Research Interests Research Projects
My research focuses on network science, which is "the study of network representations of physical, biological, and social phenomena leading to predictive models of these phenomena." Analyzing big data from a networked environment, my current work applies theories and techniques of network science, including graph theory, machine learning, statistical inference, and data mining, to solve real-world problems. My research contributions can be grouped into the following themes:
- Monitoring and information processing in complex networks: sensor networks, smart grid, online social networks
- Theoretical foundation of computer networks: stochastic modeling, network tomography, network calculus, dependence modeling
- Computational sustainability: green computing and computing for green to be more specific
- Quality of service (QoS) for cloud computing and content delivery networks (CDN)
- Security and anomaly detection: computer networks, IoT systems
Recently, I became interested in applying machine learning methods to the scheduling and control of complex systems, covering autonomous driving, IoT anomaly detection, and cloud resource scheduling.
Industrial collaboration: I have worked as either an industrial consultant or a research collaborator for the following companies:
- Streetlight Intelligence Inc. (STI), Canada: designing a wireless sensor network for intelligent streetlight monitoring and control
- Nokia, Canada: developing new technologies for fast, privacy-preserving information exchange over mobile social networks
- InteLuma Inc., Canada: parking lot light control and cloud-based energy data management
- Schneider Electric, Canada, and Kinsol Research, Canada: power quality monitoring of enterprise-level power networks
- Terapeak, an eBay company: improving its recommendation system for online merchants
- CompuClever Systems, Canada: intelligent recommendation and automatic maintenance of loyalty rewards programs
- Ericsson, Canada: improving Quality of Service for the mobile telco cloud and for the content delivery networks (CDN)
- Huawei, Canada: machine learning-based intrusion detection for IoT secure gateways
Media exposure: Our work on "battling the Internet water army" has been broadly reported by MIT technology review, ACM TechNews, Time Colonist, Discovery News, the Atlantic, and more.
I was a software engineer with over 5 year's experience of commercial software development. Whenever possible, I still write code in python, c, and java.