Cellular biomechanics; water filtration; thin film adhesion and characterization; subsurface mechano-sensing; shell adhesion; fundamental intersurface forces
Network-wide pavement and bridge deck inspections: sensor technology for infrastructure; saliva-based sensor technology for disease diagnosis and monitoring; structural health monitoring for bridges; subsurface fault detection using air-coupled GPR systems
Cellular and molecular mechanobiology, mechanomedicine, and mechanohealth; cancer cell biology and mechanics; stem cell biology and mechanics; mechanomemory and mechanoresilience, mechanobiotechnologies and their applications to cells, tissues, and organisms
Real-time and energy-efficient deep learning and artificial intelligence systems, model compression of deep neural networks (DNNs), neuromorphic computing and non-von Neumann computing paradigms
Our group investigates biomolecules at the single-molecule level. We develop nanopore-based and other nanotechnology-based methods for probing the structure and dynamic behavior of biomolecules. We employ optical waveguides and single-molecule enzymatic approaches for RNA sequencing, and utilize engineered nanopore sensors for applications in single-molecule proteomics. We are experimentalists, but we also use advanced computational tools to perform big data analysis.
Development of detailed microkinetic models for complex reacting systems; automating the discovery and calculation of reaction pathways; heterogeneous catalysis
dynamics of large-scale molecular machines, working to identify the physical principles that guide biomolecular dynamics, using molecular simulation approaches to interpret experimental data from a wide range of techniques, including biochemical, small-angle X-ray scattering and cryogenic electron microscopy
Human-safe robots, medical robotics, soft robotics and soft material manufacturing, MEMS, microrobotics, bio-inspired design, flapping aerodynamics and insect flight
Computational modeling of the cardiac myocyte to understand the molecular basis of arrhythmias; machine learning in critical care medicine to identify those patients who require urgent care