Admissions Information

Learn more about the department's admissions process, including our response to COVID-19 and opportunities for diverse students.

Graduate Admissions Details

Thank you for your interest in computer science graduate studies at CU Boulder. The following faculty members and degree programs are recruiting new master's and PhD students for fall 2022. Explore opportunities in computer science education and research at CU Boulder, and learn more about what student life is like in the department.    

 

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Faculty, Labs and Research Groups

Interdisciplinary Wireless Research Lab

Spectrum Sharing for a National Radio Dynamic Zone (NRDZ) video (2021)

IWR Lab Overview Video

The Computer Science Department Interdisciplinary Wireless Research Lab focuses on Proximity Wireless Network Communications fundamental and applied research with an emphasis on the 3GPP LTE/5G and IEEE 802.11 Wi-Fi protocols.

The application emphasis is for the support of space agency (NASA, ESA, JAXA, CSA, DLR, CNES, etc.) human exploration missions and for Public Safety. Activities include fundamental research in PHY layer transmission optimization for range and throughput, the application of AI/ML for multi-layer optimization, and the development of a general solution and architecture for Dynamic Spectrum Sharing (DSS). Applied research focuses on standards (CCSDS) specification development and interoperability testing.

NALA / Natural Language Processing

Pre-research advising session video (2021)

NALA Overview Video

We will mainly be recruiting students with a degree in computer science, linguistics, or maths, but might consider students from other backgrounds on a case-by-case basis.

At NALA, we develop computational models for the understanding and generation of natural language.

Our current areas of interest include multilingual natural language processing, transfer learning, natural language processing for educational applications, computational morphology, low-resource machine translation, and language grounding. 

That Recommender Systems Lab

Pre-research advising session and recruitment event Video (2021)

Professor Robin Burke is seeking students with research interests at the intersection of algorithmic fairness and machine learning, specifically in the area of recommender systems/personalization. Interest in computational social choice would be plus.

That Recommender Systems Lab investigates recommender systems and other personalized systems, especially as these systems are deployed in complex and socially-sensitive settings, such as philanthropy, news and employment. Our current projects center on multistakeholder recommendation, and in particular, fairness-aware recommendation. We invite applications for funded PhD positions in the area of recommender systems fairness, including both computational and qualitative/HCI approaches. Applicants from groups traditionally underrepresented in computing are encouraged to apply

CU Programming Languages and Verification (CUPLV) Group

CUPLV video (2020)

CUPLV consists of about nine faculty and their graduate students working across such diverse areas as secure cyber-physical systems, provably-correct reinforcement learning, automatic theorem-proving, and verifiable distributed systems. 

Hybrid Control Systems Lab

Majid Zamani Pre-research advising video (2020)

Assistant Professor Majid Zamani's lab is focused on the formal verification and synthesis of autonomous systems.

Foundations of Autonomous Systems Lab

Pre-research advising session video (2020)  Download the Pre-research advising session slides

The Foundations of Autonomous Systems lab works on a mix of theory and applications of autonomy. 

Autonomous systems like self-driving car, artificial pancreas system or autonomous robots are prevalent in everyday world. How do we assure safety? From the theoretical side, we are looking into symbolic logics, automata theory and application of ideas from control theory to verifying properties of these self-governing systems. From the practical side, we engage a variety of researchers from robotics, aerospace engineering, cognitive science and endocrinology to help understand the application of these theoretical ideas to proving correctness of real systems. 

Physical Prediction, Inference, and Design Group

The Physical Prediction, Inference and Design group develops methods and community software for solving arising in physical and engineering sciences.

Much of this work has an element of high-performance/parallel computing and numerical analysis to design robust methods and implementations. The research is usually interdisciplinary and collaborative in the sense that group members take classes and engage significantly outside the CS department (e.g., Earth sciences, materials science, aerospace) so as to develop durable, sustainable solutions at appropriate levels of abstraction.

CU Systems Lab

Computer Systems Lab video (2020)

The Computer Systems Lab at CU consists of about 14 faculty whose expertise generally lies in building practical computer systems.

