Position Title
Professor, Electrical and Computer Engineering
Child Family Professor in Engineering, Electrical & Computer Engineering, UC Davis
Co-Director, Center for Data Science and Artificial Intelligence Research (CeDAR)
Chuah seeks to understand large-scale networked systems and learning-driven information processing, computation, and control. Her Robust & Ubiquitous Networking (RUbiNet) Lab focuses on developing data driven approach to design adaptive control and security detection mechanisms in different production networks, including IP-backbones, wireless networks, data centers, online social platforms, and software defined networks. Chuah is also interested in applying advanced data science and machine learning techniques to different application domains, including smart health and intelligent transportation. Real-time analytic platforms and AI-assistant clinical decision support systems has the potential to transform healthcare delivery from critical care to chronic disease management. (Current as of June 2025)
- Ph.D. in Electrical Engineering & Computer Sciences, University of California, Berkeley
- M.S. in Electrical Engineering & Computer Sciences, University of California, Berkeley
- B.S. in Electrical Engineering, Rutgers University
- AAAS Fellow
- UC Davis College of Engineering Outstanding Senior Faculty Award
- UC Davis IEEE Student Association’s Professor of the Year Award
- UC Davis ADVANCE Scholar Award
- IEEE Fellow
- Networks and distributed systems, data science, intelligent learning, smart health, intelligent transportation systems
- L. Cerny-Oliveira, J. Chauhan, A. Chaudhari, S. Cheung, V. Patel, A. C. Villablanca, L-W. Jin, C. DeCarli, C-N. Chuah, B. N. Dugger, “A Machine Learning Approach to Automate Microinfarct Screening in Hematoxylin and Eosin-stained Human Brain Tissues,” Journal of Neuropathology and Experimental Neurology (JNEN).
- A. Haydari, V. Agarwal, M. Zhang, and C-N. Chuah, “Constrained Reinforcement Learning for Fair and Environmentally Efficient Traffic Signal Controllers,” ACM Journal on Autonomous Transportation Systems, 2024.
- R. Scalco, L. Cerny-Oliveira, Z. Lai, D. Harvey L. Abujamil, C. DeCarli, L-W. Jin, C-N. Chuah, and B. N. Dugger, “Machine learning quantification of Amyloid-b in temporal lobe of 131 Brain Bank Cases,” Acta Neuropathologica Communications
- Z. Lai, J. Chauhan, D. Chen, B. Dugger, S-C. Cheung, and C-N. Chuah, “Semi-Path: An Interactive Semisupervised Learning Framework for Gigapixel Pathology Image Analysis,” Elsevier Smart Health Journal, (also presented in IEEE/ACM CHASE), June 2024.
- H. Siefkes, L. Cerny Oliveira, R. Koppel, W. Hogan, M. Garg, E. Manalo, N. Cresalia, Z. Lai, D. Trancredi, S. Lakshminrusimha, and C-N. Chuah, “Machine Learning Based Critical Congenital Heart Disease Screening using Dual-Site Pulse Oximetry Measurements” Journal of American Heart Association (JAHA), vol. 13, no. 12, June 2024. DOI: https://doi.org/10.1161/JAHA.123.033786