating membrane thin films, and, if time allows, X-ray reflectivity measurements of the membrane in different solvents. This hands-on research provides valuable experience in polymer science, membrane science, spectroscopy, and materials characterization.

Requirements:

  • None.

Project Website: https://ritt-lab.com

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, , Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Cody Ritt, Faculty
Email: cody.ritt@colorado.edu

Project Description

Membrane-based separations are critical to addressing global sustainability challenges, ranging from energy efficient water purification to the recovery of high-value minerals from aqueous sources. To improve membrane performance, we need new ways to increase their selectivity towards solutes of interest. The rate at which ions move across a membrane is largely influenced by the membrane's charge density. Previous synthetic approaches to increase charge density have shown limited success due to a permeability selectivity tradeoff that arises from swelling of the polymer. This project will explore new approaches to increase membrane charge density while minimizing the swelling.
 
This project entails preparing and characterizing thin polymer membranes (between roughly 10 - 100 nm in thickness). Lab work will involve membrane fabrication and testing, such as measuring water and ion permeabilities. Characterization will include experiments designed to measure chemical (e.g., charge density) and structural (e.g., swelling) features of the membranes. This hands-on research provides valuable experience in membrane science, microscopy, and materials characterization.

Requirements:

  • None.

Project Website: https://ritt-lab.com

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, , Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Cody Ritt, Faculty
Email: cody.ritt@colorado.edu

Project Description

Enzyme catalysis serves as a promising alternative to conventional heterogeneous catalysis by enabling efficient, selective reactions under mild conditions. Yet, most enzymes lose activity under industrially relevant conditions such as high temperature or organic solvents. Immobilization onto polymer brush scaffolds has emerged as a particularly effective means of enhancing enzyme stability under such conditions. Despite strong experimental evidence that polymer brush chemistry plays a key role in stabilization, the molecular basis of these effects remains poorly understood. We are using molecular dynamics simulations to studying how polymer brushes increase activity of LipA and various other lipase enzymes. Students joining this project will learn how to perform molecular dynamics simulations of proteins and analyze the results to understand how polymers can affect the catalytic activity of these proteins, in both water and organic in solvents.

Requirements: None.

Desired Majors: Applied Mathematics, Biological Engineering, Biomedical Engineering, Chemical Engineering, Computer Science, Engineering Physics

Contact

Michael Shirts, Faculty
Email: michael.shirts@colorado.edu

Joe Laforet, Graduate Student
Email: Joe.Laforet@colorado.edu

Project Description

Additive manufacturing of bio-stabilized earthen and Martian regolith materials offers a scalable platform for extraterrestrial infrastructure development by enabling in situ resource ultilization and minimizing reliance on earth-supplied binders, energy, and construction materials. Inspired by origin-of-life amino-acid-clay interactions, this project will explore amino acids and poly(amino acids) as bio-stabilizers for 3D printing earthen and Martian regolith materials. Within this project, you will get hands-on research experience studying how amino acids/poly(amino acids) interact with clay minerals. You will work with amino acids that have different chemical properties: positively charged, negatively charged, polar (water-loving), and nonpolar (water-repelling) and combine them with common subsoil minerals (kaolinite, bentonite, vermiculite, and mica), as well as Martian global simulant and its constituent minerals. You will also examine poly(amino acids) to understand how multivalent interactions and polymer chain conformation enhance interparticle cohesion. Through rheological testing and 3D printing, you will quantify how molecular chemistry governs rheology, extrusion behavior, shape retention, and mechanical properties, establishing structure-rheology-printability relationships. By demonstrating that amino acid- and poly(amino acid)-mediated interactions can stabilize earthen and Martian regolith-based materials for 3D printing, you will help develop a molecular basis for extending additive manufacturing to Martian regolith systems, supporting future in situ resource utilization and extraterrestrial construction.

Requirements:

  • Junior or Senior Standing.

Desired Majors: Aerospace Engineering Sciences, , Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Creative Technology & Design (CTD), Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Wil Srubar, Faculty
Email: wsrubar@colorado.edu

Yuhuan Wang, Post-Doc
Email: yuhuan.wang@colorado.edu

Project Description

Rehabilitated buried pipelines can experience concentrated demands at joints/discontinuities when the surrounding ground moves (e.g., differential settlement or lateral ground deformation). This CU SPUR project will support a research effort using the CIEST geotechnical centrifuge to reproduce ground-movement demands in a controlled environment and quantify how those demands translate into joint-level deformation and overall response of a buried rehabilitated pipe system. The student will assist with centrifuge model preparation, test execution support, and post-test data processing. The work is experimental and data-driven, with an emphasis on careful documentation and clear visualization of results.
Student Role and Responsibilities The SPUR student will contribute to the following tasks:
 
· Centrifuge test support
 
o Assist with physical model preparation and setup for buried pipe testing in the centrifuge environment.
 
o Support test-day operations: checklists, measurement verification, event logging, and consistent documentation (photos/notes).
 
· Data organization
 
o Clean and organize recorded data files into a consistent structure.
 
o Produce clear plots and summaries suitable for internal reporting and presentations.
 
o Compile post-test observations (visual inspection notes, photos, and qualitative damage/condition documentation).
 
If the student has CAD skills, assist with simple 3D renders to communicate or modify test configuration.

Requirements:

  • This project is best for students who already have some engineering background (not first-year). 
  • You should understand basic stress-strain and mechanics of materials so you can understand test measurements logic and help with simple engineering checks. 
  • You’ll also need to be comfortable working with data and following consistent plotting rules for clean figures; MATLAB coding and CAD/3D rendering skills are a plus.

Project Website: https://www.colorado.edu/center/ciest/

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Shideh Dashti, Faculty
Email: shideh.dashti@colorado.edu

Davis Holt, Professional Research Assistant
Email: daho5735@colorado.edu

Sina Senji, Graduate Student
Email: sina.senji@colorado.edu

Project Description

We are building a rainfall-simulation device in the geotechnical centrifuge to model compound climatic-seismic geo-hazards in the geotechnical centrifuge. The goal is to model the response of scaled slopes and embankments under extreme demands from back-to-back rainfall, flood, and earthquake conditions. This capability for physical modeling is essential for improving our mathematical predictive models of performance and improving resilience of our critical infrastructure. This project involves designing, fabricating, calibrating, and testing a new device that will be mounted on the existing shake table in the centrifuge, with subsequent instrumentation, control design, testing, and analysis.

