Amir Azarmehr

azarmehr.a at northeastern dot edu
Google Scholar, DBLP, CV

I am a PhD student in computer science at Northeastern University, where I am advised by Soheil Behnezhad.
I am broadly interested in theoretical computer science, combinatorial optimization, and randomized algorithms. My research is currently focused on the theoretical aspects of big-data graph algorithms, which includes graph algorithms in the sublinear, streaming, and dynamic regimes.
Before joining Northeastern I received BSc degrees in computer science and math from Sharif University.

Publications

Single-Pass Streaming CSPs via Two-Tier Sampling
Amir Azarmehr, Soheil Behnezhad, Shane Ferrante,
arXiv

Half-Approximating Maximum Dicut in the Streaming Setting ( STOC '26 )
Amir Azarmehr, Soheil Behnezhad, Shane Ferrante, Mohammad Saneian
arXiv

Lower Bounds for Non-adaptive Local Computation Algorithms ( FOCS '25 )
Amir Azarmehr, Soheil Behnezhad, Alma Ghafari, Madhu Sudan
arXiv

Tight Pair Query Lower Bounds for Matching and Earth Mover’s Distance ( FOCS '25 )
Amir Azarmehr, Soheil Behnezhad, Mohammad Roghani, Aviad Rubinstein
arXiv

Stochastic Matching via In-n-Out Local Computation Algorithms ( STOC '25 )
Amir Azarmehr, Soheil Behnezhad, Alma Ghafari, Ronitt Rubinfeld
arXiv

Massively Parallel Minimum Spanning Tree in General Metric Spaces ( SODA '25 )
Amir Azarmehr, Soheil Behnezhad, Rajesh Jayaram, Jakub Łącki, Vahab Mirrokni, Peilin Zhong
arXiv

Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS ( ICML '24 )
Amir Azarmehr, Soheil Behnezhad, Mohammad Roghani
arXiv

Fully Dynamic Matching: (2-√2)-Approximation in Polylog Update Time ( SODA '24 )
Amir Azarmehr, Soheil Behnezhad, Mohammad Roghani
arXiv

Robust Communication Complexity of Matching: EDCS Achieves 5/6 Approximation ( ICALP '23 )
Amir Azarmehr, Soheil Behnezhad
arXiv