Mahsa Derakhshan
Assistant Professor
Research interests
- Online algorithms
- Algorithms for stochastic graphs
- Algorithmic game theory
- Mechanism design
Education
- PhD in Computer Science, University of Maryland
Biography
Mahsa Derakhshan is an assistant professor in the Khoury College of Computer Sciences at Northeastern University. Prior to that, she was a FODSI fellow at UC Berkeley and also a postdoctoral researcher at Princeton University in the department of computer science.
She is broadly interested in the design and analysis of algorithms. Mainly, she studies algorithms under uncertainty. A few sources of such uncertainty in her research are having stochastic data, limited access to information, and the presence of strategic behavior. She primarily studies problems with applications to markets, such as matching markets and auctions.
Recent publications
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New Philosopher Inequalities for Online Bayesian Matching, via Pivotal Sampling
Citation: Mark Braverman, Mahsa Derakhshan, Tristan Pollner, Amin Saberi, David Wajc. (2025). New Philosopher Inequalities for Online Bayesian Matching, via Pivotal Sampling SODA, 3029-3068. https://doi.org/10.1137/1.9781611978322.98 -
Stochastic Minimum Vertex Cover in General Graphs: A 3/2-Approximation
Citation: Mahsa Derakhshan, Naveen Durvasula, Nika Haghtalab. (2023). Stochastic Minimum Vertex Cover in General Graphs: A 3/2-Approximation STOC, 242-253. https://doi.org/10.1145/3564246.3585230 -
Learning and Collusion in Multi-unit Auctions
Citation: Simina Brânzei, Mahsa Derakhshan, Negin Golrezaei, Yanjun Han. (2023). Learning and Collusion in Multi-unit Auctions NeurIPS. http://papers.nips.cc/paper_files/paper/2023/hash/4661b55200c03a8c4bb9c2974b4fb12d-Abstract-Conference.html -
Beating (1 – 1/e)-Approximation for Weighted Stochastic Matching
Citation: Mahsa Derakhshan, Alireza Farhadi . (2023). Beating (1 - 1/e)-Approximation for Weighted Stochastic Matching SODA, 1931-1961. https://doi.org/10.1137/1.9781611977554.ch74 -
Max-Weight Online Stochastic Matching: Improved Approximations Against the Online Benchmark
Citation: Mark Braverman, Mahsa Derakhshan, Antonio Molina Lovett. (2022). Max-Weight Online Stochastic Matching: Improved Approximations Against the Online Benchmark EC, 967-985. https://doi.org/10.1145/3490486.3538315 -
Stochastic Vertex Cover with Few Queries
Citation: Soheil Behnezhad, Avrim Blum, Mahsa Derakhshan. (2022). Stochastic Vertex Cover with Few Queries SODA, 1808-1846. https://doi.org/10.1137/1.9781611977073.73 -
Stochastic Weighted Matching: (Stochastic Weighted Matching: (1-ε) Approximation -\varepsilon$) Approximation
Citation: Soheil Behnezhad, Mahsa Derakhshan. (2020). Stochastic Weighted Matching: (Stochastic Weighted Matching: (1-ε) Approximation -varepsilon$) Approximation FOCS, 1392-1403. https://doi.org/10.1109/FOCS46700.2020.00131 -
Beating Greedy For Approximating Reserve Prices in Multi-Unit VCG Auctions
Citation: Mahsa Derakhshan, David M. Pennock, Aleksandrs Slivkins. (2021). Beating Greedy For Approximating Reserve Prices in Multi-Unit VCG Auctions SODA, 1099-1118. https://doi.org/10.1137/1.9781611976465.68
Current PhD students
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Andisheh Ghasemi
PhD Student
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Tao Yu
PhD Student