Requirements:

  • Background in coding, autocad or other drawing software, lab view, and familiarity with finite element analysis is desired but not required. 
  • Interest in hands on lab testing is needed.

Project Website: https://www.colorado.edu/center/ciest/

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Shideh Dashti, Faculty
Email: shideh.dashti@colorado.edu

Amir Sayari, Graduate Student
Email: amir.sayari@colorado.edu

Project Description

The overarching goal for this work is to study how microplastics move in the ocean. To do that, we need to create an idealized ocean flow in the lab. The specific goal of this SPUR project to build a tank that simulates ocean turbulence. This approximately meter-cubed tank will include an array of jets that randomly stir the flow. The SPUR student will participate in finalizing the design of the tank and helping with its construction. Students interested in environmental issues who like building physical things would be good candidates for this SPUR project.

Requirements:

  • No hard requirements. Preference for students with prior building experience, but students who are interested in building things and don't have experience should still apply.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Laura Sunberg, Faculty
Email: Laura.sunberg@colorado.edu

Project Description

Get your hands dirty in the lab making concrete samples and testing their wet properties and hardened strength. We will collaborate with a waste stream supplier from the US Sugar industry to create a sustainable solution to their waste management by integrating it into concrete. You will learn industry standard testing methods applied to an innovative cement chemistry and get to practice data analysis and technical writing.

Requirements:

  • Be available for lab work in the CIEST lab during the hours 9am-5pm a few times throughout the project period.

Desired Majors: Architectural Engineering, Chemical Engineering, Civil Engineering, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Mija Hubler, Faculty
Email: hubler@colorado.edu

Project Description

The SPUR student will take a lead role in running experiments to measure chemical signatures emanating from a person carrying a simulated explosive device. The student will be mentored by faculty and graduate students. Our goal is to provide an effective research training environment, and to enable the student to actively participate in research activities.
 
Many national security agencies in the US are interested in the detection of chemicals indicating the presence of explosive threats. However, little is known about where, and how quickly, odors travel from person-borne sources into the environment. This project will evaluate how factors such as wind speed and odor source location affect PBIED plume dispersion in outdoor environments. Results from this effort will be used to inform protocols and technologies for the detection of explosive threats in national security contexts.
 
SPUR students will receive training on running instruments, acquiring, and processing data, and analyzing results. The student will attend weekly lab meetings to share progress and learn about other research projects. The student will also help provide content for a final report to the project sponsors.

Requirements:

  • The student should be eager to learn to use specialized instrumentation and to write simple computer code to acquire and process data. While we will provide active mentoring (our lab was previously recognized for outstanding SPUR mentoring), the student will also need to think and work independently. 
  • Experience with hands-on laboratory work, CAD and 3D printing, data processing and technical writing would be helpful. 
  • Course work related to fluid mechanics, heat transfer, and experimental methods is ideal but not required. 
  • Our lab is a fun and friendly place to work. We try to have flexible hours, to work in a team environment when appropriate, and to produce high-quality data sets and insightful analysis.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE)

Contact

John Crimaldi, Faculty
Email: crimaldi@colorado.edu

Aaron True, Faculty
Email: aaron.true@colorado.edu

Project Description

The Larson HVAC Lab is a facility dediated to conducting experimental research to make buildings more energy efficient, and consists of two test chambers, each with their own HVAC system. In collaboration with a graduate student, the project will involve specifying, installing, and using indoor environmental quality and energy monitoring sensors to connect to a digital twin of the facility. Sensor data will be used in thermodynamic modeling of the lab and to analyze the energy performance of the research facility to improve operations and building system control algorithms. This project will involve hands on training, learning about HVAC system sensing and controls programming, and collaborating with a graduate student who developed the digital twin, as well as with the lab manager.

Requirements:

  • Required: Basic understanding of environmental sensing and data analysis. Ability to navigate tight spaces. Willingness to be hands on with sensor testing and installation.
  • Preferred: Knowledge of controls or system dynamics. Interest in building system engineering and energy efficiency.

Project Website: http://larson-lab.com/

Desired Majors: Architectural Engineering, Civil Engineering, Electrical Engineering, Electrical & Computer Engineering, Environmental Engineering, Mechanical Engineering

Contact

Nicholas Clements, Faculty
Email: nicholas.clements@colorado.edu

Moncef Krarti, Faculty
Email: moncef.krarti@colorado.edu

Project Description

Climate change impacts on local environments are complex and often the intersection of many scientific and engineering disciplines. Stress on environmentally sensitive areas, native plant and animal species decline, and ever dwindling wildlife corridors and loss of suitable habitat create conflict when it comes to the protection of these areas and policymaking local governments. Students will focus on integrating field measurements with remote sensing for prediction of crop yield, drought, and stress on sensitive habitats, leading to better prediction and prevention of long-term climate change impacts. We will develop a novel portable multispectral sensing system that will provide high-spatial resolution soil moisture, plant stress, vegetation, wind speed and surface temperature data at low cost, minimal operational and training requirements. Satellite data and drone-based measurements will be used for validation and will be incorporated to select and monitor the areas of interest. Ways to engage the public will include creating a citizen science data collection component, providing access to low-cost DIY instruments and a friendly UI.

Requirements: 

  • Some field work will be required.

Project website: https://www.colorado.edu/center/spacegrant

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Biological Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Barbra Sobhani, Faculty
Email: barbra.sobhani@colorado.edu

Collette Wilfong, Faculty
Email: collette.wilfong@colorado.edu

Project Description

Monitoring of environmental conditions in harsh, remote environments presents an engineering challenge. Satellite monitoring gives some time lapse picture of conditions, but a higher resolution measurement strategy is important for gathering information related to specific species impacts or local variations. This project will test a small portable sensor array that collects useful environmental information such as CO2, light intensity, particle size and density, temperature, humidity, ozone, soil properties, and other information that is geotagged and transmitted to either a smartphone or a website for display. This instrument will be used in conjunction with NASA developed hand-help spectrometers to study local environments and engage community members in becoming more aware of their environment related to climate change.

