Welcome to my site
Khuong (Anthony) Vo
Donald Bren Hall 3069
University of California, Irvine
Irvine, CA 92697-3435, USA
I am a Ph.D. candidate at the Donald Bren School of Information and Computer Sciences, University of California at Irvine. I am fortunate to be advised by Prof. Srinivasan, Prof. Dutt, and Prof. Cao. I’m currently working on deep latent variable models in biomedical signal processing and neurocognitive modeling. I’m also interested in efficient deep learning in healthcare IoT.
My work is supported by NSF and NIH grants.
I was an AI/ML Research Scientist Intern at Samsung Semiconductor, Inc., working on algorithms for physiological signal monitoring problems.
I received my B.Eng. (Honors) degree in CS from HCMC Vietnam National University. My previous research revolved around statistical natural language processing and has been applied in large-scale commercial systems.
[Resume] [Linkedin] [Google Scholar] [ORCID] [Github] [Twitter]
K. Vo, M. Vishwanath, R. Srinivasan, N. Dutt, and H. Cao. “Composing Graphical Models with Generative Adversarial Networks for EEG Signal Modeling”, in Proc. of IEEE ICASSP, 2022. [link][pdf]
Q. Sun, K. Vo, K. Lui, M. Nunez, J. Vandekerckhove, and R. Srinivasan. “Decision SincNet: Neurocognitive Models of Decision Making that Predict Cognitive Processes from Neural Signals”, in Proc. of IJCNN, 2022. [link][pdf]
K. Vo, E.K. Naeini, A. Naderi, D. Jilani, A.M. Rahmani, N. Dutt, and H. Cao. “P2E-WGAN: ECG Waveform Synthesis from PPG with Conditional Wasserstein Generative Adversarial Networks”, in Proc. of 36th ACM SAC, 2021. [link][pdf]
T.-Y. Lee, K. Vo, W. Baek, M. Khine, and N. Dutt. “STINT: Selective Transmission for Low-Energy Physiological Monitoring”, in Proc. of IEEE/ACM ISLPED, 2020. [link][pdf]
K. Vo, T. Le, A.M. Rahmani, N. Dutt, and H. Cao. “An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram”, Sensors, 2020. [link][pdf]