New York University

Andrew Gordon WilsonProfessor of Computer Science and Data Science

Works on Bayesian deep learning, Gaussian processes and generalization in neural networks, with numerical linear algebra for scalable inference.

• Probabilistic & causal inference
• Learning theory & optimization
• Efficient training & inference

Yann LeCunJacob T. Schwartz Chaired Professor in Computer Science

Works on deep learning and self-supervised learning, including convolutional networks, energy-based models and joint-embedding world models.

• Generative & foundation models

Saining XieAssistant Professor of Computer Science

Studies computer vision and representation learning, including visual backbones, multimodal large language models and diffusion transformers.

• Vision-language & multimodal
• Image & video generation
• Large language models

Kyunghyun ChoGlen de Vries Chaired Professor of Computer Science and Data Science

Works on deep learning for natural language, including neural machine translation, language models and machine learning for scientific discovery.

• Large language models
• Multilingual, translation & linguistics

Qiaoyu TanAssistant Professor

Studies graph machine learning, graph foundation models and multimodal learning, with applications in bioinformatics and healthcare.

• Graph mining & networks
• Generative & foundation models
• Graph learning

Chen FengInstitute Associate Professor

Directs the AI4CE Lab, working on active and collaborative robot perception, visual SLAM and robot learning for construction, manufacturing and transportation.

• Robot perception & SLAM
• Manipulation & robot learning
• Human-AI collaboration & trust

Christopher MuscoInstitute Associate Professor

Studies algorithmic foundations of machine learning and data science, including randomized numerical linear algebra, sketching and active learning.

• Data management & big data

He HeAssociate Professor of Computer Science and Data Science

Studies natural language processing and machine learning, focusing on robustness, reasoning and the trustworthiness of language models.

• Interpretability, evaluation & safety of LMs
• Large language models
• Trustworthy & safe ML

Eunsol ChoiAssociate Professor of Computer Science and Data Science

Studies natural language processing, with a focus on question answering, retrieval-augmented language models and keeping model knowledge up to date.

• Knowledge, QA & retrieval
• Large language models

Julia KempeSilver Professor of Computer Science, Mathematics and Data Science

Studies the foundations of machine learning, including scaling behavior, synthetic data and robustness, alongside quantum computing.

• Trustworthy & safe ML

Greg DurrettAssociate Professor of Computer Science and Data Science

Studies natural language processing with large language models, including reasoning, factuality checking and explanation of model outputs.

• Large language models
• Reasoning & agents
• Human-AI collaboration & trust

Lerrel PintoAssociate Professor of Computer Science

Studies robot learning for manipulation, including learning from human demonstrations and home robots that generalize to new environments.

• Manipulation & robot learning

Qi SunAssociate Professor

Leads the Immersive Computing Lab, studying perception-aware VR/AR graphics, wearable displays and computational perception.

• VR, AR & immersive media
• Rendering & appearance
• Robot perception & SLAM

Chen ZhaoAssistant Professor

Studies natural language processing, focusing on reasoning, question answering and robustness of language agents.

• Reasoning & agents
• Knowledge, QA & retrieval
• Trustworthy & safe ML

Farshad KhorramiProfessor (IEEE Fellow); Co-Founder of Center for AI and Robotics (2021); Co-Director of Center for AI and Robotics (2021-Present)

Leads the Control/Robotics Research Laboratory, working on autonomous unmanned vehicles, machine learning for robotics and cyber-physical system security.

• Manipulation & robot learning
• Planning, control & multi-robot systems
• Embodied & active vision

Mengye RenAssistant Professor of Computer Science and Data Science

Studies machine learning and computer vision for agents that learn continually from few examples and from naturalistic visual experience.

Rajesh RanganathAssociate Professor of Computer Science and Data Science

Develops probabilistic and causal inference methods, with applications to machine learning in healthcare and medicine.

• Probabilistic & causal inference
• Efficient training & inference

Tal LinzenAssociate Professor of Linguistics and Data Science

Studies language models and computational psycholinguistics, comparing how neural networks and humans learn syntax and generalize.

• Multilingual, translation & linguistics
• Large language models
• Data management & big data

Julia StoyanovichAssociate Dean of AI Initiatives; Professor; Director of the Center for Responsible AI

Works on responsible AI and data management, including fairness in ranking, data equity and AI governance and education.

• Trustworthy & safe ML
• Social computing & responsible AI
• Data management & big data

Qi LeiAssistant Professor of Mathematics and Data Science

Studies machine learning theory, including representation learning, distribution shift and data privacy in deep learning.

• Learning theory & optimization
• Trustworthy & safe ML
• Data management & big data