Requirements:

  • Electrical engineering experience preferred.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Biological Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Barbra Sobhani, Faculty
Email: barbra.sobhani@colorado.edu

Collette Wilfong, Faculty
Email: collette.wilfong@colorado.edu

Project Description

GLEE is a scientific and technological mission that is developing small and inexpensive sensor packages (LunaSats) that can be deployed on the surface of the Moon, in order to provide a platform for students from around the world to actively do lunar science (https://www.glee2023.org/). Lunasats will be deployed as a mesh network for distributed sensing, using radio frequency (RF) for communication. They are based upon an easily accessible and open source architecture (Arduino) and standard sensors and preparing such systems for lunar deployment requires extensive testing. This phase of development is focusing on the reliability of the accelerometer for moonquake detection and the reliability of RF communication, requiring additional Lunasat production (v7.1). The science sub-team will comparing standard seismometers with the Lunasat detection network. GLEE is a unique opportunity for students to work on a lunar mission, developing and testing hardware to be flown on a lunar flight in 2028. GLEE provides access to undergraduate research that will be presented at a professional conference as well as a statewide undergraduate research symposium.

Requirements: None. 

Project website: https://www.glee2023.org/

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Barbra Sobhani, Faculty
Email: barbra.sobhani@colorado.edu

Collette Wilfong, Faculty
Email: collette.wilfong@colorado.edu

Project Description

GLEE is a scientific and technological mission that is developing small and inexpensive sensor packages (LunaSats) that can be deployed on the surface of the Moon, in order to provide a platform for students from around the world to actively do lunar science . Lunasats will be deployed as a mesh network for distributed sensing, using radio frequency (RF) for communication. They are based upon an easily accessible and open source architecture (Arduino) and standard sensors and preparing such systems for lunar deployment requires extensive testing. This phase of development is focusing on the reliability of the accelerometer for moonquake detection and the reliability of RF communication, requiring additional Lunasat production (v7.1). The software and data analysis sub-team will be working with science and avionics on our system. GLEE is a unique opportunity for students to work on a lunar mission, developing and testing hardware to be flown on a lunar flight in 2028. GLEE provides access to undergraduate research that will be presented at a professional conference as well as a statewide undergraduate research symposium.

Requirements: 

  • Software and data analysis experience.

Website: https://www.glee2023.org/

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Barbra Sobhani, Faculty
Email: barbra.sobhani@colorado.edu

Collette Wilfong, Faculty
Email: collette.wilfong@colorado.edu

Project Description

The SCOUT Mission represents a significant initiative in the domain of event-driven sensors, aiming to harness their potential for dynamic object tracking and enhancing space situational awareness aboard our 2U CubeSat. Our primary objective is to identify objects approaching commercial satellites and notify ground services by transmitting large streams of data, thereby advancing collision avoidance protocols that could play a pivotal role in the future of space exploration. We are looking for team members to assist in the creation of a software system to track and filter various orbital debris objects in Low earth orbit. This includes the usage of open cv and various other applications to create this code. The major aspect of the projects involves optimizing this code to work on low power circuit boards, in addition allowing for the manipulation of this system to track different objects for testing.

Requirements: None. 

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Barbra Sobhani, Faculty
Email: barbra.sobhani@colorado.edu

Collette Wilfong, Faculty
Email: collette.wilfong@colorado.edu

Project Description

GLEE is a scientific and technological mission that is developing small and inexpensive sensor packages (LunaSats) that can be deployed on the surface of the Moon or other planetary bodies, in order to provide a platform for students from around the world to actively do lunar science (https://www.glee2023.org/). Lunasats will be deployed using an autonomous rover, as a mesh network for distributed sensing, using radio frequency (RF) for communication. They are based upon an easily accessible and open source architecture (Arduino) and standard sensors and preparing such systems for lunar deployment requires extensive testing. This phase of development is focusing on prototyping and testing a robotic deployment system for the LunaSats. Students will work on adapting an autonomous rover, navigating with computer vision, to safely deploy the sensor network in a remote location.

Requirements: 

  • Experience with robotics and computer vision preferred.

Project website: https://www.colorado.edu/center/spacegrant

Hosting the following students:CU Boulder Student, Community College Student (from Colorado)

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering, Mechanical Engineering

Contact

Barbra Sobhani, Faculty
Email: barbra.sobhani@colorado.edu

Collette Wilfong, Faculty
Email: collette.wilfong@colorado.edu

Project Description

Honeybee hives have a special caste of bees that leave the hive to forage for food. When the forager bees return to the hive, they distribute this food to unfed bees using a process called "trophallaxis," which is the direct transfer of food between two bees. Using these local food exchange interactions, bees are able to spread food evenly throughout the entire hive, though there is no overall planning involved. Previous work has shown that bees use "scenting," directional propagation of pheromones, to communicate where they should aggregate to exchange food, however, the amount of food exchanged and the distance at which pheromones travel remains unknown. We aim to bridge this gap by collecting high resolution data on large groups of fed and unfed bees as they distribute food in experimental arenas. Using fluorescent dye to mark the food, will allow us to see how it is distributed. This project will focus on designing, building, conducting and analyzing experiments with honeybees, and the results will be used to improve models of food distribution in social insects.

Requirements: 

  • All majors will be considered, however, this project will primarily focus on designing and using experimental setups to study honeybee food distribution, collecting data from honeybees, scientific imaging, and computer vision.
  • Skill, experience, or interest in the following would be a good fit for the project: coding ability (i.e. python/c++/matlab), working with honeybees, data collection, and computer vision.
  • Experience with honeybees is not required, but students should be open to working with bees both in the lab and outdoors during the summer. All training and necessary equipment will be provided.

Project website: www.pelgelab.com

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering, Mechanical Engineering

Contact

Orit Peleg, Faculty
Email: orit.peleg@colorado.edu

Richard Terrile, Graduate Student
Email: rite5632@colorado.edu

Project Description

Many animals use signals with unique temporal patterns to choose mates and identify competitors. Fireflies flash, frogs croak, woodpeckers drum on tree trunks, and knifefish emit electric pulses. Although these signals vary substantially in form, they share a common underlying theme: all involve repeating a small set of discrete signaling elements in a pattern that is unique to each species, creating a biological equivalent of Morse code. In the Peleg Lab, we are investigating whether these different discrete animal communication systems might be shaped by universal principles from information theory and physics. To do this, we are generating a comparative dataset documenting signal characteristics across multiple animal groups. SPUR student researchers on this project will help generate this dataset by extracting signal parameters from a variety of species, e.g. via analysis of spectrograms and videos.

