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I am a Ph.D. student in the Electrical Engineering and Computer Science Department at MIT. I am very fortunate to be advised by Professor Patrick Jaillet in the Laboratory for Information & Decision Systems (MIT LIDS). I am also advised by Professor Gabriele Farina. My research interests broadly encompass machine learning theory, statistics, and optimization. Currently, I am focused on computational-statistical trade-offs, the understanding of overparameterized models (including non-convex optimization and generalization), learning dynamics in games and causality.

Prior to MIT, I earned a B.Sc. degree in Computer Engineering from Sharif University of Technology. During my undergrad, I was a research assistant at Max Planck Institute for Intelligent Systems (MPI-IS) under supervision of Professor Bernhard Schölkopf and Professor Stefan Bauer. Besides, I spent a couple of months working with Professor Martin Jaggi at EPFL.

Here is a link to my google scholar.

Recent News

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February 2023
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I am an organizer of the 28th Annual MIT LIDS Student Conference! I will also give a talk about doubly robust causal feature selection.

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January 2023
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I gave a talk at "Causality x AI/ML" about our work "Causal Feature Selection via Orthogonal Search".

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December 2022
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Our workshop proposal "Machine Learning for Drug Discovery (MLDD)" has been accepted to ICLR 2023!

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August 2022
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Our paper "Causal Feature Selection via Orthogonal Search" is accepted to Transactions on Machine Learning Research (TMLR) 2022.

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July 2022
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Our paper "Pyfectious: A probabilistic hierarchical simulator of infectious diseases and fine-grained control measures" will be published in PLOS Computational Biology.

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June 2022
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Our work "GeneDisco: A Benchmark for Experimental Design in Drug Discovery" is accepted for spotlight presentation at ReALML @ ICML.

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April 2022
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Our work on "Federated Learning in Multi-Center Critical Care Research: A Systematic Case Study using the eICU Database" is placed on arXiv.