Staff

  • S. R. Srinivasa Varadhan

    Interim Director of Center for Data Science; Professor of Mathematics
    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

    Deputy Director of Center for Data Science; Executive Director of the Moore-Sloan Data Science Environment; Associate Professor of Physics
    Astronomy; Cosmology; Probabilistic inference; MCMC
  • Roy Lowrance

    Managing Director of Center for Data Science
    email: lowrance@cims.nyu.edu
  • Rebecca Liebe

    Manager, Academic Affairs of Center for Data Science
    email: rebecca.liebe@nyu.edu
  • Varsha Tiger

    Program Administrator of Center for Data Science
    email: varsha.tiger@nyu.edu
  • David Clark

    Administrative Aide of Center for Data Science
    email: david.clark@nyu.edu

Associated Faculty

  • Constantin Aliferis

    Director or NYU Center for Health Informatics and Bioinformatics; Director of Biomedical Informatics Cores of NYU Clinical and Translational Science Institute and the NYU Cancer Center; Associate Professor, Department of Pathology
    Machine learning in medicine and biology, Causality discovery, Data analytics methodology, Citation analysis.
  • Neal Beck

    Professor of Politics
    Political methodology, more specifically longitudinal data and non-linear methods
  • Juan Bello

    Associate Professor of Music and Music Education
    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
  • Gérard Ben Arous

    Professor of Mathematics; Director of the Courant Institute of Mathematical Sciences; Vice Provost for Science
    Probability theory and its applications
  • Richard Bonneau

    Associate Professor of Biology and Computer Science
    Systems biology and protein modeling.
  • Adam Brandenburger

    J.P. Valles Professor and Vice Dean for Graduate Education, Stern School of Business
    Game theory, Business strategy, Quantum information
  • Chris Bregler

    Professor of Computer Science
    Computer vision; Machine learning; Motion capture and human motion analysis
  • Kyle Cranmer

    Assistant Professor of Physics
    Collaborative statistical modeling; Statistical methods in particle physics; Data preservation and open access; Digital publishing; Data-analysis
  • Vasant Dhar

    Professor and Head of the Information Systems Group, Co-Director of the Center for Business Analytics
    Data mining; Digital marketing
  • Rob Fergus

    Associate Professor of Computer Science (on sabbattical)
    Computer Vision; Large scale object recognition; Deep learning; Machine learning; Statistical methods in astronomy; Computational photography
  • Juliana Freire

    Professor of Computer Science and Engineering at NYU-Poly
    Large-scale information integration; Information visualization and visual analytics; Provenance management;  Big data management and analysis
  • Jonathan Goodman

    Professor of Mathematics
    Monte Carlo methods; Bayesian methods in astrophysics and finance; Stochastic and deterministic optimization
  • Leslie Greengard

    Professor of Mathematics
    Quantitative methods in biology and medicine; Scientific computing; Electromagnetics; Acoustics; Fluid dynamics; Solid mechanics.
  • Jennifer Hill

    Associate Professor of Applied Statistics
    Causal inference; Missing data; Bayesian nonparametrics
  • David W. Hogg

    Deputy Director of Center for Data Science; Executive Director of the Moore-Sloan Data Science Environment; Associate Professor of Physics
    Astronomy; Cosmology; Probabilistic inference; MCMC
  • Clifford M. Hurvich

    Leonard N. Stern Professor of Statistics & Operations Research, Doctoral Coordinator of IOMS-Statistics
    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)
  • Panos Ipeirotis

    Associate Professor of Information, Operations and Management Sciences
    Crowdsourcing; Text mining; Web mining; Data mining; Machine learning; Databases
  • John Jost

    Professor of Psychology and Politics
    Experimental social psychology; Public opinion survey research methods; Quantitative and qualitative analysis of behavioral data in the social sciences
  • Steven Koonin

    Director of NYU Center for Urban Science and Progress (CUSP); Professor of Information, Operations & Management Sciences
    Global environmental science
  • Mik Laver

    Professor of Politics; Dean for the Social Sciences
    Crowd-sourced data coding; Automated text analysis; Agent-based modeling
  • Yann LeCun

    Courant Institute of Mathematical Sciences Silver Professor of Computer Science, Neural Science, and Electrical & Computer Engineering
    Machine learning; Computer vision; Mobile robotics; Computational neuroscience.
  • Ying Lu

