News

• [03/04/24] I am giving a talk at Georgia Tech's ARC Colloquium Seminar Series on the Power of Adaptivity in SGD.
• [12/15/23] I attended the NeurIPS'23 workshop, Algorithmic Fairness through the Lens of Time, where Jessica and I presented our poster, On Mitigating Unconscious Bias through Bandits with Evolving Biased Feedback.
• [12/07/23] I successfully gave my Progress Review at UT Austin.
• [09/28/23] I attended Allerton, where Constantine presented our work on Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD in the Learning and Networks III session.
• [09/06/23] I am organizing the ML Tea seminar series at UT Austin this year. We'll have weekly whiteboard talks by student speakers. Feel free to reach out to me if you'd like to give a talk on your work!
• [07/15/23] I presented our work on Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD at the Stochastic optimization session at COLT'23. Here are the slides.
• [06/09/23] I received Dr. Brooks Carlton Fowler Endowed Presidential Graduate Fellowship in Electrical and Computer Engineering from the Cockrell School of Engineering for the 2023-2024 academic year.
• [05/14/23] One paper accepted to COLT 2023, Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD!
• [04/21/23] I presented our work on Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD at the IFML Workshop hosted at University of Washington.
• [02/13/23] New paper on arXiv, Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD!
• [10/06/22] I presented our work on The Power of Adaptivity in SGD at a poster session in the Joint IFML/Data-Driven Decision Processes Workshop at the Simons Institute.
• [07/26/22] I attended the Joint IFML/SFI meeting on Foundations of Machine Learning, where Sanjay presented our work on The Power of Adaptivity in SGD.
• [07/04/22] I presented our work on The Power of Adaptivity in SGD in the Optimization I session at COLT'22. Here are the slides.
• [06/09/22] I presented our work on Learning To Maximize Welfare with a Reusable Resource in the Optimization II session at SIGMETRICS'22. Here are the slides.
• [05/14/22] One paper accepted to COLT 2022, The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance!
• [03/28/22] One paper accepted to SIGMETRICS 2022, Learning To Maximize Welfare with a Reusable Resource!
• [02/11/22] New paper on arXiv, The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance!
• [01/10/22] I presented our work on Single Sample Prophet Inequalities at SODA'22. Here are the slides.
• [11/02/21] I attended the Joint IFML/CCSI Symposium at Simons in UC Berkeley.
• [10/02/21] One paper accepted to SODA 2022: Single Sample Prophet Inequalities via Greedy-Ordered Selection (supersedes Single-Sample Prophet Inequalities Revisited)
• [03/24/21] New paper on arXiv, Single-Sample Prophet Inequalities Revisited!
• [12/09/20] I presented our Mix & Match paper at the virtual NeurIPS 2020 poster session.
• [09/25/20] One paper accepted to NeurIPS 2020!
• [05/26/20] I received a fellowship from the NXP Foundation for the 2020-2021 academic year.
• [11/12/19] I presented a poster of our paper, Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions, at the Texas Wireless Summit at UT Austin.
• [10/09/19] New paper on arXiv, Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions!
• [08/29/18] I started graduate school at UT Austin!