Requirements: None.

Project website: www.pelgelab.com

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering, Mechanical Engineering

Contact

Orit Peleg, Faculty
Email: orit.peleg@colorado.edu

Sandra Winters, Post Doc
Email: sandra.winters@colorado.edu

Project Description

Honeybee swarms are self-assembled, cohesive structures composed of a queen bee and several thousand workers. Together, the bees maintain thermoregulation, structural stability, and information flow while collectively selecting a future nest site. This project aims to understand how honeybee swarms assemble and disassemble without centralized control. Using multi-camera stereo imaging, we will track individual bees as they join or depart the swarm and to quantify changes in swarm morphology over time. We apply both traditional and deep-learning–based computer vision methods for detection, segmentation, and tracking of individual bees and the swarm as a whole. The project will involve designing, building, and conducting experiments with honeybees, as well as analyzing video data to connect individual bee behavior to swarm-level organization.

Requirements: 

  • Willingness to work outdoors conducting experiments with honeybees (no prior experience with honeybees required)
  • Basic familiarity with MATLAB and/or Python scripting
  • Experience with Arduino, prototyping (e.g., 3D printing, wood shop), electronics/sensors, and quantitative imaging is helpful but not required
  • Strong ability to work collaboratively in a team environment

Project website: www.pelgelab.com

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering, Mechanical Engineering

Contact

Orit Peleg, Faculty
Email: orit.peleg@colorado.edu

Danielle Chase, Post Doc
Email: danielle.chase@colorado.edu

Project Description

The Development, Education, and Learning (DEL) Lab investigates the cognitive processes that underpin how we learn new systems of information, such as language, mathematics, musical notation, and more. We use eye tracking to measure how attention, language, and sensorimotor processes are coordinated during learning in real-world educational settings. During Summer 2026, we will be focusing on collecting data at local preschools for a project investigating how children (ages 4-6) learn multi-digit numbers.
 
This project explores how children engage with different educational materials as they learn place-value principles (e.g., how we learn the difference between 27 and 72). In particular, we use eye-tracking to examine how different ways of presenting multi-digit-number information—such as spoken number names, visual symbols, and physical objects—shape children’s attention and learning processes on a moment-by-moment basis. Findings from this work have implications for early math instruction and the design of educational tools that align with children’s developing knowledge and attentional systems.
 
 
Students will be involved in multiple areas of the lab research, including:
 
- Assisting with data collection in preschool and after-school settings
- Receiving training to administer structured learning activities with children
-Supporting video, audio, and eye-tracking data processing
- Learning research methods in developmental and educational psychology
- Processing and analyzing behavioral and eye tracking data.
- Testing and helping to debug a multisensory learning application.
- Reading related literature and participating in lab discussions
- Contributing to a final presentation based on their summer research experience
 
Who would be a great fit:
We especially encourage students with prior experience working with children (e.g., babysitting, tutoring, camp counseling, classroom support) to apply. If Students have analysis and app development experience, they can contribute to those areas of research. No prior research experience is required; students will receive structured training and close mentorship throughout the summer.

Requirements:

  • We especially encourage students with prior experience working with children (e.g., babysitting, tutoring, camp counseling, classroom support) to apply.

Project website: https://www.colorado.edu/lab/del/

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering, Mechanical Engineering

Contact

Lei Yuan, Faculty
Email: lei.yuan@colorado.edu

Lucile Vleugels, Graduate Student
Email: luvl8876@colorado.edu

Project Description

The vision of this project is to develop 4D (space and time) machine learning representations for Earth Systems that ingest real-world observations from satellites and in-situ sensors (such as from float, profilers, underwater robots, ground sensors, and more) and are used for ecological monitoring applications. As part of this project, students will assist in developing AI/machine learning-ready datasets, and corresponding visualizations and evaluation pipelines, consisting of satellite and sub-surface ocean observations. This will allow researchers to train, test, and evaluate various aspects of large-scale geospatial AI technologies. Example data sources include NASA’s Sentinel-3, PACE, MODIS-Aqua, Landsat, and the World Ocean Database (including Argo floats, GO-SHIP, animal-based sensors, etc.).

Requirements:

  • Students should be well-versed in either Python and/or Javascript and interested in machine learning, ecology, and/or geospatial AI technologies.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Esther Rolf, Faculty
Email: Esther.Rolf@colorado.edu

Levi Cai, Post Doc
Email: levi.cai@colorado.edu

Project Description

Honeybees construct wax comb in a distributed fashion, with many bees building the structure simultaneously and without longterm planning. This results in irregular hexagons and topological defects in areas where unaligned comb is combined. Bees also display a strong preference for cells properly sized for specific goals, such as pollen or honey storage, or brood rearing. We will investigate how the comb is constructed over time using time series data of honeycomb built on 3D-printed experimental frames with a variety of foundation cell sizes to constrain early development. Previous research has revealed multiple strategies to adapt comb cell sizes, like merging, tilting, and layering. This project seeks to better understand how these strategies are employed in the day-to-day construction of honeycomb walls. This project involves consistent data collection from our outdoor apiary over the summer, image processing, data analysis, and some model development. The project will integrate concepts from computer science, physics, applied math, and engineering.

Requirements:

  • All majors will be considered, however, this project will primarily focus on experimental setups to study honeybee comb, collecting data from honeybbes, scientific imaging, and computer vision.
  • Skill, experience, or interest in the following would be a good fit for the project: coding ability (i.e. python/c++/matlab), working with honeybees, data collection, and computer vision.
  • Experience with honeybees is not required, but students should be open to working with bees both in the lab and outdoors during the summer. All training and necessary equipment will be provided.

Project website: www.pelgelab.com

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering, Mechanical Engineering

Contact

Orit Peleg, Faculty
Email: orit.peleg@colorado.edu

Richard Terrile, Graduate Student
Email: rite5632@colorado.edu

Project Description

This project will deal with the antenna measurements. Specifically, the student will work on the design and fabrication of an antenna test system to support the research in apertures on sea surfaces. The near- or far-field system will be designed, fabricated, and tested to validate it's performance.