Most of the Systems faculty are co-located in a single large lab with their students. Students and faculty receive funding for and work in areas including large scale network systems; cloud and edge computing; distributed systems; virtualization; wireless and mobile systems including IoT, drones, and sensors; privacy preserving networks; network security and anticensorship; computer architecture security; autonomous and software-defined networks; automotive and telematics systems; social computing; data analytics; distributed and embedded machine learning and computer vision; and cybersafety and cyberbullying. 

SHINE Lab & HCI Research in the NSF Institute for Student AI-Teaming

SHINE Lab Overview Video

SHINE Lab's research explores the use of non-invasive brain measurement to passively classify users’ social, cognitive and affective states in order to enhance usability testing and the design of adaptive systems design.

The HCI Research in the Institute for Student AI-Teaming is focused on orchestrating successful student and teacher interactions with AI. We work primarily with functional near-infrared spectroscopy (fNIRS), a relatively new non-invasive brain imaging device that is safe, portable, robust to noise, which can be implemented wirelessly; making it ideal for research in human-computer interaction. The high density fNIRS equipment in the SHINE lab provides rich spatio-temporal data that is well suited as input into deep neural networks and other advanced machine learning algorithms. Our interdisciplinary research draws from areas such as neuroscience, psychology, human-computer interaction, and human factors. We also use machine learning and reinforcement learning for predicting social, cognitive, affective states (like workload, trust, frustration), and for building AI systems that react ‘appropriately’ to a human’s mental state. Ultimately our research aims to improve human performance during human-computer interactions and in the human-agent teaming domain.

Image and Video Computing Group

December 2: CS pre-research advising session

Image and Video Computing Video

We are recruiting PhD students!

Our aim is to create computing systems that enable and accelerate the analysis of visual information, as a critical precursor to discoveries and innovations that can benefit society at large.

Our research involves computer vision, machine learning, crowdsourcing, human computation, human-computer interaction, accessibility, and (bio)medical image analysis.

Living Matter Lab

November 17: CS pre-research advising session

Living Matter Lab Overview Video

We are looking for students with backgrounds in Biology, Biochemistry and BioComputing/BioInformatics.

The Living Matter Lab investigates the extent to which we can change healthcare to make it a personal process.

The research focuses around microfluidic biochips, devices that enable direct interaction of humans with their microbiome for diagnosis purposes. So far, we have built systems based on biochips to serve as personal laboratories: small portable devices that people can own and use to develop customized bio-protocols ("bio-apps").

The Layer Lab (Computational Biology)

Rapid Structural Variant Visualization with samplot presentation video

The Layer Lab develops algorithms for large-scale genomic data exploration in a range of populations, from sick kids to wildlife populations.

Boulder Computer Architecture Research Lab

We are looking for people with background in either computer architecture, security, or information theory.

We are working on the intersection of computer architecture and security. Specifically we are looking to incorporate security metrics into a processor simulator, as well as develop a security focused benchmark suite.

Theoretical Computer Science Group

Theory Group Overview Video 

CCC Symposium (2017): Poster Session with Rafael Frongillo

Our faculty and students research all aspects of theoretical computer science, from core areas such as algorithms, complexity, and cryptography, to connections with other fields such as machine learning, algebraic geometry, economics, dynamical systems, biology, and control theory.  

Emotive Computing Lab

Emotive Computing Lab Overview video

Our research is at the intersection of the cognitive, affective, computing, and learning sciences. Specific interests include affective computing, social signal processing, intelligent learning environments, speech and language processing, human-computer interaction, and multimodal machine learning.

We are interested in the dynamic interplay between cognition and emotion while individuals and groups engage in complex real-world tasks. We apply insights gleaned from this basic research program to develop intelligent technologies that help people achieve to their fullest potential by coordinating what they think and feel with what they know and do.

Eric Wustrow

If you have an interest in learning more about how network technologies can be used to directly improve peoples' lives around the world, please apply or reach out!

I do research on computer and network security, with a focus on censorship circumvention. We have been researching and building new kinds of circumvention proxies, and deploying them to the real world to be used by people in censoring countries.

