| S. R. Srinivasa Varadhan |
Various aspects of stochastic processes; Diffusion processes and their connection to the theory of partial differential equations; Scaling limits of large systems; Large deviations and the analysis of rare events; |
| David W. Hogg |
Astronomy; Cosmology; Probabilistic inference; MCMC; |
| Juliana Freire |
Large-scale information integration; Information visualization and visual analytics; Provenance management; Big data management and analysis; |
| Roy Lowrance |
machine learning; mathematics; |
| Rebecca Liebe |
Higher Education Operations Management; Valuation; Merger and Acquisition; joint venture; |
| David Clark |
n/a; |
| Jennifer Hill |
Causal inference; Missing data; Bayesian nonparametrics; |
| Michael (Mik) Laver |
Crowd-sourced data coding; Automated text analysis; Agent-based modeling; Analytical computational and empirical accounts of political competition and decision-making; |
| Yann LeCun |
Machine learning; Computer vision; Mobile robotics; Computational neuroscience; Data Compression; Digital Libraries; the Physics of Computation; applications of machine learning (Vision, Speech, Language, Document understanding, Data Mining, Bioinformatics); deep learning; optical character recognition and computer vision using convolutional neural networks (CNN); a founding father of convolutional nets; research; technical consulting; scientific advising; |
| Foster J. Provost |
Data science; Data mining; Knowledge discovery; Machine learning; Predictive modeling; Integrating human and machine computation; Learning; Inference in network data; Social network analysis; Crowdsourcing; Micro-outsourcing systems; |
| Claudio T. Silva |
Big Data and Urban Systems; Visualization and data analysis; Sports Analytics & visualization; Geometry processing; |
| Eero P. Simoncelli |
Probabilistic analysis and representation in biological and machine vision (and audition); Statistical signal and image processing; |
| David Sontag |
Theoretical and practical aspects of machine learning and probabilistic inference; Medical informatics; Information retrieval; Natural language processing; |
| Karen E. Adolph |
Perceptual-motor learning and development; Open video data sharing; |
| Constantin Aliferis |
Machine learning in medicine and biology; Causality discovery; Data analytics methodology; Citation analysis; |
| Nathaniel (Neal) Beck |
Political methodology, more specifically longitudinal data and non-linear methods; Political Economy; |
| Juan Bello |
Computer-based analysis of musical signals and its application to music information retrieval; Digital audio effects and interactive music systems; Machine learning; Data mining; Audio signal processing; Digital Signal Processing; Computer Audition; Music and audio research; |
| Michael Blanton |
Astronomical spectroscopy and image analysis; clustering statistics in large-scale galaxy maps; demographics of the galaxy population; Realistic Models of Galaxy Formation and Large-Scale Structure Statistics; Astrophysics; formation and evolution of galaxies, by confronting theoretical predictions with results from large observational data sets; the population of extremely low luminosity galaxies, using data from the Magellan 6.5m telescopes, the Kitt Peak National Observatory 4m telescope, the Green Bank Telescope, Arecibo, and the Very Large Array; the change in the galaxy population since early epochs, using a new instrument for obtaining huge numbers of high redshifts -- a low dispersion prism on the IMACS instrument at Magellan; the large-scale structure in the galaxy distribution, using huge maps of the Universe (helping to create) such as the Sloan Digital Sky Survey --- and its successors; |
| Jan Bluestein |
Quantitative methods in policy research; Health service equity; chronic illness; the Medicare program; statistics; program evaluation; research methods; Health management; Health Policy; inequality; Law & regulation; Public & Non-profit organizations; Race, Class, Gender, & Diversity; Social policy; |
| Richard A. Bonneau |
Systems biology and protein modeling; protein structure prediction; network inference; bioinformatics; systems biology; learning networks from functional genomics data; predicting and designing protein and peptoid structure; experimental psychologists to apply methods for learning network structure from time series to social media time series data (using Twitter, online blogs about politics, and Facebook as initial data sources); computational biology; |
| Adam Brandenburger |
