School of Engineering
Showing 1-10 of 15 Results
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Ching-Yao Lai
Assistant Professor of Geophysics
BioMy group attacks fundamental questions in ice-dynamics, geophysics, and fluid dynamics by integrating mathematical and machine-learned models with observational data. We use our findings to address challenges facing the world, such as advancing our scientific knowledge of ice dynamics under climate change. The length scale of the systems we are interested in varies broadly from a few microns to thousands of kilometers, because the governing physical principles are often universal across a range of length and time scales. We use mathematical models, simulations, and machine learning to study the complex interactions between fluids and elasticity and their interfacial dynamics, such as multiphase flows, flows in deformable structures, and cracks. We extend our findings to tackle emerging topics in climate science and geophysics, such as understand the missing physics that governs the flow of ice sheets in a warming climate. We welcome collaborations across disciplinary lines, from geophysics, engineering, physics, applied math to computer science, since we believe combining expertise and methodologies across fields is crucial for new discoveries.
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Sanjiva Lele
Edward C. Wells Professor of the School of Engineering and Professor of Mechanical Engineering
BioProfessor Lele's research combines numerical simulations with modeling to study fundamental unsteady flow phemonema, turbulence, flow instabilities, and flow-generated sound. Recent projects include shock-turbulent boundary layer interactions, supersonic jet noise, wind turbine aeroacoustics, wind farm modeling, aircraft contrails, multi-material mixing and multi-phase flows involving cavitation. He is also interested in developing high-fidelity computational methods for engineering applications.
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Adrian Lew
Professor of Mechanical Engineering
BioProf. Lew's interests lie in the broad area of computational solid mechanics. He is concerned with the fundamental design and mathematical analysis of material models and numerical algorithms.
Currently the group is focused on the design of algorithms to simulate hydraulic fracturing. To this end we work on algorithms for time-integration embedded or immersed boundary methods. -
Zetian Li
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2024
Current Research and Scholarly InterestsStatistical Learning, Machine Learning, Bayesian Statistics, Probability Theory