    Assistant Profesor of Applied Statistics
    Quantitative methodology in social and behavioral sciences; Applications in demography; Health and political behavior; Model selection and hypothesis testing
  • Andrew Majda

    Morse Professor of Arts and Sciences, Professor of Mathematics and Atmosphere/Ocean Science
    Modern applied mathematics: merging asymptotic methods, numerical methods, physical reasoning and rigorous mathematical analysis
  • Michael Overton

    Professor of Computer Science and Mathematics
    Numerical algorithms and theory for convex and non-convex optimization.
  • Patrick Perry

    Assistant Professor of Information, Operations and Management Sciences
    Modern multivariate statistics; Network and text data; Statistical computing
  • Foster Provost

    Professor of Information Systems
    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
  • Michael Purugganan

    Dorothy Schiff Professor of Genomics, Professor of Biology, Dean for Science
    Evolutionary and ecological genomics of plant adaptations.
  • Marc Scott

    Associate Professor of Applied Statistics
    Computationally Intensive Statistics; Categorical Data Models & Clustering Techniques; Statistics in Social Science and Health Applications
  • Dennis Shasha

    Professor of Computer Science
    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
  • Claudio Silva

    Professor of Computer Science and Engineering at NYU-Poly
    Big Data and Urban Systems; Visualization and data analysis; Geometry processing
  • Eero Simoncelli

    Professor of Neural Science, Mathematics, and Psychology
    Probabilistic analysis and representation in biological and machine vision (and audition); Statistical signal and image processing
  • Jeff Simonoff

    Professor of Statistics
    Applications of statistics; Statistical methodology; Statistical properties of modern data analytic methods
  • David Sontag

    Assistant Professor of Computer Science
    Theoretical and practical aspects of machine learning and probabilistic inference; Medical informatics; Information retrieval; Natural language processing
  • Alexander Statnikov

    Assistant Professor, Department of Medicine, Division of Clinical Pharmacology, NYU School of Medicine; Director, Computational Causal Discovery Laboratory, Center for Health Informatics and Bioinformatics
    Computational causal discovery, variable selection, and supervised learning in high-dimensional data; Comprehensive empirical benchmarking of various machine learning methodologies
  • Esteban Tabak

    Professor of Mathematics, Chair of the Department of Mathematics
    Density estimation; Dimensional reduction; Classification; Data-driven optimal transport; Bio-statistics; Data-based medical diagnosis
  • Eric Vanden-Eijnden

    Professor of Mathematics
    Development of mathematical tools and numerical methods for the analysis of dynamical system which are both stochastic and multiscale.
  • S. R. Srinivasa Varadhan

    Interim Director of Center for Data Science; Professor of Mathematics
    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
  • Margaret Wright

    Professor of Computer Science
    Optimization methods in science and engineering, especially derivative-free methods and constrained nonlinear optimization.

Affiliated Faculty

  • Karen Adolph

    Professor in the Department of Psychology and the Center for Neuroscience
    Perceptual-motor learning and development; Open video data sharing
  • Michael Blanton

    Associate Professor in the Department of Physics
    Astronomical spectroscopy and image analysis- clustering statistics in large-scale galaxy maps- demographics of the galaxy population
  • Jan Blustein

    Professor of Health Policy and Medicine
    Quantitative methods in policy research; Health management
  • Jack Buckley

    Associate Professor of Applied Statistics
    Statistical methodology in public policy and education
  • David Cai

    Professor of Mathematics and Neural Science
    Theoretical and computational neuroscience; Applied dynamical systems; Stochastic processes
  • Andrew Caplin

    Silver Professor of Economics
    Combining theoretical and machine learning methods to optimize financial offers and financial decisions at household level
  • Gloria Coruzzi

    Carroll & Milton Petrie Professor
    Gene network analysis; Data mining and visualization; Systems biology and phylogenomics
  • Nathaniel Daw

    Associate Professor of Neural Science and Psychology
    Quantitative methods in neuroscience; Computational neuroscience; Machine learning; Data analysis
  • Rohit Deo

    Professor of Statistics and Operations Research
    Long memory time series; Financial data modeling
  • Halina Frydman

