## 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