Trung Le, PhD

Trung Le, PhD

Postdoctoral Fellow

Emory University

Trung is a Postdoctoral Fellow in the Coulter Department of Biomedical Engineering at Emory University. His research lies at the intersection of machine learning and systems neuroscience. In particular, he is interested in studying how dynamical modeling approaches can support robust decoding across time, behavioral contexts, and individuals, with applications in speech and motor neuroprostheses.

Trung received his BS from Texas A&M University in 2017, his MS from University of California, Los Angeles in 2020, and his PhD from University of Washington in 2025, all in Electrical and Computer Engineering. His doctoral research focused on developing computational models leveraging properties of neural dynamics to improve representation learning, cell type identification, and behavior decoding. During his postdoctoral fellowship, he is working to extend these approaches toward scalable neural decoding systems suitable for long-term online deployment.

In his free time, he enjoys hiking, listening to podcasts, and practicing piano.

Interests
  • NeuroAI
  • brain-computer interfaces
  • neural dynamics
  • cats, especially if they are black
Education

  • PhD in Electrical and Computer Engineering, 2025

    University of Washington

  • MS in Electrical and Computer Engineering, 2020

    University of California, Los Angeles

  • BS in Electrical Engineering, 2017

    Texas A&M University

Publications

A generalizable speech neuroprosthesis

bioRxiv (2026)

Zachery M. Fogg, Nicholas S. Card, Maitreyee Wairagkar, Aparna Srinivasan, Tyler Singer-Clark, Xianda Hou, Elizaveta Okorokova, Hamza Peracha, Carrina Iacobacci, Tiffany Brailow, Justin Jude, Hadar Levi-Aharoni, Trung Le, Domenick Mifsud, Pranav I. Deevi, Samuel R. Nason-Tomaszewski, Anna L. Pritchard, Yunnuo Zhang, Brice Richards, Payton Bechefsky, Leigh R. Hochberg, Ziv Williams, Kiarash Shahlaie, Nicholas AuYong, Daniel B. Rubin, Chethan Pandarinath, David M. Brandman, Sergey D. Stavisky
PDF DOI
A generalizable speech neuroprosthesis