On this page: Overview • Areas • PhD Advisory Group
Overview
This page is designed to guide prospective and current PhD students in the Data Science program at CDS. It provides a detailed overview of the various research areas within the program and highlights the faculty members who specialize in each domain. Whichever area of data science you’re interested in, this resource helps you identify the professors whose expertise aligns with your research interests. By exploring the faculty members listed under each research area, you can find potential mentors, collaborators, and advisors who can support your academic journey.
Areas
Machine Learning and Perception
- Audio Processing
- Computer Vision
- Data Annotation and Crowdsourcing
- Deep Learning
- Image Processing
- Natural Language Processing
- Probabilistic Modeling
- Reinforcement Learning
Theory
- High-Dimensional Statistics
- Inverse Problems
- Optimization
- Probabilistic Modeling
- Theory of Deep Learning
Data Engineering & Data Visualization
- AutoML
- Big Data
- Explainable Artificial Intelligence
- Visualization
Medical School Track
- Automatic Diagnostics
- Medical Imaging
- Sensor Analytics
- Image Processing
Responsible AI
- Algorithmic Fairness & Diversity
- Data Governance
- Ethics and Legal Compliance
- Reproducibility
- Transparency & Interpretability
The PhD Advisory Group
- Emily Black
- Sam Bowman
- Joan Bruna
- Kyunghyun Cho
- Eunsol Choi
- SueYeon Chung
- Vasant Dhar
- Martin Farach-Colton
- Rob Fergus
- Carlos Fernandez-Granda
- Juliana Freire
- Todd Gureckis
- Yanjun Han
- He He
- Julia Kempe
- Brenden Lake
- Yann LeCun
- Qi Lei
- Grace Lindsay
- Tal Linzen
- Romain Lopez
- Brian McFee
- Jonathan Niles-Weed
- Sunoo Park
- Rajesh Ranganath
- Oded Regev
- Mengye Ren
- Cristina Savin
- Claudio Silva
- Eero Simoncelli
- Julia Stoyanovich
- Andrew Wilson
- Laure Zanna