Requirements: None.

Desired Majors: Electrical Engineering, Electrical & Computer Engineering

Contact

Dejan Filipovic, Faculty
Email: dejan@colorado.edu

Ljubodrag Boskovic, Graduate Student
Email: ljubodrag.boskovic@colorado.edu

Project Description

Photonic neuromorphic systems require an optically implemented neuron with a nonlinear transmission in the forwards direction and a gated transmission in the backwards direction needed for back propagation learning. We are implementing large parallel arrays of such neurons with a rectufying linear unit (ReLU) response using a liquid crystal on smart-pixel CMOS detector and electronic driver circuitry.

Requirements:

  • The student will help with CMOS circuit design and simulation so must have analog circuit and VLSI experience. In addition optical testing of the smart-pixel optical ReLU will be performed, so interest in photonics would be desirable.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Kelvin Wagner, Faculty
Email: kelvin@colorado.edu

Felicia Lee, Graduate Student
Email: felicia.li@colorado.edu

Project Description

Optical fiber is central to many applications in both research and industry. In the lab, this includes broadband laser generation, time transfer between optical clocks, and squeezed states of light. These techniques require knowing the fiber's dispersion, a material property that describes how light pulses propagate through them. During this project, the student will build a supercontinuum laser source and use it to measure the dispersion profile of several relevant types of fiber. The student will have the opportunity to learn about and perform techniques such as fiber splicing, interferometry, laser development, and nonlinear optics.

Requirements:

  • A class in waves and/or optics is required.

Desired Majors: Chemical Engineering, Electrical Engineering, Engineering Physics

Contact

Scott Diddams, Faculty
Email: scott.diddams@colorado.edu

Mike Wahl, Graduate Student
Email: mike.wahl@colorado.edu

Project Description

We are developing a C++ Open Radar Code Architecture (ORCA) that will allow researchers to rapidly prototype radar systems on Software Defined Radios (SDRs). The accepted students will work on a team to expand the current ORCA functionality with features such as new waveforms, faster data piping, GPS-stamping data, developing data writing standards, and adding support for additional SDRs. This work will streamline and speed up radar development efforts across the country.

Requirements: 

  • Students must have taken an Intro to C or C++ class such as ECEN 1310 or CSCI 1300.
  • In addition to submitting your SPUR application, fill out this questionnaire
  • We're looking for students who are excited to learn, thrive in a collaborative team environment, and are ready to take on new challenges!

Desired Majors: Computer Science, Electrical Engineering, Electrical & Computer Engineering

Contact

Nicole Bienert, Faculty
Email: bienert@colorado.edu

Zoe Worall, Graduate Student
Email: zoe.worrall@colorado.edu

Project Description

This project will involve the use of an FPGA-based RF System on Chip (RFSoC) for use in a radio-frequency (RF) transmitter. The research goal is to develop more linear power amplifiers (PAs) for 5G/6G wireless communications, without sacrificing energy efficiency or other RF performance metrics. The student researcher will develop code for the FPGA to receive, modify, and output signals from the PA in the transmitter. This signal manipulation will be used to detect and compensate for distortion generated by the nonlinear transistor in the PA. After the initial code development, the student researcher will have the opportunity to perform experimental testing on the RF hardware.

Requirements:

  • Familiarity with FPGA tools preferred.

Desired Majors: Aerospace Engineering Sciences, Computer Science, Electrical Engineering, Electrical & Computer Engineering

Contact

Taylor Barton, Faculty
Email: taylor.w.barton@colorado.edu

Osian Jones, Graduate Student
Email: osian.jones@colorado.edu

Project Description

We would like to recruit a few undergraduate students to help develop automated photonic integrated circuit characterization setups. The neural network will be built and trained using Python, then deployed using Moku:Pro (https://liquidinstruments.com/neural-network/) to achieve low-latency inference and react quickly to changing experimental conditions.

Requirements:

  • Experience in FPGA programming.
  • Experience in neural network.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Shu Wei Huang, Faculty
Email: shuwei.huang@colorado.edu

Project Description

The goal of this project is to characterize the time-domain switching behavior of a set of Schottky diodes to be incorporated on a reconfigurable metasurface. The requirement is to switch between on/off states faster than 1 GHz.  The diodes’ static electromagnetic responses have already been verified in simulation and measurement. A graduate student is designing a circuit for characterizing the diodes’ time-domain switching profiles. The role of the SPUR student will be to fabricate and test the circuit with the diodes in the lab using a high-bandwidth oscilloscope, and assist the graduate student with post processing and coming up with design modifications. The undergraduate will learn fundamentals of RF/high-speed design, PCB fabrication, assembly, and measurements with a final PCB prototype to show.

Requirements:

  • The student must be familiar with circuit design. ECEN 2250/2260 (i.e. Circuits 1 and 2) or equivalent are preferred but not necessary.

Website: www.scarboroughlab.com

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Mechanical Engineering

Contact

Cody Scarborough, Faculty
Email: cody.scarborough@colorado.edu

Alan Brannon, Faculty
Email: brannona@colorado.edu

Project Description

This project will convert the current benchtop Instant FLIM (https://opg.optica.org/optica/viewmedia.cfm?uri=optica-8-6-885) analog signal processing chain into a compact printed circuit board module that can be reliably integrated into a two-photon microscope. The student will help design the RF and baseband electronics that distribute the laser reference, generate phase-shifted channels, perform mixer-based demodulation, filter the outputs, and interface with a DAQ for simultaneous multi-phase acquisition and real-time lifetime computation. Typical tasks include schematic capture and PCB layout with controlled impedance routing, selecting and characterizing RF components, assembling and testing prototypes, developing a simple calibration workflow for phase and gain mismatch, and validating lifetime imaging performance on microscope data.

Requirements:

  • Demonstrated expertise in PCB design and RF electronics is required. 
  • The student should be proficient with schematic capture and PCB layout tools, comfortable with transmission-line and impedance-matching concepts, and experienced with RF lab equipment, including oscilloscopes, spectrum analyzers, network analyzers, and signal generators. 
  • Consistent weekly lab availability and strong troubleshooting skills are required.