Game theory; Business strategy; Quantum information; |
| David Cai |
Theoretical and computational neuroscience; Applied dynamical systems; Stochastic processe; |
| Andrew Caplin |
Combining theoretical and machine learning methods to optimize financial offers and financial decisions at household level; Economic data engineering; |
| Xi Chen |
Machine learning; High-dimensional statistics; Optimization under Uncertainty; Operations Research; Statistics for Business Control, Regression, and Forecasting Models; Regression and Forecasting Models; Stochastic modeling; Machine learning and Statistical Inference for high-dimensional and structured data analysis; Optimization methods and theory for large-scale and high-dimensional data analysis.; Learning from collective intelligence; statistical learning and online decision making for crowdsourcing; Operations research/management problems, such as the optimal network design in process flexibility, approximate dynamic programming and revenue management.; Applications to web text mining; recommendation systems; financial data anlaysis; environmental data analysis; bioinformatics; |
| Gloria Coruzzi |
Gene network analysis; Data mining and visualization; Systems biology and phylogenomics; Plant Systems Biology; combines genomic, bioinformatic, and system biology approaches to identify gene networks involved in biological regulatory mechanisms controlling nitrogen use and the evolution of seeds; evolutionary genomics; |
| Kyle Cranmer |
Collaborative statistical modeling; Statistical methods in particle physics; Data preservation and open access; Digital publishing; Data-analysis; |
| Nathaniel Daw |
Quantitative methods in neuroscience; Computational neuroscience; Machine learning; Data analysis; how people and animals learn from trial and error (and from rewards and punishments) to make decisions, combining computational, neural, and behavioral perspectives; understanding how subjects cope with computationally demanding decision situations, notably choice under uncertainty and in tasks (such as mazes or chess) requiring many decisions to be made sequentially; using computational frameworks of reinforcement learning and Bayesian decision theory as a basis for analyzing and understanding biological decision making; Computational models in neuroscientific experiments; interactions between multiple decision-making systems; Learning and neuromodulation; |
| Vasant Dhar |
Data Science; Predictive Analytics; Prediction; finance; healthcare; education; Business- sports; digital marketing; Trading Strategies; social media; data mining; machine learning; big data; small data; artificial intelligence; |
| Dustin T. Duncan |
Social Epidemiology; Spatial Epidemiology; Neighborhoods; Health Disparities; |
| Rob Fergus |
Computer Vision; Large scale object recognition; Deep learning; Machine learning; Statistical methods in astronomy; Computational photography; |
| Halina Frydman |
Statistics; Survival analysis; Stochastic models in finance and labor economics; Corporate credit ratings migration; Mixtures of Markov chains; Estimation in continuous and discrete time Markov chains from incomplete data; Modeling intensities of corporate default and other credit events; |
| Judith D. Goldberg, ScD |
Statistical methods for the design, conduct, and analysis of clinical and translational research; Statistical methods for epidemiology Survival analysis Statistical methods for the analysis of observational data; Statistical issues in medical screening; Survival Analysis; Clinical Trials; Methods for the Analysis of Screening and Diagnostic Tests; Misclassification; Methods for the Analysis of Observational Data; Statistical Methods in Epidemiology; Statistical Genomics; |
| Jonathan Goodman |
Monte Carlo methods; Bayesian methods in astrophysics and finance; Stochastic and deterministic optimization; Large time behavior of viscous planar shock profiles; Anisotropic adaptive refinement in finite elements; Large time behavior of linear and nonlinear waves in multidimensional lattices; A nonlinear parabilic evolution equation; Some problems in finance; |
| Leslie F. Greengard |
Quantitative methods in biology and medicine; Scientific computing; Electromagnetics; Acoustics; Fluid dynamics; Solid mechanics; fast algorithms; fast multipole method (FMM); adaptive methods; integral equations; potential theory; electromagnetics; computational chemistry; computational biology; |
| C. Sinan Gunturk |
