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.