Faculty Research Areas

Faculty Research Areas




Our unique program encompasses the interdisciplinary study of both natural & social science subjects as well as contemporary scientific methods and technologies such as machine learning & artificial intelligence, applied mathematics, computer vision, astronomy, physics, neuroscience, biology, political science, ethics, and data governance.

Below is an overview of what field/area each of our faculty members covers and specializes in.


Joint Faculty

Sam Bowman
Associate Professor of Linguistics and Data Science

  • Natural language processing
  • Artificial neural networks
  • Computational semantics

Joan Bruna
Associate Professor of Computer Science and Data Science

  • Machine learning
  • Signal processing
  • High-dimensional statistics

Kyunghyun Cho
Associate Professor of Computer Science and Data Science

  • Machine learning
  • Natural language processing (NLP)
  • Application of data science in medicine

Carlos Fernandez-Granda
Associate Professor of Mathematics and Data Science

  • Applied mathematics
  • Inverse problems
  • Machine learning
  • Signal processing
  • Applications in healthcare

Juliana Freire
Professor of Computer Science and Engineering and Data Science

  • Big data
  • Data analysis and visualization
  • Provenance management and analytics
  • Computational reproducibility
  • Scientific data management
  • Large-scale information integration
  • Data quality
  • Web information retrieval and analysis
  • Web crawling
  • Spatio-temporal analytics

He He
Assistant Professor of Computer Science and Data Science

  • Machine learning
  • Natural language processing
  • Dialogue and communication

Yanjun Han
Assistant Professor of Mathematics and Data Science (starting fall 2023)

  • Statistical machine learning
  • High-dimensional and nonparametric statistics
  • Online learning and bandits
  • Information theory

Julia Kempe
Professor of Computer Science, Mathematics and Data Science

  • Mathematics of data science
  • Machine learning
  • Connections to quantum computation
  • Data Science applied to problems in physics and material science

Brenden Lake
Assistant Professor of Psychology and Data Science

  • Computational cognitive modeling
  • Machine learning
  • Structured probabilistic models
  • Deep learning

Qi Lei
Assistant Professor of Mathematics and Data Science

  • Machine learning
  • Deep learning
  • Optimization

Grace Lindsay
Assistant Professor of Psychology and Data Science

  • Neuroscience
  • Sensory Processing
  • Machine learning

Tal Linzen
Assistant Professor of Linguistics and Data Science

  • Computational linguistics
  • Computational cognitive science
  • Human language comprehension and processing

Brian McFee
Assistant Professor of Music Technology and Data Science

  • Machine learning
  • Music information retrieval
  • Recommender systems
  • Multimedia signal processing

Jonathan Niles-Weed
Assistant Professor of Mathematics and Data Science

  • Statistics
  • Information theory
  • Optimization
  • Mathematics of data science
  • Optimal transport

Rajesh Ranganath
Assistant Professor of Computer Science and Data Science

  • Probabilistic modeling
  • Approximate inference
  • Bayesian nonparametric statistics
  • Machine learning for healthcare and causal inference

Mengye Ren
Assistant Professor of Computer Science and Data Science

  • Machine learning
  • Computer vision
  • Meta-learning
  • Representation learning

Cristina Savin
Assistant Professor of Neural Science and Data Science

  • Computational neuroscience
  • Machine learning
  • Time series models
  • Bayesian nonparametrics

Claudio Silva
Professor of Computer Science and Engineering and Data Science

  • Data science
  • Urban computing
  • Sports analytics
  • Visualization and graphics
  • Geometry processing

Arthur Spirling
Professor of Politics and Data Science

  • Quantitative analysis of political behavior
  • Institutional development and the use of text-as-data
  • Political methodology
  • Data science

Julia Stoyanovich
Associate Professor of Computer Science and Engineering and Data Science

  • Computer science
  • Data and knowledge management
  • Ethical data management and analysis
  • Management and analysis of evolving graphs
  • Management and analysis of preference data

Andrew Wilson
Associate Professor of Computer Science and Data Science

  • Probabilistic modeling
  • Bayesian deep learning
  • Gaussian processes
  • Foundations of machine learning


Associated Faculty

Richard Bonneau
Professor of Biology, Computer Science and Data Science

  • Systems biology and protein modeling

Vasant Dhar
Professor of Information Systems and Data Science

  • Prediction
  • Data mining
  • Artificial intelligence
  • Decision making

Rob Fergus
Associate Professor of Computer Science and Data Science

  • Computer vision
  • Large-scale object recognition
  • Deep learning
  • Machine learning
  • Statistical methods in astronomy
  • Computational photography

Jennifer Hill
Professor of Applied Statistics and Data Science

  • Causal inference
  • Missing data
  • Bayesian nonparametrics

David W. Hogg
Professor of Physics and Data Science

  • Astronomy
  • Cosmology
  • Probabilistic inference
  • MCMC

Panos Ipeirotis
Professor of Information, Operations and Management Sciences and Data Science

  • Crowdsourcing
  • Machine learning
  • Integrating human and machine intelligence
  • Text and web mining
  • Data management

Yann LeCun
Silver Professor of Computer Science, Neural Science, Electrical and Computer Engineering and Data Science

  • Machine learning
  • Computer vision
  • Mobile robotics
  • Computational neuroscience

Foster Provost
Professor of Information Systems and Data Science

  • Data science
  • Data mining
  • Machine learning
  • Predictive modeling
  • Integrating human and machine computation
  • Inference in network data
  • Social network analysis
  • Crowdsourcing
  • Micro-outsourcing systems

S.R. Srinivasa Varadhan
Professor of Mathematics and Data Science

  • Probability theory 
  • Stochastic processes

Eero Simoncelli
Professor of Neural Science, Mathematics, Psychology and Data Science

  • Probabilistic analysis/representation in biological and machine vision
  • Statistical signal and image processing


Affiliated Shanghai Faculty

Mathieu Laurière
Assistant Professor of Mathematics and Data Science NYU Shanghai

  • Mean field control and mean field games numerical methods
  • Partial differential equations
  • Stochastic analysis
  • Machine learning
  • Complexity theory and quantum computing

Shuyang Ling
Assistant Professor of Data Science, NYU Shanghai

  • Applied mathematics
  • Optimization
  • Probability
  • Signal processing
  • Mathematics of data science
  • Machine learning