I am a first-year computer science Ph.D. student at Stanford University broadly interested in quantum computing and theoretical computer science. During Summer 2026, I will be a Student Researcher at Google Quantum AI in Venice, CA.

I received my B.A. in computer science and astrophysics at the University of California, Berkeley. As an undergraduate, I was fortunate to be mentored by John Preskill, Jason Li, Jelani Nelson, and Lili Su, among many others.

Research

(Authors are ordered by contribution unless denoted “(a)” for alphabetical ordering. ^* denotes equal contribution.)

Optimizing Sparse SYK
Matthew Ding, Robbie King, Bobak T. Kiani, and Eric R. Anschuetz
Quantum 10, 2029 (2026)

Fast and Robust State Estimation and Tracking via Hierarchical Learning
Connor Mclaughlin^*, Matthew Ding^*, Deniz Erdogmus, and Lili Su
IEEE Transactions on Automatic Control 71, 3 (2026)

Space Complexity of Minimum Cut Problems in Single-Pass Streams
(a) Matthew Ding, Alexandro Garces, Jason Li, Honghao Lin, Jelani Nelson, Vihan Shah, and David P. Woodruff
Presented at Innovations in Theoretical Computer Science (ITCS 2025) [Slides]

Deterministic Minimum Steiner Cut in Maximum Flow Time
(a) Matthew Ding and Jason Li
Presented at European Symposium on Algorithms (ESA 2024) [Slides]

BeeGees: Stayin’ Alive in Chained BFT
Neil Giridharan, Florian Suri-Payer, Matthew Ding, Heidi Howard, Ittai Abraham, and Natacha Crooks
ACM Symposium on Principles of Distributed Computing (PODC 2023)

Teaching

Teaching Assistant
EECS 126: Probability and Random Processes (UC Berkeley, Spring 2025)

Teaching Assistant
CS 70: Discrete Mathematics and Probability Theory (UC Berkeley, Fall 2024)

Notes

Lecture 24 Notes: The Sensitivity Conjecture
CS 294-92: Analysis of Boolean Functions (UC Berkeley, Spring 2025)

Lecture 12 Notes: Linear probing with 5-wise independence, symmetrization, approximate membership
CS 270: Combinatorial Algorithms and Data Structures (UC Berkeley, Spring 2023)