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ICME Welcomes Five New Affiliated Faculty Members

ICME is excited to announce the addition of five new affiliated faculty as members of the institute.

Emily Fox, Professor of Statistics and Computer Science. Emily Fox is a Professor in the Department of Statistics and Department of Computer Science at Stanford University. Prior to Stanford, she was the Amazon Professor of Machine Learning in the Paul G. Allen School of Computer Science & Engineering and Department of Statistics at the University of Washington. From 2018-2021, Emily led the Health AI team at Apple, where she was a Distinguished Engineer. Learn more.

Ching-Yao Lai, Assistant Professor of Geophysics. My 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. Learn More.

Christian Linder, Professor of Civil and Environmental Engineering. Christian Linder is a Professor of Civil and Environmental Engineering and, by courtesy, of Mechanical Engineering. Through the development of novel and efficient in-house computational methods based on a sound mathematical foundation, the research goal of the Computational Mechanics of Materials (CM2) Lab at Stanford University, led by Dr. Linder, is to understand micromechanically originated multi-scale and multi-physics mechanisms in solid materials undergoing large deformations and fracture. Applications include sustainable energy storage materials, flexible electronics, and granular materials. Learn more.

Markus Pelger, Assistant Professor of Management Science and Engineering. Markus Pelger is an Assistant Professor of Management Science & Engineering at Stanford University and a Reid and Polly Anderson Faculty Fellow. His research focuses on understanding and managing financial risk. He develops mathematical financial models and statistical methods, analyzes financial data and engineers computational techniques. His research is divided into three streams: statistical learning in high-dimensional financial data sets, stochastic financial modeling, and high-frequency statistics. His most recent work focuses on developing machine learning solutions to big-data problems in empirical asset pricing. Learn more.

Vasilis Syrgkanis, Assistant Professor of Management Science and Engineering. I am an Assistant Professor in Management Science and Engineering and (by courtesy) in Computer Science and Electrical Engineering, in the School of Engineering at Stanford University. I am also an affiliated with the Institute for Computational and Mathematical Engineering (ICME). I am an active member of the Stanford Operations Research Group, the Statistical Machine Learning Group, the CS Theory Group and affiliated with the Stanford AI Lab (SAIL), the center for Human-Centered AI (HAI) and Stanford Data Science. My research interests are in the areas of machine learning, causal inference, econometrics, online and reinforcement learning, game theory/mechanism design and algorithm design. Learn More.

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