Hi! I'm Maryam Negahbani,

a Ph.D. candidate in Computer Science at Dartmouth College under supervision of Prof. Deeparnab Chakrabarty. My research interest is broadly Approximation Algorithms and Combinatorial Optimization. Currently my focus is on Clustering Algorithms: Improving approximation ratios, proving hardness of approximation, fairness and other generalizations.

I got my B.Sc. from University of Isfahan, Iran and my M.Sc. from Sharif University of Technology, Iran. I've interned at Google Research last Summer. Here is my resume:

email

maryam@cs.dartmouth.edu

LinkedIn

linkedin.com/in/maryamnegahbani

profile_image

Publications


Better Algorithms for Individually Fair k-Clustering [arxiv] [GitHub]
with D. Chakrabarty,
In Conference on Neural Information Processing Systems [NeurIPS] 2021

Revisiting Priority k-Center: Fairness and Outliers [YouTube] [arxiv]
with T. Bajpai, D. Chakrabarty, and C. Chekuri
In International Colloquium on Automata [ICALP] 2021

Robust k-Center with Two Types of Radii [YouTube] [arxiv]
with D. Chakrabarty,
In Integer Programming and Combinatorial Optimization [IPCO] 2021

Generalized Center Problems with Outliers [arxiv]
with D. Chakrabarty,
In ACM Transactions on Algorithms [TALG] 2019
First version appeared in International Colloquium on Automata [ICALP] 2018

Fair Algorithms for Clustering [arxiv]
with S. Bera, D. Chakrabarty, and N. J. Flores,
In Conference on Neural Information Processing Systems [NeurIPS] 2019