Systems research with Shiv Mishra

Shiv Mishra pre-research advising presentation (2020)

I have multiple openings for Ph.D. students in the areas of edge computing, mobile and pervasive computing, IoT, cybersafety and social computing. Please check out my current research on my webpage and then contact me.

Danny Dig

Code migration for ML-based software video

I’m looking for students who are excited to work at the intersection of Software Engineering tools for ML and Data Scientists.

It is widely known that at least two-thirds of software costs are due to evolution, with some industrial surveys claiming 90%. ML software and models need to evolve to respond to internal & external changes.

An important example of evolution is to migrate code to use the newer version of ML libraries or to optimize performance. Due to many non-backwards- compatible API changes, this often requires engineers to rewrite their code & models from scratch. Our goal is to mechanize such tasks that are expensive, time-consuming, and error- prone. We first automatically mine evolutionary code changes from a wide repository of open-source ML codebases. Grounded on these formative studies, we will design, implement, and evaluate refactoring tools to help engineers evolve their codebases safely and effectively.

Gowtham Kaki

My research is driven by the curiousity to apply PL and FM way of thinking to solve hard problems in other domains of Computer Science, such as Distributed Systems, Databases, and Artificial Intelligence.

In my current research, I am exploring how provably-correct and scalable distributed applications can be built with least amount of programming effort. The research has practical implications to the up and coming area of decentralized trustless computing.

 

Degrees and Admissions

MS Degrees Overview

  • Host: Rajshree Shrestha

October 12,13, 14: Masters in CS General Info Sessions (2021)

View the Presentation Slides (2020)

Join Graduate Program Manager Rajshree Shrestha to learn more about the Master of Science degrees offered in the department. 

Also, check out our list of pre-advising sessions!

PhD Degree Overview

  • Host: Rajshree Shrestha

November 1: Computer Science PhD Info Session 

View the Presentation Slides (2020)

Learn more about pursuing a PhD in computer science at CU Boulder. 

Master's in Network Engineering Overview

  • Host: Levi Perigo

October 15: Network Engineering Info Session

November 9, 19: Network Engineering Info Session

Watch the Recorded Session (2020)

Join Scholar in Residence Levi Perigo to learn more about our master's in network engineering. 

Master's in Technology, Cybersecurity & Policy Overview

  • Host: James Curry 

October 14: Technology, cybersecurity and policy general info session

November 9, 19: Technology, Cybersecurity and policy general info sessions

From security-minded business and policy leaders to technical cybersecurity professionals, over 17,000 positions paying three times the national median salary remain unfilled in Colorado, with many more globally. The master’s in TCP will prepare you for these roles regardless of your background.

You will learn how to defend people, organizations and nations from adversaries. You will be equipped with the best methods, technologies and strategies to assess threats, mitigate vulnerabilities and understand complex systems and policies. Adversarial thinking, professional communication and critical problem solving will be central to your education.

Master's in Data Science Overview

  • Host: Jane Wall 

October 14: Master's in Data Science Overview

Watch the Recorded Session (2020)

Learn more about the campus' Professional MS in Data Science with on-campus and coursera options. 

Hear from Current PhD Students

  • Hosts: Ananya Ganesh and Michael Hoefer

Watch the Recording  View the Presentation Slides

Get advice on your PhD application, directly from two current computer science PhD students! 

What Are Professors Looking For?

  • Host: Dan Larremore

Watch the Recorded Session

Join computer science and BioFrontiers Assistant Professor Dan Larremore for a discussion of how to choose good research questions, as well as what faculty are looking for in PhD or postdoc applicants. 

PhD Application Tips

  • Host: Casey Fiesler 

Watch the Videos

Casey Fiesler, assistant professor in information science and computer science, shares her advice on how to choose the PhD program that's right for you, tips on writing a good statement of purpose and more in this YouTube playlist. 

CS Alumni Series

CS Alumni Series Video Playlist: Fall 2021

CS Alumni Calendar Events

These are the recording of talks given as part of our alumni series where folks share their experiences on how they applied for internships/jobs and how they reached where they are today!