Mathematics of analog-to-digital conversion; Sampling theory in signal processing and harmonic analysis; Sparse representations and redundant representations of data in signal processing; Approximation theory and harmonic analysis methods in data compression; Harmonic Analysis; efficient digital representations of analog signals; quantization theory in information theory; approximation power of sigma-delta modulation schemes in the classical setting of bandlimited functions; building a quantization theory for compressive sampling; |
| Todd M. Gureckis |
Computational cognitive science; Unsupervised learning; Active Learning; Human decision making; decision processes; Research applications of crowdsourcing; human learning; memory; combination of behavioral studies and computational modeling; modeling approaches inspired by research in computer science on machine learning and artificial intelligence; efforts to understand how people actively explore their environment when learning, how they generate and test hypotheses about the world, how they learn abstract concepts from concrete examples, and the influence of concept learning on perception.; |
| Peter F. Halpin |
Psychometrics; Educational data mining; Computer supported collaborative learning and assessment; Scalable methods for non-stationary time series; |
| Daphna Harel |
Psychometrics; Item response theory; Measurement in the applied health sciences; Model misspecification; Crowdsourcing; |
| David J. Heeger |
Computational neuroscience (developing and testing computational theories of brain function); Characterizing how the activity of large numbers of neurons represent sensory stimuli, motor actions, and cognitive states; Dimensionality reduction; Vision and image processing; Statistics of images; Bayesian estimation, inference, and prediction; neuroimaging; Autism; Neuroethics and NeuroLaw; Functional Brain Imaging; Human Vision/Psychophysics; Electrophysiology; Image Processing, Computer Graphics, and Computer Vision; |
| Ming Hu |
Bayesian analysis in bioinformatics and statistical genetics, with particular focus on analyzing the next generation sequencing data; cancer genomics; Bayesian inference of spatial organizations of chromosomes using Hi-C data; analyzing ChIP-Seq and single-cell RNA-Seq data; alyzing next-generation DNA sequencing data and studying complex human diseases, such as asthma, chronic obstructive pulmonary diseases (COPD) and age-related macular degeneration (AMD); |
| Clifford M. Hurvich |
Time Series Analysis; Model selection for parametric models as well as smoothing parameters and regularization parameters; FFT-Based Algorithms for solving large ill-conditioned Toeplitz systems with applications to forecasting; Point process methods with applications to high-frequency financial data; Long-Range Dependence (scaling laws); |
| Panagiotis G. Ipeirotis (Panos) |
Crowdsourcing; Text mining; Web mining; Data mining; Machine learning; Databases; Online Labor Markets; Social Media Analytics; Information Retrieval; |
| Srikanth Jagabathula |
intersection of Operations Management, Marketing, and Machine Learning; building data-driven models that inform operational decisions of businesses; predictive choice modeling; fitting choice models and then solving the resulting assortment optimization decision problems.; |
| John Jost |
Experimental social psychology; Public opinion survey research methods; Quantitative and qualitative analysis of behavioral data in the social sciences; |
| Robert V. Kohn |
Mathematical aspects of materials science; cloaking; coarsening due to energydriven motion; composite materials; effective moduli; epitaxial growth; interface motion laws; martensitic transformation; micromagnetics; photonics; pattern formation due to energy minimization; polycrystal plasticity; shape–memory materials; structural optimization; surface energy as a selection mechanism; thermally-activated switching; wrinkling of thin elastic sheets; Nonlinear partial differential equations and nonconvex variational problems; bounds and extremal microstructures for composites; electric current tomography; homogenization; r–convergence; image segmentation; motion by curvature; relaxation of nonconvex; variational problems; self-similarity in solutions of nonlinear evolution equations; singularly perturbed variational problems; |
| Petter Nils Kolm |
Algorithmic and quantitative trading strategies; Econometrics; Data exploration; Forecasting models; High frequency trading (HFT); Portfolio construction; Portfolio optimization; Transaction costs; Risk management; |
| Peter Lakner |