Website: https://boltslab.org/

Desired Majors: Biomedical Engineering, Chemical Engineering, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Yide Zhang, Faculty
Email: yide.zhang@colorado.edu

Project Description

Many important decisions in engineering, data science, and operations are made by solving optimization problems. These problems take inputs, such as system conditions, demand, or uncertainty, and produce decisions that must satisfy strict constraints. While optimization methods are reliable, repeatedly solving these problems can be slow, which motivates the use of machine learning to approximate their behavior.
 
This project explores how machine learning can be used to learn decision rules that approximate optimization-based decisions, and why this works well in some cases but poorly in others. The goal is not only to build fast learning-based models, but also to understand their limitations and design simple, reliable, and interpretable alternatives.
 
Two undergraduate students will work on complementary projects under this shared theme. Each student will have a clearly defined role and will contribute a distinct piece to the overall research effort.
 
Project A: Understanding When Optimization-Based Decisions Are Easy or Hard to Learn
 
Description:
This project focuses on understanding when machine learning models can accurately reproduce the decisions produced by optimization models, and when they struggle to do so. The student will generate datasets by repeatedly solving optimization problems under varying inputs or parameters and will train learning models to predict optimal decisions directly from these inputs. By systematically evaluating learning performance across different operating conditions, the student will identify patterns that help explain why learning succeeds in some cases and fails in others. Understanding these limits is important for determining when learning-based decision models can be trusted and when optimization-based methods remain necessary.
 
In this project, the student will contribute to the overall research effort by:
- Generating and curating datasets from optimization-based decision models
- Training and evaluating machine learning models of varying complexity
- Measuring learning performance in terms of decision accuracy, robustness, and generalization
- Identifying regimes or conditions under which learning becomes unreliable
- Developing intuitive explanations for observed success and failure modes
 
This project provides the diagnostic foundation for the overall effort by clarifying where learning-based decision-making is appropriate and where its limitations arise.
 
Project B: Interpretable Learning for Constrained Decision-Making
 
Description:
This project focuses on learning simple and interpretable decision rules, such as linear decision rules, that approximate optimization-based decisions while remaining transparent and analytically tractable. The student will investigate how structural properties, such as sparsity, influence performance, feasibility, and robustness, and how these learned structures connect to the underlying optimization problem. Interpretable decision rules are important because they allow practitioners to understand, trust, and verify learning-based decisions in safety- and constraint-critical settings.
 
In this project, the student will contribute to the design of transparent and reliable decision models by:
- Implementing structured decision rules (e.g., linear or sparsity-promoting models)
- Analyzing how optimal decisions depend on problem parameters and inputs
- Studying the role of sparsity and bias terms in interpretability and robustness
- Comparing structured decision rules against more expressive, black-box learning models
 
This project emphasizes clarity, insight, and reliability over black-box accuracy, and is well-suited for students interested in optimization, applied mathematics, and interpretable machine learning.

Requirements:

  • Completion of at least one course involving linear algebra, optimization, data science, or machine learning (can be in progress)
  • Programming experience in Julia, Python, MATLAB, or a similar language

Desired Majors: Applied Mathematics, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics

Contact

Gonzalo Constante, Faculty
Email: gonzalo.constante@colorado.edu

Andre Quisaguano, Graduate Student
Email: andre.quisaguanoparedes@colorado.edu

Project Description

You will design and build a simple ESP32 based system to automatically characterize the performance of a power supply. The project will be prototyped in a solderless bread board and then turned into a circuit board. This involves writing some code in the Arduino IDE to control a circuit, measurements, analyze the results and present them in graphical form. Some phyton or Jupyter notebooks may be required. There will be at least one publication from this project.

Requirements: 

  • No requirements except an interest in circuits, and physical computing with microcontrollers

Desired Majors: Aerospace Engineering Sciences, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Integrated Design Engineering (IDE)

Contact

Eric Bogatin, Faculty
Email: eric.bogatin@colorado.edu

Melinda Piket-May, Faculty
Email: melinda.piket-may@Colorado.edu

Project Description

This project aims to develop the understanding of large protected quantum circuits by using numerical methods to simulate their energy structure and quantum gates. The project will involve analytical calculation and numerical simulation using the Python language. At the end of the project, the goal is to understand how the wavefunctions of large quantum circuits behave and determine whether these circuits can be used as qubits with intrinsic error protection.

Requirements:

  • Strong understanding of quantum mechanics.

Desired Majors: Applied Mathematics, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics

Contact

Andras Gyenis, Faculty
Email: andras.gyenis@colorado.edu

Kamal Sharma, Post Doc
Email: Kamal.Sharma@colorado.edu

Project Description

My lab has developed a specialize shield, compatible with a variety of microcontrollers that enables high performance measurements such as microvolt level signals, high accuracy signal frequencies and stimulus response analysis of sensors and systems. This project will be to exercise this shield to explore a variety of applications. There will be some code to write in the Arduino IDE or Jupyter notebooks to take the measurements, perform analysis and present the results in graphical form. This project will emphasize measurement automation and analysis of the results.

Requirements:

  • Some experience with the Arduino IDE, interest in circuits and physical computing.

Desired Majors: Biomedical Engineering, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Integrated Design Engineering (IDE)

Contact

Eric Bogatin, Faculty
Email: eric.bogatin@colorado.edu

Melinda Piket-May, Faculty
Email: melinda.piket-may@Colorado.edu

Project Description

Synthetic biology has the potential to lead to new or more efficient production of medicines, fuels, and other important compounds. Crucial to the success of synthetic biology is effective standards for the storage and sharing of genetic design knowledge between researchers and institutions. This project will develop SynBioHub3, an interactive data repository that will accelerate the pace of discovery and innovation for this critical emerging field. The SPUR student on this project will contribute to the development of SynBioHub3.

Requirements:

  • Experience with programming with Python, Java, and/or Javascript would be beneficial.