    Professor of Statistics and Operations Research
    Survival analysis; Stochastic models in finance and labor economics; Corporate credit ratings migration; Mixtures of Markov chains
  • Judith D. Goldberg

    Professor of Biostatistics
    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  
  • Marc Gourevitch

    Professor and founding Chair of the Department of Population Health
    Population health metrics; Mapping health
  • Sinan Gunturk

    Associate Professor of Mathematics
    Mathematics of analog-to-digital conversion; Sampling and quantization theory; Sparse representations and redundant representations of data in signal processing; Approximation theory and harmonic analysis methods in data compression
  • Todd Gureckis

    Associate Professor of Psychology
    Computational cognitive science, Unsupervised learning, Active Learning,  Human decision making, Research applications of crowdsourcing
  • Peter Halpin

    Associate Professor
    Psychometrics; Educational data mining; Computer supported collaborative learning and assessment; Scalable methods for non-stationary time series
  • David Heeger

    Professor of Psychology and Neural Science
    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
  • Lisa Hellerstein

    Professor of Computer Science and Engineering
    Computational learning theory; Machine learning; Algorithms; Complexity theory; Discrete mathematics
  • Ming Hu

    Assistant Professor of Biostatistics
    Bayesian analysis in bioinformatics and statistical genetics, with particular focus on analyzing the next generation sequencing data
  • Robert Kohn

    Professor of Mathematical Science
    Image processing, inverse problems, quantitative finance, regret-minimization-based methods for prediction; The calculus of variations; Pattern-formation problems from materials science (describing and explaining material microstructure and its consequences)
  • Petter Kolm

    Director of the Mathematics in Finance M.S. Program, Clinical Associate Professor of Mathematics
    Algorithmic and quantitative trading strategies, Econometrics, Data exploration, Forecasting models, High frequency trading, Portfolio construction, Portfolio optimization, Transaction costs, Risk management
  • Peter Lakner

    Associate Professor of Statistics and Operations Research
    Probability; Stochastic processes; Stochastic optimization and control
  • Jinyang Li

    Associate Professor
    Distributed and networked systems, the systems aspect of Big Data, wireless and mobile systems
  • Mengling Liu

    Associate Professor of Biostatistics
    Semiparametric modeling and inference for survival data, including survival endpoint in joint analysis with longitudinal data
  • Edward Melnick

    Professor of Statistics
    Analysis of time series data; Developing time series models and their statistical properties; Issues related to risk and especially to homeland security
  • Joel Middleton

    Visiting Assistant Professor of Applied Statistics
    Data-driven politics; Design-based estimation and causal inference in randomized experiments; Experiments in voter behavior and political persuasion
  • Bud Mishra

    Professor of Computer Science and Mathematics
    Bayesian and Empirical Bayesian analysis; Shrinkage; Rate-distortion theory; Redescription; Phenomenological models; Model checking and causality analysis
  • Chuck Newman

    Silver Professor of Mathematics
    Probability Theory, especially interacting particle systems and percolation models; Statistical Physics, especially Ising, spin glass and coarsening models Monte Carlo and Analytic approaches to the above areas
  • Bijan Pesaran

    Associate Professor of Neural Science
    Neural dynamics and decision making; Brain-machine interface
  • Keith Ross

    Leonard J. Shustek Chair Professor in Computer Science
    Security and Privacy; Peer-to-Peer Networking; Internet Measurement; Video Streaming; Multi-Service Loss Networks; Content Distribution Networks; Queuing Theory; Markov Decision Processes
  • Youngzhao Shao

    Professor of Biostatistics and Deputy Director of NYU Cancer Institute Biostatistics Shared Resources (BSR)
    Statistical methodology and applications to medical research
  • Torsten Suel

    Professor of Computer Science and Engineering
    Web Search Technology; Algorithms; Databases; Data Compression; Distributed Computation
  • Arun Sundararajan

    Associate Professor of Information, Operations and Management Sciences
    Online privacy; Social network analysis; Computational social science; Causal inference; Econometrics; Text mining
  • Aaron Tennebein

    Professor of Statistics and Actuarial Science
    Sampling; Regression analysis; Application to actuarial problems in mortality estimation; Risk theory
  • Sharon Weinberg

    Professor of Applied Statistics and Psychology
    Application of quantitative methods in the social sciences