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University research directory
Research labs at
University of Virginia (Main campus).
Compare 5 listed faculty-led profiles, explore their research interests, and follow the evidence in their selected work. These listings are a starting point for discovery and do not establish recruiting availability.
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Review each lab’s official website and recent publications. Compare the methods used, the questions being asked, and the practical requirements of any published opening. Unclaimed profiles are independently curated; the university has not approved or endorsed them.
How to compare research labs ↗Official university website ↗5 research-led lab profiles
Browse labs by their listed college affiliationGalloway Lab
University of Virginia (Main campus)Laura Galloway · Commonwealth Professor of Biology
How do plants adapt when climates warm and their geographic ranges change? The lab combines field and greenhouse studies with ecological genetics, genomics and bioinformatics to investigate evolution in natural plant populations. Research examines populations remaining at the edges of ranges after glacial retreat as opportunities to understand responses to warmer conditions. Other projects connect historical range expansion with mating-system traits. The group also investigates whether differences in organelle genomes, including chloroplast DNA, contribute to reproductive isolation during the earliest stages of speciation.
Kevin Skadron Research Group
University of Virginia (Main campus)Kevin Skadron · Harry Douglas Forsyth Professor of Computer Science
How can memory be augmented to perform computation directly to reduce data movement and improve throughput for data-intensive workloads? His group develops new processing-in-memory architectures and evaluates them (e.g., Fulcrum, Gearbox, Sieve, DRAM-CAM, DRAM-AP) to explore performance and design trade-offs. The researchers design new automata and regular-expression processing hardware and runtimes through the UVA Center for Automata Processing (CAP) to enable high-throughput pattern matching and monitoring. The team builds programming models, APIs, and compiler support to simplify mapping applications to heterogeneous and PIM systems. They also create simulation frameworks and benchmark suites, including the PIMeval simulation framework and PIMbench benchmark suite, for quantitative evaluation.
Nathan Swami Research Group
University of Virginia (Main campus)Nathan Swami · Professor of Electrical & Computer Engineering and Chemistry
Can small electrical and microfluidic devices reveal differences between cells that conventional measurements miss? The group develops microsystems for separating biological samples and detecting their characteristics. Research includes electrochemical measurements in droplets and microfluidic channels, soft-material platforms, and label-free methods that measure single-cell electrical impedance and deformability. These approaches investigate heterogeneity in stem cells, tumor cells, microbes and extracellular vesicles. The work connects biological samples with devices, circuits and signal analysis, with applications in regenerative biomanufacturing and diagnostics in settings with limited resources.
Papin Lab
University of Virginia (Main campus)Jason Papin · Professor
Can maps of cellular metabolism reveal how cells respond to disease and changes in their environment? The group reconstructs and analyzes large biochemical networks, combining high-throughput experimental data with mathematical and computational models. Researchers develop methods for incorporating measurements into network reconstructions and use experiments to test and improve model predictions. Applications include infectious disease, cancer, toxicology and metabolic engineering. The work connects the activity of many biochemical reactions with the behavior of whole cellular systems, seeking mechanisms relevant to human health.
Soft Biomatter Laboratory
University of Virginia (Main campus)Liheng Cai · Associate Professor of Materials Science and Engineering
How can soft materials be designed to interact predictably with living systems? The lab investigates the interface between soft biomaterials and biology, drawing on polymer physics and principles of soft matter. Research asks how these materials interact with biological objects and whether physical principles can help explain biological behavior. The program also explores AI and machine learning as tools for discovering fundamental relationships in soft materials. Its research areas include biomaterials, advanced biomanufacturing and self-driving laboratory approaches, with questions motivated by health, energy and sustainability.
Showing 1–5 of 5 labs