Project website: http://geneticlogiclab.org/

Desired Majors: Applied Mathematics, Biological Engineering, Biomedical Engineering, Computer Science, Electrical Engineering, Electrical & Computer Engineering

Contact

Chris Myers, Faculty
Email: chris.myers@colorado.edu

Daniel Fang, Graduate Student
Email: daniel.fang@colorado.edu

Project Description

Synthetic biology research has led to the development of many software tools for designing, constructing, editing, simulating, and sharing genetic parts and circuits. Among these tools are SBOLCanvas, iBioSim, and SynBioHub, which can be used in conjunction to create a genetic circuit design following the design-build-test-learn process. However, although automation works within these tools, most of these software tools are not integrated, and the process of transferring information between them is a very manual, error-prone process. To address this problem, this work automates some of these processes and presents SynBioSuite, a cloud-based tool that eliminates many of the drawbacks of the current approach by automating the setup and reception of results for simulating a designed genetic circuit via an application programming interface. The SPUR student on this project will be adding new features to the SynBioSuite tool to enable wider support of modeling and analysis capabilities.

Requirements:

  • Programming experience with languages such as Python, Java, and Javascript would be beneficial.

Project website: http://geneticlogiclab.org

Hosting the following students:CU Boulder Student, Community College Student (from Colorado)

Desired Majors: Applied Mathematics, Biological Engineering, Biomedical Engineering, Computer Science, Electrical Engineering, Electrical & Computer Engineering

Contact

Chris Myers, Faculty
Email: chris.myers@colorado.edu

Gonzalo Vidal, Post Doc
Email: gonzalo.vidalpena@colorado.edu

Project Description

In this project, a 10 GHz test platform for computing the response of dielectric materials will be adapted to obtain the effective properties of patterned PCBs. The metallic patterning on the PCB will be designed by the SPUR student to exhibit a so-called anisotropic response (i.e. a material whose wave-speed depends on the polarization of the applied field). The SPUR student will work alongside a graduate student who has already built an enclosed waveguide material tester. Together they will expand the design to identify the full effective permittivity tensor of a metamaterial. Students will gain direct experience working with EM solvers like Ansys HFSS and using microwave test equipment such as a vector network analyzer and waveguide passive components.

Requirements:

  • ECEN 3400 (Electromagnetic Fields 1) or equivalent.

Website: https://www.scarboroughlab.com

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Mechanical Engineering

Contact

Cody Scarborough, Faculty
Email: cody.scarborough@colorado.edu

Project Description

Due to warmer summer conditions the concentrations of acidity and trace metals have been increasing in the drainage from mineralized areas in the Colorado Rockies. When these metals enter streams, the iron and aluminum can precipitate on the streambed and impair the habitat for aquatic biota. The dissolve trace metals can be directly toxic to algae and fish. The student will work with a graduate student to analyze the diatoms that are in a sediment core that our research team collected from Grizzly Reservoir in the Lincoln Creek watershed, located near Aspen. This reservoir has been receiving both acid rock and acid mine drainage since its construction in 1936. Diatoms are a type of algae that have a siliceous shell that is preserved in the layers of the reservoir sediments. Thus, the diatoms can be identified microscopically to see how the types of diatoms changed as the concentrations of metals increased. The student will learn to recognize different diatoms and prepare samples for microscopic analysis. The student may have the opportunity to go to the field site to support ongoing field study.

Requirements: 

  • The student must have taken environmental microbiology or applied ecology, or have a comparable background.
  • The student must be able to work in 4-5 hour blocks in the lab.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Engineering Physics, Environmental Engineering, Mechanical Engineering

Contact

Diane McKnight, Faculty
Email: diane.mcknight@colorado.edu

Blanca Hinojosa, Graduate Student
Email: Blanca.Hinojosa@colorado.edu

Project Description

Due to warmer summer conditions the concentrations of acidity and trace metals have been increasing in the drainage from mineralized areas in the Colorado Rockies. When these metals enter streams, the iron and aluminum can precipitate on the streambed and impair the habitat for aquatic biota, especially stream insects, such as mayflies and stoneflies. The dissolve trace metals can be directly toxic to these insects. As part of an ongoing study of these impacts in the Lincoln Creek watershed near Aspen, CO, the student will participate in the collection of these insects at several sites and at sites in a reference unimpacted stream. The student will learn about benthic insects and prepare the samples for analysis of the trace metal and rare earth element content of the insects. The student will then analyze the results in comparison to the concentration of these metals and rare earth elements in the stream water.

Requirements:

  • The student must have taken environmental microbiology or applied ecology, or have a comparable background.
  • The student must be able to work in 4-5 hour blocks in the lab.
  • The student also must be able to go to the field to collect samples on all day or overnight sampling trips.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Engineering Physics, Environmental Engineering

Contact

Diane McKnight, Faculty
Email: diane.mcknight@colorado.edu

Analiese Terrell, Graduate Student
Email: Analiese.Terrell@colorado.edu

Project Description

Our project focuses on the critical role of engineering in maintaining water quality for public health through innovative disinfection methods. Specifically, we aim to study the impact of UV irradiation for drinking water treatment and water distribution systems. This research investigates how different light wavelengths can improve disinfection of bacterial biofilms within water distribution networks.
The student will work alongside a PhD student and develop their own research involving setting up and running bench scale experiments simulating UV treatment of drinking water as well as assist with standard microbiology lab methods such as culture techniques. An interest in microbiology, drinking water, and treatment systems is essential; prior lab experience is preferred but not required. This project integrates microbiology and engineering to demonstrate the feasibility of UV-based purification in water treatment plants, offering participants hands-on experience in improving water treatment systems while contributing to public health advancements.

Requirements:

  • An interest in microbiology, drinking water, and treatment systems.
  • We are looking for long-term students for our laboratory.

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Creative Technology & Design (CTD), Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Karl Linden, Faculty
Email: karl.linden@colorado.edu

Melanie Gamboa, Graduate Student
Email: melanie.gamboa@colorado.edu

Project Description

The student will assist with building, testing, and deploying low-cost air quality sensors to monitor methane emissions at a Colorado landfill. The project includes hands-on lab work, field deployment, and data analysis and visualization, providing practical experience in environmental monitoring, sensor technology, and air quality research.

Requirements:

  • Work in person
  • Know Python/Matlab
  • Availability to travel (Colorado)

Project website: https://www.colorado.edu/lab/hannigan/lab-technology

Desired Majors: Aerospace Engineering Sciences, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Michael Hannigan, Faculty
Email: Michael.hannigan@colorado.edu

Gabriela Cortes, Graduate Student
Email: Gabriela.cortes@colorado.edu

Project Description

This project investigates the career readiness competencies (CRCs) that predicate effective mechanical engineering practice and examines how these competencies develop prior to senior capstone design. The National Association of Colleges and Employers (NACE) defines career readiness as the “core competencies that broadly prepare the college educated for success in the workplace and lifelong career management”. By extension, CRCs in engineering are the situated professional knowledge, skills, and attitudes essential for success in both capstone design and early career engineering contexts.
 
