Congratulations to more than a dozen CU Engineering students for earning a major National Science Foundation fellowship.
The NSF Graduate Research Fellowship Program (GRFP) recognizes outstanding graduate students from across the country in science, technology, engineering and mathematics (STEM) fields. The initiative is recognizing 13 current students and 2 incoming students with majors from across the College of Engineering and Applied Science as 2018 honorees. Each will receive a $34,000 annual stipend for the next three years as well as professional development opportunities.
“The outstanding students selected for these graduate fellowships represent the next generation of science and technology leaders," said college of engineering Dean Bobby Braun. "They have passions across the spectrum of engineering and are advancing the kind of impactful interdisciplinary research that our college and university are known for."
This year, NSF received over 12,000 applications and made 2,000 award offers to students nationwide.
Advisor: Allie Anderson
Research: Boppana is completing his first year as a PhD student in Aerospace Engineering Sciences at the University of Colorado Boulder, with an emphasis in Bioastronautics. His research has included work to develop a wearable contact pressure sensor system for injury monitoring inside spacesuits. His other research interests include biomechanical modeling, developing wearable sensors, using computer vision techniques to model the human body, and using virtual reality to study human factors
Major: Computer Science
Advisor: Paul Constantine.
Research: There has been great progress in modeling biological and engineering systems using mathematics. We can describe the process of combustion in a jet engine, the spread of a flu epidemic, and the development of a tumor using well-developed equations. These models enable us to conduct computational experiments, predict future events, and gain discipline-specific insights. Oftentimes such models are dependent on many parameters -- if we are modeling the growth of a tumor, for example, are the parameters that most affect its size on the first day of development different from those on the 20th day? Answering such questions could lead to new drug development, new treatment programs, and more advanced models. In my research I develop mathematical methods for answering such questions and giving insight into the time-dependent sensitivity of models to their parameters.
This summer I begin research with Dr. Marco Pavone in the Aerospace Engineering department at Stanford. We will be developing mathematical models that measure the societal impact of self-driving cars. This research has potential to rigorously prepare society for the advances of artificial intelligence (AI), to enable informed policy decisions that incorporate the impact of AI on our jobs, economy, neighborhoods, and public transportation, and to responsibly understand the impacts of our technology advances.
Research: I have worked on creating novel large eddy simulation models and discretization techniques for turbulent fluid flows. These flows appear in a wide range of applications, but are very difficult to simulate. The techniques I have been developing have the potential to improve both the accuracy and realm of applicability of large eddy simulation. In the future I plan on further refining these methods to quantify the uncertainty present in the predictions of fluid behavior, which will hopefully lead to better engineering design of fluid systems.
Research: My research revolves around the design and analysis of optimal algorithms that find keywords within text-based data. Additionally, I hope to expand on my work by developing probabilistic techniques to characterize the frequency such keywords occur within a text. These findings could potentially give rise to new methods for studying patterns within DNA.
Research: I use CHEMKIN simulations to study the chemical kinetics of combustion and reacting flows in various systems like an engine. This provides better understanding of the complex chemistry associated with specific fuels and environments and helps predict important system parameters such as ignition delay. In the future I hope to combine the chemistry and physics of combustion to better predict the performance of alternative jet fuels in a variety of conditions.
Research: My research is focused on the autonomous navigation of robots in deformable environments through visual feedback and the dynamic modeling/mapping of these environments. I plan to apply this research to medical devices and procedures.
Research: The evolution of pathogenic bacteria to resist known antibiotic drugs poses an ever-increasing threat to the world’s health and economic wellbeing. My research focuses on confronting these organisms via the development of novel pharmaceuticals and biomolecular diagnostic methods. Nanotherapeutics called quantum dots have demonstrated preliminary efficacy against resistant strains and I am working within a team of researchers to further advance this technology. Furthermore, I am investigating high throughput optical sequencing and detection methods that may one day possess the speed and reliability necessary for more immediate targeted treatment of antibiotic resistant infection patients.
Research: My research involves optimizing spacecraft maneuvers to minimize uncertainty in the spacecraft state. This approach may be preferred in low gravity environments, such as near asteroids and comets, where propellant requirements are minimal, but maneuver accuracy is paramount. The control framework developed will allow spacecraft with large thrust uncertainty to more accurately maneuver in low gravity environments, decreasing reliance on ground control, increasing operational safety, and freeing up mission time for science objectives.
Research: The climate is studied by preforming simulations using earth system models (ESM). Current limitations in computational power restrict simulations from fully resolving all spatial and time scales relevant to the climate system. The smaller scales are parameterized in ESMs. My research currently focuses on improving these parameterizations by performing large eddy simulations (LES) of small scale dynamics. I am investigating the impact small scale and submesoscale turbulence has on biogeochemistry in the upper ocean. Improving our understanding of the coupling between ocean dynamics and biogeochemical tracer evolution will lead to better parameterizations and more accurate results from ESMs.
Research: Martinez is currently a student at the University of New Mexico and will be attending CU Boulder starting in the Fall 2018. She will be working with Dr. Ding to develop a Super Tough Hydrogel (STH) for membrane usage and separation processes. STHs are incredibly different than your typical hydrogels; being much stronger and having an ability to withstand large amounts of pressure driven forces ultimately allowing us to utilize the hydrogel as a membrane for desalination and bio-filtration purposes.
Research: The goal of my research is to analyze turbulent reacting flows using computational fluid dynamics to produce better reduced order models. I primarily use modal decompositions, such as proper orthogonal decomposition, to examine the flow. In the future, we plan to implement these techniques on interacting bluff-body stabilized flames to improve propulsion systems and decrease emissions generated from unburnt hydrocarbons.
Research: Most research on career trajectories in academia is limited in scope to researchers from a particular discipline, and all previous work is focused on those who were hired or ultimately granted tenure. The goal of my research is to use software engineering and machine learning to generate longitudinal data sets, across disciplines, of not only those who stayed in academia, but also those who left, in order to suggest public policy interventions to improve gender representation in science.
Research: My research involves analyzing land surface and hydro-climatological relationships with a variety of water quality constituents in surface water. The goal of my research is to enable forecasting of future water quality scenarios that incorporate climate and land surface variability using primarily satellite data. A tool I will develop from this work will facilitate decision makers with forming strategies to address variability in surface water quality for human and environmental health under climate change.
Sundaram is currently a student at the University of Pittsburgh and will be attending CU Boulder starting in the Fall 2018.