NSF Recognizes 9 UVA Innovators with Prestigious CAREER Awards
The National Science Foundation’s CAREER award celebrates early-career faculty who have shown leadership in research and education. This year, nine University of Virginia faculty members have won the prestigious award and are using it to make advancements in medicine, astronomy, mathematics and technology.
Camille Bilodeau
Camille Bilodeau, an assistant professor of chemical engineering in the School of Engineering and Applied Science, received a $600,000 CAREER award to support her use of PepMNet �” a deep learning model �” to create a tool to rapidly predict the surface-water interactions of tethered peptides.
Tethered peptides, which bind to natural materials, can be modified to influence biological processes in a specific manner. However, since they are made of two or more amino acids, there are countless peptide combinations. Because of this, AI tools are essential for rapidly computing possible amino acid combinations and their effects.
Collaborating with Bio-Rad Laboratories, Bilodeau’s technology aims to help identify peptides that can be utilized in healthcare and the development of new technologies to address emergencies.
Amanda Gibson
Using her $1.5 million CAREER award, Amanda Gibson, an associate professor of biology in the College and Graduate School of Arts & Sciences, will research parasite avoidance.
While traditional science focuses on immune systems as the primary defense mechanism against diseases, Gibson investigates how organisms can evolve to avoid parasites. Similar to how social distancing and quarantining managed the spread of COVID-19, an organism’s aversion to certain areas could potentially mitigate the spread of infection �” especially since pathogens and parasites are distributed in patches.
Specifically, Gibson will study nematode Caenorhabditis elegans �” microscopic worms �” to see if movement helps them protect against disease. She will also explore how avoidance strategies might reduce the importance of other defense mechanisms.
Tariq Iqbal
With a $630,000 CAREER award from the National Science Foundation, Tariq Iqbal, an assistant professor of systems and information engineering and computer science in the School of Engineering and Applied Science, is developing robots that can interpret human intent through speech, gestures, and eye gaze. His goal is to create adaptive systems that respond reliably, even as people and environments change.
Iqbal’s research focuses on designing smarter algorithms and learning techniques that help robots understand what people mean�”not just what they say. These robots will be able to adjust to subtle shifts in communication and surroundings, making them more useful in homes, hospitals, and workplaces.
Yen-Ling Kuo
From vacuum cleaners to medical assistants, robots are everywhere in modern society. Because of this, Yen-Ling Kuo, an assistant professor of computer science and Anita Jones Faculty Fellow in the School of Engineering and Applied Science, is using her $655,000 CAREER award to help robots engage with humans.
Working in the Link Lab, Kuo is seeking to make robots better social partners by programming them to understand spoken cues along with unspoken cues, such as movements and gaze. By combining artificial intelligence with cognitive science, Kuo aims to make robots adaptable and learn from real-time feedback.
Chang Lou
Cloud systems carry important data. From healthcare records to financial information, they are the foundation of the digital world. These systems, however, are often plagued with failures that could compromise personal information and lead to financial losses amounting to billions of dollars. While there are traditional failure-checking tools, they are not practical for large systems as they are manually written and can be error-prone.
To tackle this problem, Chang Lou, an assistant professor of computer science in the School of Engineering and Applied Science, is using a $700,000+ CAREER award to protect cloud systems with automated failure-checking tools. Collaborating with Microsoft and Amazon, Lou is enabling these tools to rapidly detect, correct and prevent problems in real-world cloud system environments.
David Nichols
Hypothesized by Albert Einstein, the theory of general relativity presents gravitational waves as ripples in spacetime caused by massive cosmic events. With a $400,000 CAREER award, David Nichols, an assistant professor of physics in the College and Graduate School of Arts & Sciences, is developing new analytical techniques for examining gravitational waves and studying the unknown effects of general relativity.
Nichols’ work will aid him in examining the lasting impacts of cosmic events, such as black hole collisions, on the structure of space. He will also investigate what makes gravitational wave memory effects unique compared to the effects of electricity and magnetism.
This research could reveal essential information about the origins of the universe and the fundamental properties of gravity. Producing some of the most accurate measurements ever taken, Nichols’ data could also improve how observatories detect gravitational wave signals and study dark matter.
JD Quigley
JD Quigley, an assistant professor of mathematics in the College and Graduate School of Arts & Sciences, researches symmetry in high-dimensional geometry, topology and algebra.
With a CAREER award of about $450,000, Quigley is examining the complex symmetries of high-dimensional fields. Understanding the symmetry of high-dimensional problems will allow for more accurate predictions, which can lead to the development of more effective solutions.
These solutions can be used in the fields of biology, medicine, data analysis and industrial materials development.
Nick Vecchiarello
Nick Vecchiarello, an assistant professor of engineering in the School of Engineering and Applied Science, earned a $600,000 CAREER award to design materials that can improve drug purification.
Drugs are used to treat illnesses ranging from diabetes to multiple sclerosis to cancer. Because of this, it is important to make sure manufacturing isn’t delayed due to the presence of contaminants.
Vecchiarello is developing surfaces coated with peptides that can be modified to bind to or reject a specific molecule. Similar to Camille Bilodeau’s research using machine learning models to identify useful peptides, Vecchiarello is also testing amino acid combinations.
By preventing the creation of contaminated batches, this research can lead to faster, cleaner and more cost-effective ways of producing treatment drugs.
Shangtong Zhang
Shangtong Zhang, the Alf Weaver Assistant Professor of Computer Science in the School of Engineering and Applied Science, is advancing research in reinforcement learning with support from a CAREER award. His work addresses a key challenge in AI: how to safely and efficiently test autonomous systems without relying on costly or risky real-world trials.
Zhang’s project combines offline data with targeted online testing to develop scalable, low-risk evaluation methods. His team at the Sequential Intelligence Lab is pioneering new approaches in Monte Carlo sampling, value function learning, and reward modeling to improve how machines learn from experience and make decisions over time.