Algorithms and Foundations Group

We are the Algorithms and Foundations Group in the Computer Science and Engineering Department at NYU's Tandon School of Engineering. Our group is composed of researchers interested in applying mathematical and theoretical tools to a variety of disciplines in computer science, from machine learning, to systems, to geometry, to computational biology, and beyond. You can visit our individual webpages to learn more. If you would like to join our mailing list (for news, relevant talks, etc.) please request to be added here.

Our department is hiring tenure track faculty this year and one of the priority areas is Theory + X! Please see the official job ad here. This is a late search (the ad was posted in late December 2022) so applications are being accepted on a rolling basis. Please apply early for fullest consideration. You can reach out to Christopher Musco with any questions about the search and position.

We co-host the NYU Theory Seminar with the NYU Courant Theoretical Computer Science Group, held weekly on Thursdays in Manhattan. Visit the page for more information if you would like to attend or give a talk!

Faculty

Boris Aronov

Computational and Combinatorial Geometry, Algorithms

Yi-Jen Chiang

Data Visualization, Motion Planning, Computational Geometry, Algorithms

Chinmay Hegde

Machine Learning, Algorithms, Signal and Image Processing

Lisa Hellerstein

Computational Learning Theory, Machine Learning, Algorithms, Complexity

Christopher Musco

Algorithms, Scalable Machine Learning, Numerical Linear Algebra

Postdocs and Instructors

Pruthuvi Maheshakya Wijewardena

Approximation Algorithms, Distributed and Federated Learning

Tyler Chen

Numerical Linear Algebra, Randomized Algorithms, Quantum Physics

Current Students

Noah Amsel (Ph.D.)

Deep Learning Theory, Numerical Linear Algebra, Continuous Optimization

Aritra Bhowmick (Ph.D.)

Streaming and Sketching Algorithms, Deep Learning, Graphs

Minsu (Daniel) Cho (Ph.D.)

Automated ML, Model Compression, Generative Models, Signal Processing

Majid Daliri (Ph.D.)

Statistics, Information Theory, Optimization, ML theory, Graphs and Networks.

Haya Diwan (Ph.D.)

Algorithms, Machine Learning and AI, Theory of Computation, Discrete Math

Feyza Duman Keles (Ph.D.)

Machine Learning, Deep Learning Theory, Approximation Algos, Randomized Algos

Aarshvi Gajjar (Ph.D.)

Sampling + Sketching, Approximation Theory, High Dimensional Geometry

Ameya Joshi (Ph.D.)

Robust ML, Deep Generative Models, Physics Informed Learning

Danrong Li (M.S.)

Algorithmic Machine Learning and Data Science

Kelly Marshall (Ph.D.)

Machine learning, Deep Reinforcement Learning, Generative Models

Raphael Meyer (Ph.D.)

Statistical Learning Theory, Randomized Algorithms, Optimization

Minh Pham (Ph.D.)

Machine Learning

Apoorv V. Singh (Ph.D.)

Algorithmic Machine Learning, Robust Statistics, Randomized Algorithms

R. Teal Witter (Ph.D.)

Algorithms, Graph Theory, Boolean Functions, ML, Quantum Computing

Indu Ramesh (Ph.D.)

Algorithms, Graph Theory, Computational Geometry

Atsushi Shimizu (M.S.)

Machine Learning, Numerical Linear Algebra, Algorithms