Beiyu Lin

Assistant Professor

Education
Ph.D., Computer Science (2020)
Center for Advanced Studies in Adaptive Systems, Washington State University
M.S., Mathematics (2015)
Washington State University
M.S., Applied Math
State University of New York, Stony Brook
B.S., Math and Applied Math
Shanghai Maritime University, China

Research Focus

Machine learning
Deep learning
Behavior modeling
Home/building security
Biomedical applications of AI
Smart Environments

Experience and Awards

Assistant Professor (tenure-track), Computer Science, University of Nevada-Las Vegas.
Affiliate Faculty Member, Nevada Center for Astrophysics, UNLV.
Assistant Professor (tenure-track), Computer Science, University of Texas-Rio Grande Valley.
People Choice Award for Young Professional Poster Competition, IEEE Rising Stars, Jan. 2022
Best Applied Data Science Paper Award, SIAM International Conference on Data Mining (SDM), April 2021

Selected Publications

Yan, J., Huang, X., Wang, S., He, Y., Li, X., Hohl, A., Li, X., Aly, M. and Lin, B., 2023. Toward a comprehensive understanding of eye-level urban greenness: a systematic review. International Journal of Digital Earth, 16(2), pp.4769-4789 (2023)
7/2023 Katherine Wuestney, Beiyu Lin, Diane Cook, Roschelle Fritz. Modeling Human Frailty with a Smart Home-Based Approximation of Entropy, rapid-fire oral presentation, ACM-BCB’23 (2023)
Tan Nguyen, Beiyu Lin. Machine Learning for Parkinson Detection via Speech Analysis, KDD’23 SoCal Data Science Day
Seungman Park, Anna Lien-Lun Chien; Beiyu Lin; Keva Li. Improved diagnosis of rosacea by combining deep learning models, full paper to Journal: Applied Sciences (2023)
Taif Anjum, Louis Chirade, Beiyu Lin, Apurva Narayan. Learning Spatiotemporal Features via 3D CNNs to Forecast Time-To-Accident, short paper, International Conference on Agents and Artificial Intelligence (ICAART)’23 (accepted)
2022 Louis Barbier, Beiyu Lin. Unsupervised Learning for Extreme Space Weather Detection, Posters and Demos ACM/IEEE Symposium on Edge Computing (SEC)’22.
Cicelia Siu, Beiyu Lin. Imitation Learning for cortical speech-evoked responses, Posters and Demos ACM/IEEE SEC’22