R. Teal Witter

370 Jay St. Brooklyn NY, 11201 • rtealwitter [at] nyu.edu • CVGithubGoogle Scholar

I am a PhD candidate at NYU Tandon where I am fortunate to be co-advised by Lisa Hellerstein and Chris Musco. My research is generously supported by an NSF Graduate Research Fellowship. I am broadly interested in algorithms, complexity theory, and discrete math.

I received my undergraduate degrees in Mathematics and Computer Science from Middlebury College. At Middlebury, I designed quantum algorithms for graph theory problems with Shelby Kimmel and worked on applications of math in recreational board games with Alex Lyford.


NYU Tandon

PhD in Computer Science • September 2020 - Present

Middlebury College

BA in Math, Computer Science • Summa Cum Laude • February 2017 - May 2020


Note: As is the tradition in theoretical computer science, authors are ordered alphabetically by last name unless otherwise noted with an asterisk.

How to Quantify Polarization in Models of Opinion Dynamics

Christopher Musco, Indu Ramesh, Johan Ugander, and R. Teal Witter

17th International Workshop on Mining and Learning with Graphs (MLG 2022)

Backgammon is Hard

R. Teal Witter

15th International Conference on Combinatorial Optimization and Applications (COCOA 2021)

A Query-Efficient Quantum Algorithm for Maximum Matching on General Graphs

Shelby Kimmel and R. Teal Witter

17th Algorithms and Data Structures Symposium (WADS 2021)

Applications of Graph Theory and Probability in the Board Game Ticket to Ride

R. Teal Witter and Alex Lyford*

15th International Conference on the Foundations of Digital Games (FDG 2020)

Applications of the Quantum Algorithm for st-Connectivity

Kai DeLorenzo, Shelby Kimmel, and R. Teal Witter

14th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2019)


Course Assistant at NYU Tandon

CS-GY 6763: Algorithmic Machine Learning and Data Science (Fall 2021, Spring 2022)

CS-GY 6923: Machine Learning (Spring 2021)

Course Assistant at Middlebury College

MATH 345: Combinatorics (Spring 2020)

MATH 310: Probability (Fall 2019)

MATH 223: Multivariable Calculus (Spring 2019)

MATH 200: Linear Algebra (Fall 2018)

CSCI 302: Algorithms and Complexity (Spring 2020)

CSCI 333: Quantum Computing (Fall 2019)

CSCI 201: Data Structures (Spring 2019)

CSCI 200: Math Foundations of Computing (Spring, Fall 2018)