Bioelectronics, protein engineering, metabolic engineering, microbial communities, cell-material interfaces, synthetic biology, biophysics

Use of synthetic biology and metabolic engineering to address important problems in sustainable energy, the environment, industry and human health

Biophysics, cell engineering, protein interactions, phase separation in cells

Bacterial persistence, host-pathogen interactions, network biology of bacterial stress

Herding cells for pleasure and non-profit; Tissue engineering with bioelectric ‘sheepdogs’; Cellular crowd dynamics in healing and tissue growth; Living swarm biomechanics and biophysics; 3D biomaterials mimicking cells; Waterbears and extreme biology

Microscopy and bioimaging; bioelectronics, flexible electronics, and nanotechnology; cell and developmental biology; tissue engineering; neuroscience

Synthetic biology, cell programming, AI for biology, protein engineering, biochemistry

Understanding and engineering of biomolecular condensates; multiscale computer simulations; biophysics; protein self-assembly

Developing molecular and optical approaches to study the function and molecular organization of neurons in the brain

Understanding and controlling complex cell behaviors

DNA repair and the DNA damage response, genome editing, technology development

Defining and engineering plant-microbe and microbe-microbe interactions at plant-microbe interfaces

The cell biology of tissue polarity and epithelial patterning

Nonlinear optics and photonics for biomedical imaging

Theoretical and computational materials science; physics of materials; physical biology; microstructure formation

Waste treatment systems;  environmental remediation; biogeochemically mediated dynamics

Biogenesis, function and engineering of the eukaryotic CO2-fixing organelle, the pyrenoid

Chemical biology approaches to investigate RNA dynamics and post-transcriptional regulation

Design and mechanics of metamaterials with unusual material properties; Mechanics in morphogenesis during embryo development

Our lab seeks to understand how patterns of neural activity generate animal behavior.

How noncoding regions of the genome function to control the differential patterns of gene expression, both spatial and temporal, that define cell behavior

Protein engineering, peptides, natural products, antibiotics, microbiology, genomics, and supramolecular chemistry

How the brain converts sensory stimuli into meaningful representations, and how these representations drive behavioral responses

CRISPR-based technologies for studying viral and cellular RNA

Molecular architecture and function of the microtubule cytoskeleton

Applying statistics, machine learning and efficient algorithms to biology and medicine with integrative analysis of multi-dimensional data

Polymeric formulations for drug encapsulation, delivery, and release

Developing and applying computational and mathematical methods to address biological questions at the molecular and cellular level

Integrated circuits and chip-scale systems operating across RF-THz-optical frequencies in low-cost, smart biomedical devices for point-of-care use

Using techniques from machine learning and social computing to extract brain structure from light and electron microscopic images

How life emerges from collections of molecules, cells, and organisms; asking how bacterial cells grow, divide, and move; how collections of cells form patterns; and how and why discrete animal behaviors are generated by the brain

Quantitative analysis of pattern formation in developing tissues; genetics, genomics and computational studies of signaling pathways

Computational biology and bioinformatics; computational science

Animal coloration and patterning, avian color vision, evolution of eggs

Theory, simulation and experiments in surface tension, buoyancy, fluid rotation and surfactants; flow of lipids and motions of suspended particles

Micronanofabricated technologies for electronics, displays, and bio-interfacing devices.

Genomic data integration; bioinformatics, algorithms and machine learning.

Machine learning and reinforcement learning, with applications in healthcare, drug discovery, intelligent systems

Machine learning, computational and structural biology, 3D computer vision, biological imaging