Cat P. Le received a B.S. degree Summa Cum Laude in Electrical and Computer Engineering from Rutgers University in 2016,
an M.S. degree in Electrical Engineering from California Institute of Technology (Caltech) in 2017, and a Ph.D. degree in
Machine Learning from Duke University in 2023. At Duke University, he worked on Task Affinity and Its Applications in Machine Learning
under the guidance of Dr. Vahid Tarokh. He currently holds a Postdoctoral Research Associate position at Duke University.
His research interest includes Machine Learning, Computer Vision, and Natural Language Processing, focusing on
Transfer Learning, Few-Shot Learning, Continual Learning, Multi-Task Learning, and Neural Architecture Search.
His honors include the Matthew Leydt Society, Outstanding Engineering Scholar, John B. Smith Award, Nikola Tesla Scholar,
and E. M. Toomey Scholarship. He is also a member of the Tau Beta Pi, Eta Kappa Nu, and Sigma Alpha Pi honor societies.
C. P. Le, L. Dai, M. Johnston, Y. Liu, M. Walker, R. Ghanadan
Diversity in Dialogue Systems, IWDSD 2023
Best Paper Award Runner-Up
View PaperA. Aloui, J. Dong, C. P. Le, and V. Tarokh
UAI 2023
View PaperC. P. Le, J. Dong, M. Soltani, and V. Tarokh
ICLR 2022
View PaperC. P. Le, M. Soltani, J. Dong, and V. Tarokh
IEEE Access Journal, Volume 10, 2022
View PaperC. P. Le, M. Soltani, R. Ravier, and V. Tarokh
IEEE ICASSP 2021
View PaperC. P. Le, M. Soltani, R. Ravier, and V. Tarokh
CoRR 2021
View PaperC. P. Le, Y. Zhou, J. Ding, and V. Tarokh
IEEE ICASSP 2020
View Paper