Dr. Gen Li is an Associate Professor in the Department of Biostatistics. He is devoted to developing new statistical methods for analyzing complex biomedical data, including multi-way tensor array data, multi-view data, and compositional data. His methodological research interests include dimension reduction, predictive modeling, association analysis, and functional data analysis. He also has research interests … Read more
In this project, we use multi-scale models coupled with machine learning algorithms to study cardiac electromechanic coupling. The approach spans out the molecular, Brownian, and Langevin dynamics of the contractile (sarcomeric proteins) mechanism of cardiac cells and up-to-the finite element analysis of the tissue and organ levels. In this work, a novel surrogate machine learning … Read more
Lu’s research is focused on natural language processing, computational social science, and machine learning. More specifically, Lu works on algorithms for text summarization, language generation, argument mining, information extraction, and discourse analysis, as well as novel applications that apply such techniques to understand media bias and polarization and other interdisciplinary subjects. Awards and Accomplishments
Yixin Wang works in the fields of Bayesian statistics, machine learning, and causal inference, with applications to recommender systems, text data, and genetics. She also works on algorithmic fairness and reinforcement learning, often via connections to causality. Her research centers around developing practical and trustworthy machine learning algorithms for large datasets that can enhance scientific … Read more
My PhD research focused on identifying the size and mineralogical composition of interstellar dust through X-ray imaging of dust scattering halos to X-ray spectroscopy of bright objects to study absorption from intervening material. Over the course of my PhD I also developed an open source, object oriented approach to computing extinction properties of particles in … Read more
Dr. Lu brings expertise in machine learning, particularly integrating human knowledge into machine learning and explainable machine learning. He has applied machine learning in a range of domain applications, such as autonomous driving and machine learning for optimized design and control of energy storage systems. Awards and Accomplishments
The Ahmed lab studies behavioral neural circuits and attempts to repair them when they go awry in neurological disorders. Working with patients and with transgenic rodent models, we focus on how space, time and speed are encoded by the spatial navigation and memory circuits of the brain. We also focus on how these same circuits … Read more
Dr. Andrew Gronewold, P.E., is an Associate Professor with the School for Environment and Sustainability (SEAS) at the University of Michigan. He also holds adjunct faculty appointments in the University of Michigan’s Department of Civil and Environmental Engineering, and the Department of Earth and Environmental Sciences. Dr. Gronewold conducts research through a range of hydrological … Read more
Prof. Huang is specialized in satellite remote sensing, atmospheric radiation, and climate modeling. Optimization, pattern analysis, and dimensional reduction are extensively used in his research for explaining observed spectrally resolved infrared spectra, estimating geophysical parameters from such hyperspectral observations, and deducing human influence on the climate in the presence of natural variability of the climate … Read more