Probability; Stochastic optimization and control; Applied Stochastic Processes in Finance; Stochastic Models in Finance; Continuous Time Processes; Statistics and Data Analysis; |
| Jinyang Li (李金扬) |
Semiparametric modeling and inference for survival data including survival endpoint in joint analysis with longitudinal data; Distributed systems; operating systems; wireless networks; |
| Mengling Liu |
Semiparametric modeling and inference for survival data, including survival endpoint in joint analysis with longitudinal data; Biomarkers and Breast Cancer Risk Prediction in Younger Women; Integration and Evaluation of Pooled Cancer Studies with Heterogeneity; Statistical Genetics and Clinical Trials; |
| Alessandro Lizzeri |
n/a; |
| Ying Lu |
Quantitative methodology in social and behavioral sciences; Applications in demography; Health and political behavior; General statistical methodology such as model selection and hypothesis testing; |
| Andrew J. Majda |
Modern applied mathematics; merging asymptotic methods; numerical methods; physical reasoning and rigorous mathematical analysis; partial differential equations; shock waves; combustion; incompressible flow; vortex dynamics; atmospheric sciences; cross-disciplinary research with modern applied mathematics in climate modeling and prediction; |
| Suzanne McIntosh |
High performance computing architectures; Big Data analytics; realtime systems; secure software engineering; virtualization; Computer Science; Distributed Systems; Algorithms; Cloud computing; Hadoop; Operating Systems; Embedded Systems; System architecture; Machine Learning; SQL; Enterprise Architecture; Integration; |
| Edward Melnick |
Analysis of time series data; Developing time series models and their statistical properties; Issues related to risk and especially to homeland security; Forecasting; Theory of Estimation; Information Theory; Quantitative Risk Analysis and Assessment; Advanced Theory of Statistics; Forecasting Time Series Data; Introduction to the Theory of Probability; Statistical Inference and Regression; formulation of analytical models and the development of statistical methodology needed to analyze them; order statistics; the occurrence of low probability events that result with catastrophic consequences.; |
| Joel Middleton |
Data-driven politics; Design-based estimation and causal inference in randomized experiments; Experiments in voter behavior and political persuasion; survey sampling and design; field experiments; data analysis; political decision making; |
| Bud Mishra |
Bayesian and Empirical Bayesian analysis; Shrinkage; Rate-distortion theory; Redescription; Phenomenological models; Model checking and causality analysis; Joining the data scientists in silicon alley to make a BIG data scientist.; applied contributions to bioinformatics, cybersecurity, and computational finance.; |
| Charles (Chuck) M. Newman |
Probability Theory, especially interacting particle systems and percolation models; Statistical Physics, especially Ising, spin glass and coarsening models Monte Carlo; Analytic approaches to the above areas; fields where probability mixes with physics, including metastability, spin glasses, the mathematics of food webs and the Ising model; percolation theory including its connections to Schramm–Loewner evolutions and the Brownian web; |
| Patrick O. Perry |
Modern multivariate statistics; Network and text data; Statistical computing; Emerging data sources; High-dimensional latent factor models; Cross-validation for unsupervised learning; Modeling and inference of network dynamics; Social and economic networks; Regression and Forecasting Models; Statistics for Business Control and Regression and Forecasting Models; |
| Bijan Pesaran |
Neural dynamics and decision making; Brain-machine interface; Investigating brain circuits underlying behavior; Developing techniques to analyze neural activity and behavior; Developing new technologies to treat brain disorders; |
| Michael Purugganan |
Evolutionary and ecological genomics of plant adaptations; Genetics of Plant Domestication; The Evolution of Multicellularity and Social Behaviour; |
| Keith W. Ross |
Data-driven privacy analysis; online social networks; applied probability; Markov decision processes; Computer Networking; Network Security; Privacy; Teaching fundamentals of Computer Science; |
| Marc A. Scott |
