I am currently a final-year Ph.D. Candidate in Computer Science and Engineering at the University of Connecticut (UCONN) in
Laboratory of Machine Learning & Health Informatics, working on
Machine Learning (ML) / Artificial Intelligence (AI) in the Internet of Things (IoT) / Cyber-Physical Systems (CPS)
supervised by Prof. Jinbo Bi. Previously, I was working on Underwater Acoustic Sensor Networks
(UWASN) in Tianjin University supervised by Prof. Zhigang Jin.
My research focuses on developing new methodologies in AI/ML to enhance the Efficiency,
Security, and Scalability of the IoT/CPS. My research interests include: Reinforcement Learning, Federated Learning, On-Device Learning, Computer Vision,
Contrastive Learning, Representation Learning; Location-based Services (LBS), Edge Computing, Data Privacy, Remote Sensing Imagery,
Smart City, Mobile Computing, Wireless Networks.
My research lies in analyzing and resolving challenges associated with Machine Intelligence of Ubiquitous
Computing in Distributed Systems, including:
- inefficiency and low scalability of trained models, especially when the
solution space is large;
- security and privacy concerns of user data;
- data heterogeneity across devices and imbalanced
data distribution on individual devices;
- communication bottlenecks and high computational costs in distributed systems.
The goal is to foster interdisciplinary research and offer opportunities for introducing transformative technologies to enable
new real-life products and services.