Aryan Mokhtari
- Assistant Professor, Dept. of Electrical & Computer Engineering (ECE), UT Austin
- Jack Kilby/Texas Instruments Endowed Faculty Fellowship in Computer Engineering
- Affiliated with:
- Google Scholar / Twitter / CV
News
- Apr. ’24: Google Research Scholar Award. (Announcement)
- Apr. ’24: New paper: “Non-asymptotic Global Convergence Rates of BFGS with Exact Line Search” [pdf]
- Feb. ’24: New Talk: “In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness” [Sildes]
- Based on the following paper: [pdf]
- Jan. ’24: NSF CAREER Award.
- Jan. ’24: Paper at AISTATS 2024:
- Oct. ’23: New Talk: “Online Learning Guided Quasi-Newton Methods: Improved Global Non-asymptotic Guarantees” [Slides]
- Based the following COLT 2023 and NeurIPS 2023 papers.
- Sep. ’23: Papers at NeurIPS 2023:
- June ’23: New short talk on Bilevel Optimization at SIAM Conference on Optimization. [Slides][Paper]
- May ’23: Papers at COLT 2023:
Support
My research is supported by an NSF CAREER Award CCF-2338846, NSF Grants CCF-2007668 and ECCS-2127697, an ARO Early Career Program (ECP) Award, the NSF AI Institute for Foundations of Machine Learning (IFML), the NSF AI Institute for Future Edge Networks and Distributed Intelligence (AI-EDGE), and the Machine Learning Laboratory at UT Austin.