Ian Wang Dept of Environmental Science, Policy & Management genetics and genomics, genomics, landscape genetics, evolution, population genetics, conservation, herpetology, GIS, spatial analysis, statistical methods, epigenetics
Daniel Klein Division of Computer Science (EECS) unsupervised language acquisition, efficient algorithms for NLP, linguistically rich models of language, integrating symbolic and statistical methods for NLP, organization of the web, machine translation, information extraction
Nilah Ioannidis Division of Computer Science (EECS) computational biology, machine learning, artificial intelligence, genomics, personal genome interpretation, precision health, rare diseases, statistical genetics, molecular biology, biophysics
Panayiotis Papadopoulos Dept of Mechanical Engineering continuum mechanics, computational mechanics, contact mechanics, computational plasticity, materials modeling, solid mechanics, applied mathematics, dynamics of pseudo-rigid bodies
Lexin Li School of Public Health neuroimaging data analysis, deep brain stimulation, brain-computer-interface, statistical machine learning, Deep Learning, reinforcement learning, networks data analysis, functional data analysis, tensor analysis, ordinary differential equations, dimension reduction, high dimensional inference
Henry Brady Dept of Political Science Goldman School of Public Policy comparative politics, public policy, electoral politics, political participation, survey research, program evaluation, statistical methods in the social sciences, social welfare policy, Soviet Union, inequality in America
Michelle Wilkerson School of Education K-12 math and science education, science education, mathematics education, computing education, design-based research, computers in K-12 education, data literacy, data science education
Kannan Ramchandran Division of Computer Science (EECS) Division of Electrical Engineering (EECS) statistical and sparse signal processing, adversarial and distributed machine learning, coded computing, privacy and security, scalable distributed video-on-demand delivery, coding theory, communications, information theory, peer-to-peer networking, blockchains
Vadim Gorin Dept of Mathematics Dept of Statistics integrable probability, random matrices, asymptotic representation theory
Jennifer Chayes Dept of Mathematics Dept of Statistics Division of Computer Science (EECS) phase transitions in computer science, structural and dynamical properties of networks, graphons, machine learning, ethical decision making, climate change
Bin Yu Dept of Statistics machine learning, trustworthy data science and AI, interdisciplinary research in biomedicine, neuroscience, climate science
Sam Pimentel Dept of Statistics causal inference, health services & policy analysis, biostatistics, discrete optimization
Olga Holtz Dept of Mathematics numerical analysis, matrix and operator theory, approximation theory, wavelets and splines, orthogonal polynomials and special functions, analysis of algorithms and computational complexity
Dan-Virgil Voiculescu Dept of Mathematics operator algebras, free probability theory, random matrices, K-theory of operator algebras, single operator theory
Mark van der Laan Dept of Statistics School of Public Health targeted learning, real-world data integration in RCTs, sequential adaptive designs, computational biology and genomics, censored data and survival analysis, medical research, inference in longitudinal studies
Ian Agol Dept of Mathematics topology of 3-manifolds, interaction hyperbolic geometry, low-dimensional topology
Venkatesan Guruswami Dept of Mathematics Division of Computer Science (EECS) theoretical computer science, coding theory, approximate optimization, randomness in computation, computational complexity
Gabriel Goldberg Dept of Mathematics set theory, large cardinals, inner model theory, infinite combinatorics
Ian Wang
