Peng Zhang's homepage

I am an assistant professor in Computer Science at Rutgers University, and a graduate faculty in Statistics at Rutgers. 

I was a postdoc at Yale University, under the supervision of Prof. Daniel Spielman, during 2018 - 2021. I obtained my Ph.D. from Georgia Tech in 2018, advised by Prof. Richard Peng. Before that, I got my MS from Purdue University in 2015 and my BS from Zhejiang University in 2013.


Hill Center, Room 444

I am broadly interested in the design of algorithms and data science. Specifically, I am interested in solving structured systems of linear equations, discrepancy theory and its applications in causal inference.

My research is generously supported by the National Science Foundation (NSF) (Faculty Early Career Development (CAREER) Award: CCF-2238682), Adobe Data Science Research Award, and Rutgers Research Council Individual Fulcrum Award.


Balancing Covariates in Randomized Controlled Trials with Non-Uniform Treatment Probabilities

with Anup Rao, 2023

Efficient Algorithms for Partitioning Circulant Graphs with Optimal Spectral Approximation 

with Surya Teja Gavva, 2023

Balancing covariates in randomized experiments using the Gram-Schmidt walk 

with Christopher Harshaw, Fredrik Savje, and Daniel Spielman

Journal of the American Statistical Association (JASA), 2023


Efficient $1$-Laplacian Solvers for Well-Shaped Simplicial Complexes  

with Ming Ding

ESA 2023

Hardness Results for Minimizing the Covariance of Randomly Signed Sum of Vectors

Arxiv abs/2211.14658, 2022

Hardness Results for Weaver's Discrepancy Problem  

with Daniel Spielman


Hardness Results for Laplacians of Simplicial Complexes via Sparse-Linear Equation Complete Gadgets 

with Ming Ding, Rasmus Kyng, and Maximilian Probst Gutenberg

ICALP 2022

Two-Commodity Flow is as Hard as Linear Programming under Nearly Linear-Time Reductions 

with Ming Ding and Rasmus Kyng

ICALP 2022

Positive LPs are Hard to Solve Accurately, Assuming Linear Equations are Hard 

with Rasmus Kyng and Di Wang

SODA 2020

Incomplete Nested Dissection 

with Rasmus Kyng, Richard Peng, and Robert Schwieterman

STOC 2018

Hardness Results for Structured Linear Systems 

with Rasmus Kyng

FOCS 2017, won the best student paper award

SIAM Journal on Computing (2020)

On Approximate Pattern Matching with Thresholds 

with Mikhail J. Atallah

Information Processing Letters 123 (2017): 21-26

Approximating the Solution to Mixed Packing and Covering LPs in Parallel O~(ε^{−3}) Time 

with Michael W. Mahoney, Satish Rao, and Di Wang

ICALP 2016

Faster and Simpler Width-Independent Parallel Algorithms for Positive Semidefinite Programming 

with Richard Peng, Kanat Tangwongsan

Arxiv abs/1201.5135, 2016

Optimal Query Complexity for Estimating the Trace of a Matrix 

with Karl Wimmer and Yi Wu

ICALP 2014

Minimizing Seed Set Selection with Probabilistic Coverage Guarantee in a Social Network 

with Wei Chen, Xiaoming Sun, Yajun Wang, and Jialin Zhang


My Ph.D. dissertation:

Hardness and Tractability For Structured Numerical Problems. 2018. Georgia Tech College of Computing Dissertation Award