Across engineering education literature, different terminologies are used, such as soft skills, professional skills, non-technical skills, employability traits, and behavioral attributes. Although this diverse terminology signals broad agreement that engineers require skills beyond technical expertise, it has also contributed to positioning these abilities as supplemental or secondary. Several scholars critique this framing, noting that descriptors such as soft, non-technical, or add-on implicitly suggest that these capabilities are optional rather than integral to engineering practice. However, in our project, we acknowledge the central role of CRCs in preparing engineers to navigate complex workplaces and systems, collaborate across diverse contexts, respond responsibly to societal needs, and creating a fulfilling engineering career.
 
This project involves studying the development of CRCs in undergraduate education, with a focus on preparing students for senior capstone. Working closely with the P.I. and graduate students, the researcher will support the analysis of survey and interview data gathered over the 2025-2026 academic year.

Requirements:

  • This project does not have specific requirements, however students with experience and special interest in areas emphasized in the NACE Career Readiness framework will be strongly considered: https://www.naceweb.org/docs/default-source/default-document-library/2025/career-readiness/competencies/nace-career-readiness-competencies-december-2025.pdf?sfvrsn=a8abf91a_3

Project website: https://www.burleson-globaldesign.com

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Grace Burleson, Faculty
Email: grace.burleson@colorado.edu

Project Description

As the world is impacted by global crises such as natural disasters, conflicts, and pandemics, there has been a shifting culture in engineering, highlighting the importance of social responsibility and ethical decision-making, alongside technical competence in addressing these humanitarian crises. When engaging in humanitarian work, engineers are often designing for communities living around the world in different contexts from their own, making empathy a crucial skill to design appropriate solutions.
 
This project focuses on developing and assessing workshops for students that introduce “empathy” in engineering, and explore how it applies to design. Our prior work has implemented a workshop that engages students through design challenges and scenario-based activities to practice making design decisions, considering both the social and technical implications of their design. During this workshop, we facilitated group discussions on different components of empathy to reflect on their design decisions.
 
The student on this project will assist a graduate student in expanding our current workshop, and developing a second follow-up workshop. Their responsibilities will include conducting a brief literature review and creating new design challenges and activities to explore components of empathy. The student will have the opportunity to pilot the workshop at the end of the summer for some preliminary data collection, and potentially present the workshop in first-year class in Fall 2026.

Requirements:

  • No specific requirements, however experience in human-centred design, inclusive design, or engineering ethics courses is preferred (e.g., completion of Dr. Tsai's Design for Inclusion course, Herbst ethics/leadership courses).

Desired Majors: Aerospace Engineering Sciences, Applied Mathematics, Architectural Engineering, Biological Engineering, Biomedical Engineering, Chemical Engineering, Civil Engineering, Computer Science, Creative Technology & Design (CTD), Electrical Engineering, Electrical & Computer Engineering, Engineering Physics, Environmental Engineering, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Grace Burleson, Faculty
Email: Grace.Burleson@colorado.edu

Julianne Attai, Graduate Student
Email: julianne.attai@colorado.edu

Project Description

The cardiovascular disease is the number one killer in the United States and many other developed countries. Vascular implants play a critical role in the contemporary management of a wide range of clinical conditions, including atherosclerosis, aneurysm, congenital malformation, vasculitis and stroke. The use of synthetic polymer for vascular implant fabrication, however, has been associated with thrombosis and intimal hyperplasia, resulting from platelet accumulation, blood clotting and tissue overgrowth, respectively. Therefore, there remains a substantial unfulfilled need for regenerative materials that provide long-term patency of vascular implants. Herein, we are developing regenerative multilayered vascular implants or implant coatings made of electrospun co-axial nanofibers. Building on our existing fabrication process, we are further examining how several manufacturing parameters influences implant materials properties, which are important for the preclinical translation. In particular, the addition of an amphiphilic stabilizer and anticoagulants are being explored for their respective impact on increasing the layer adhesion and hemocompatibility performance of implant materials. This project involves biomechanical, cellular and in vivo evaluations of these newly developed vascular implants.

Requirements:

  • Student must have taken a biomaterials or biochemistry or physiology or an equivalent course, have a good class standing, and be available to work in 6-hour blocks.

Desired Majors: Aerospace Engineering Sciences, Biological Engineering, Biomedical Engineering, Chemical Engineering, Creative Technology & Design (CTD), Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Wei Tan, Faculty
Email: wtan@colorado.edu

, Graduate Student
Email: 

Project Description

Cardiovascular diseases, particularly coronary heart disease and atherosclerosis, remain the leading cause of morbidity and mortality worldwide, underscoring the need for more effective and predictive therapeutic strategies. This project aims to develop a machine learning–assisted platform for vascular materials design by integrating artificial intelligence, multifunctional biomatrix engineering, and high-throughput matrix screening. The platform will enable systematic and interactive exploration of complex design spaces, incorporating material composition, structure and mechanics, biomolecular functionalization, and disease-relevant biophysical and biochemical environments, while linking these inputs to disease stage-specific cellular responses such as inflammation, proliferation, and functional loss. By embedding machine learning into human cell–based experimental models, this approach will move beyond trial-and-error experimentation to enable rapid optimization and validation of regenerative vascular implant materials. Ultimately, the technology will accelerate therapeutic biomaterials discovery at lower cost and higher predictive power, advancing the translation of innovative vascular treatments from laboratory design to patient care.

Requirements:

  • Student must have taken a biomaterials or biochemistry or physiology or an equivalent course, have a good class standing, and be available to work in two 5-hour blocks,

Desired Majors: Biological Engineering, Biomedical Engineering, Chemical Engineering, Computer Science, Creative Technology & Design (CTD), Engineering Physics, Integrated Design Engineering (IDE), Mechanical Engineering

Contact

Wei Tan, Faculty
Email: wtan@colorado.edu

Anh Thy Nguyen, Graduate Student
Email: anng8974@colorado.edu