## About Us

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 talk announcements, etc.) please email Professor Boris Aronov or Christopher Musco.

We are looking for independent and mathematically mature Ph.D. students to join our group beginning in the 2022-2023 academic year. You should be interested in algorithms, theoretical computer science (TCS), theoretical machine learning, applied mathematics, or related areas. All applications should be made directly to NYU Tandon's Ph.D. program in CSE.

## 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

## Affiliated Faculty

## Postdocs

## Current Students

##### Minsu (Daniel) Cho (Ph.D.)

Automated ML, Model Compression, Generative Models, Signal Processing

##### Aarshvi Gajjar (Ph.D.)

Statistical Machine Learning, Randomized Dimensionality Reduction

##### Gauri Jagatap (Ph.D.)

Machine Learning, Signal Processing, Generative Models, Model Compression

##### Ameya Joshi (Ph.D.)

Robust ML, Deep Generative Models, Physics Informed Learning

##### 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

##### Xinyu Luo (M.S.)

Machine Learning, Approximation Algorithms, High-dimensional Geometry, Random Matrix Theory

##### Indu Ramesh (M.S.)

Algorithms, Graph Theory, Computational Geometry