News

[26 Jan 2024] Our paper How Much Pre-training Is Enough to Discover a Good Subnetwork? has been accepted at Transactions on Machine Learning Research (TMLR). Congratulations to all the co-authors!

[16 Jan 2024] Our paper Adaptive Federated Learning with Auto-Tuned Clients has been accepted at the International Conference on Learning Representations (ICLR), 2024. This is joint work with M. Taha Toghani, Prof. César A. Uribe, and Prof. Tasos Kyrillidis.

[12 Dec 2023] Our paper When is Momentum Extragradient Optimal? A Polynomial-Based Analysis has been accepted at Transactions on Machine Learning Research (TMLR). This is joint work with Prof. Gauthier Gidel, Prof. Tasos Kyrillidis, and Dr. Fabian Pedregosa.

[27 Oct 2023] I co-organized Quantum Information Processing Systems (QuantIPS 2023). Thank you to all the speakers and participants!

[29 Sep 2023] I co-organized Texas Colloquium on Distributed Learning (TL;DR 2023). Thank you to all the speakers and participants!

[19 June 2023] Adaptive Federated Learning with Auto-Tuned Clients via Local Smoothness got accepted at ICML 2023 Federated Learning Workshop. My poster is available here.

[08 May 2023] I started my summer research visit at MILA under the supervision of Prof. Ioannis Mitliagkas and Prof. Gauthier Gidel.

[20 Apr 2023] I completed my PhD Proposal. Committee: Profs. Anastasios Kyrillidis (chair), César A. Uribe, and Nai-Hui Chia.

[07 Feb 2023] I presented Fast Quantum State Tomography via Accelerated Non-convex Programming and Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography at Quantum Information Processing 2023 as poster presentations.

[06 Feb 2023] I was selected as a top reviewer (top-10%) for AISTATS 2023.

[19 Jan 2023] Our paper Fast Quantum State Tomography via Accelerated Non-convex Programming has been accepted at Photonics 2023. A relevant blog post can be found here. This work was also featured in this article.

[08 Dec 2022] I presented Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography at CDC 2022.

[03 Dec 2022] I presented Momentum Extragradient is Optimal for Games with Cross-Shaped Jacobian Spectrum at NeurIPS 2022 Workshop on Optimization for Machine Learning.

[24 Nov 2022] Our paper Fast Quantum State Tomography via Accelerated Non-convex Programming and Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography have been accepted at Quantum Information Processing 2023 for poster presentations.

[20 Oct 2022] Our paper Momentum Extragradient is Optimal for Games with Cross-Shaped Jacobian Spectrum has been accepted at NeurIPS 2022 Workshop on Optimization for Machine Learning.

[28 Jul 2022] I presented Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum at INFORMS 2022.

[28 Jul 2022] I presented Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum at ICCOPT 2022.

[09 Jun 2022] Our paper Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography has been accepted at the IEEE Control Systems Letters (L-CSS), 2022. This is joint work with M. Taha Toghani, Prof. César A. Uribe, and Prof. Tasos Kyrillidis.

[09 May 2022] I started my research intenship at Meta (FAIR) under the supervision of Dr. Aaron Defazio.

[23 Mar 2022] Our new paper Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography is available on arXiv. This is joint work with M. Taha Toghani, Prof. César A. Uribe, and Prof. Tasos Kyrillidis.

[01 Mar 2022] Our paper Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum has been accepted at Learning for Dynamics and Control (L4DC) 2022.

[27 Oct 2021] I presented Fast Quantum State Tomography via Accelerated Non-convex Programming at INFORMS 2021.

[20 Oct 2021] Our paper Acceleration and Stability of the Stochastic Proximal Point Algorithm has been accepted for a spotlight presentation at NeurIPS 2021 Workshop on Optimization for Machine Learning.

[24 Jul 2021] I am co-organizing a workshop Beyond first-order methods in ML systems in ICML 2021. (Co-organizers: Albert S. Berahas, Raghu Bollapragada, Rixon Crane, Amir Gholami, Anastasios Kyrillidis, Michael Mahoney, Fred Roosta, and Rachael Tappenden).

[15 Apr 2021] I passed my qualification exam (research project defense). Committee: Profs. Anastasios Kyrillidis (chair), Santiago Segarra, and Richard Baraniuk.

[14 Apr 2021] Our paper Fast Quantum State Tomography via Accelerated Non-convex Programming is on arXiv. A relevant blog post can be found here. This work was also featured in this article.

[01 Dec 2019] I officially joined OptimaLab led by Prof. Anastasios Kyrillidis.

[25 Aug 2019] I started my Ph.D. studies in Computer Science at Rice University.