Theoretical Computer Science at NYU

This page maintains a list of graduate topics courses that may be of interest to students working in theory, including courses at other institutions in NYC. Please contact faculty or department administrators directly for questions about enrollment.

Fall 2026

New York University

CSCI-GA.3033-137: Information Theory and Applications in Computer Science. Instructor: Marshall Ball.

CSCI-GA.3033-139: Quantum Cryptography. Instructor: Fermi Ma.

CSCI-GA.3033-140: Honors Machine Learning. Instructor: Gautam Kamath.

CSCI-GA.3033-141: Theoretical Foundations in Modern Machine Learning. Instructor: Allen Liu.

CSCI-GA.3033-142: Quantum Information. Instructor: Tony Metger.

CS-GY 6763: Algorithmic Machine Learning and Data Science. Instructor: Ainesh Bakshi.

CS-GY 9223 N: Modern Paradigms in Learning and Decision-Making. Instructor: Juan Carlos Perdomo.

CSCI-GA.3210-001: Introduction To Cryptography. Instructor: Nir Bitansky.

CSCI-GA.3520-001: Honors Analysis of Algorithms. Instructor: Subhash Khot.

CS-GY 6043: Design and Analysis of Algorithms II. Instructor: Aaron Bernstein.

Columbia

COMS E 6998-002: Adv Tpcs Competitive Prog. Instructor: Josh Alman.

COMS E 6998-010: Algos Large Lang Models. Instructor: Alexandr Andoni.

COMS E 6298-002: Boolean Function Analysis. Instructor: Rocco A. Servedio.

COMS E 6998-012: Computation And The Brain. Instructor: Christos H. Papadimitriou.

COMS E 6298-001: Intro Property Testing. Instructor: Xi Chen.

COMS W 4236-001: Introduction To Computational Complexity. Instructor: Toniann Pitassi.

COMS W 4281-001: Introduction to Quantum Computing. Instructor: Henry Yuen.

COMS E 4773-001: Machine Learning Theory. Instructor: Daniel J. Hsu.