Computationally Intensive Statistics (e.g. Applied Spatial Statistics); Categorical Data Models & Clustering Techniques; Statistics in Social Science and Health Applications; development of statistical models for longitudinal data; Using latent variable technology; development of covariance models; examining recent trends in wage inequality; medical histories; models for longitudinal sequence analysis; influence of the entire pathway (e.g., the timing of educational and employment spells and interruptions to these) on an outcome measure such as wages or degree completion; examining low-wage labor markets to find similar structure in the career histories and education of workers to identify more and less successful career ladders; |
| Youngzhao Shao |
Statistical methodology and applications to medical research; independent methodological research in developing innovative statistical methods and study designs and as an investigator participating on a wide spectrum of NIH funded research projects on cancer studies and population and environmental health research.; cancer research; population and environmental health research; |
| Dennis Shasha |
Computational methods in biology, finance, and wireless communication; Pattern recognition; Querying in trees and graphs; Pattern discovery in time series; Cryptographic file systems; Database tuning; |
| Jeff Simonoff |
Applications of statistics; Statistical methodology; Statistical properties of modern data analytic methods; categorical data; outlier identification and robust estimation; smoothing methods; computer intensive statistical methodology; applications of statistics to business problems; |
| Alexander Statnikov |
Computational causal discovery; variable selection, and supervised learning in high-dimensional data; Comprehensive empirical benchmarking of various machine learning methodologies; Machine learning analysis of biomedical and other high-dimensional data; Causal structure/network discovery and analysis; Variable/feature selection; Predictive modeling and supervised learning (classification and regression); Benchmarking/evaluation of methods for analysis of high-dimensional data; Multicriteria optimization; |
| Lakshminarayanan Subramanian |
Big Data Analytics; Networked Systems; Computing for Development; Wireless and Mobile Systems; Connectivity and Web access; Crowdsourcing; Mobile security; Networks and Markets; Inference; Data privacy; bridging the digital divide; developing innovative computing solutions to address real-world societal challenges, especially those pertaining to enhancing global development; |
| Torsten Suel |
Web Search Technology; Algorithms; Databases; Data Compression; Distributed Computation; |
| Arun Sundararajan |
Online privacy; Social network analysis; Computational social science; Causal inference; Econometrics; Text mining; Network effects; Digital rights management; Price discrimination; |
| Esteban Tabak |
Density estimation; Dimensional reduction; Classification; Data-driven optimal transport; Bio-statistics; Data-based medical diagnosis; Applied Mathematics and Physics; Fluid Dynamics, Atmosphere and Ocean Science; Data Analysis; |
| Aaron Tennebein |
Sampling; Sample surveys; Simulation methodology; Fixed income instruments; Statistical methods in risk management and actuarial science; Regression analysis; Application to actuarial problems in mortality estimation; Risk theory; |
| Eric Vanden-Eijnden |
Development of mathematical tools and numerical methods for the analysis of dynamical system which are both stochastic and multiscale.; theoretical physics; |
| Sharon L. Weinberg |
Application of quantitative methods in the social sciences; Statistics; General Linear Model; Multivariate Analysis; Factor Analysis; Multidimensional Scaling; Research and Survey Design; Computer Applications; |
| Margaret H. Wright |
Optimization methods in science and engineering, especially derivative-free methods and constrained nonlinear optimization.; linear algebra, scientific computing, and their applications; |
| Laura Noren |
Workplace Ethnography especially Small Group Collaboration, Professionalization, and Fields; Social media communities; Research methods; |
| Brian McFee |
Machine learning; Music Information Retrieval; Recommender Systems; Multimedia Signal Processing; |
| Brenden Lake |
Computational Cognitive Science; Structured Probabilistic Models; One-Shot Learning; Human-Inspired Machine Learning; |
| Daniela Huppenkothen |
High-energy Astrophysics; Black Holes and Neutron Stars; Fourier Methods; Statistical Methods for Astronomical Time Series; applying recent advances in statistics and computer science to data from X-ray and gamma-ray telescopes; |
