About Me

I am an assistant professor at the Department of Computer Science at Vanderbilt University. My research is motivated by the challenges facing today’s machine learning (ML) algorithms for deployment in critical physical world applications. My research lab, Machine Intelligence and Neural Technologies (MINT), focuses on creating the next generation of core machine learning algorithms that are mathematically grounded, uncertainty aware, label-efficient, and can continually learn from the nonstationary and never-ending data stream. Among recent directions that my team and I have contributed to are: 1) single and multi-agent lifelong learning machines as part of three Defense Advanced Research Projects Agency (DARPA) programs, 2) uncertainty-aware deep learning as part of the DARPA Enabling Confidence program, 3) geometric deep learning, and 4) applications of optimal mass transportation theory in ML and computer vision. I am an inventor of over 20 issued patents and have over 50 published articles in high-impact machine learning, computer vision, and signal processing journals and conferences.

[Open Positions] I am recruiting motivated PhD students with strong mathematical background to work with me on topics aligned with my lab's 'research directions'. Master’s and undergraduate students within Vanderbilt University and visiting scholars are always welcome. Please refer to my lab's website for more information.


  • Congratulations to my postdoctoral research assistant, Dr. Yikun Bai, for acceptance of his paper at CVPR 2023.
  • Congratulations to my students Zihao (Harry) Wu (CS Undergrad) and Huy Tran for acceptance of their paper to IEEE ICASSP 2023.
  • Congratulations to my student Ali Abbasi for acceptance of his paper to the Proceedings of the Conference on Lifelong Learning Agents, 2022.
  • Our paper on "Generalized Sliced Probability Metrics'' received the Best Paper Award from IEEE ICASSP 2022 - May 27, 2022
  • Our Machine Learning Seminars are now available on YouTube! - Feb 20, 2022
  • I gave a talk at the One World Seminar on the Mathematics of Machine Learning focused on "Wasserstein Embeddings." (Video) - Nov 24, 2021.
  • Our paper 'Pooling by Sliced Wasserstein Embedding' got accepted to NeurIPS 2021 - Oct 06, 2021.
  • I joined Vanderbilt University as an Assistant Professor of Computer Science - Aug 16, 2021.
  • Our paper 'Wasserstein Embedding for Graph Learning' got accepted to ICLR2021 for a poster presentation - Jan 07, 2021.
  • Our paper 'Statistical and Topological Properties of Sliced Probability Divergences' got accepted to NeurIPS2020 for a spotlight presentation - Sep 25, 2020.