Patrick P. C. Lee Professor, Department of Computer Science and Engineering, CUHK Address: Room 108, Ho Sin Hang Engineering Building Department of Computer Science and Engineering The Chinese University of Hong Kong Shatin, Hong Kong Email:

Patrick P. C. Lee received the B.Eng. degree (first-class honors) in Information Engineering from the Chinese University of Hong Kong in 2001, the M.Phil. degree in Computer Science and Engineering from the Chinese University of Hong Kong in 2003, and the Ph.D. degree in Computer Science from Columbia University in 2008. He was a postdoctoral researcher at University of Massachusetts, Amherst in 2008-2009. He is now a Professor of the Department of Computer Science and Engineering at the Chinese University of Hong Kong. He currently heads the Applied Distributed Systems Lab and is working very closely with a group of graduate students on different projects in large-scale software systems. He was a collaborator with Alcatel-Lucent in developing network management solutions for 3G wireless networks in 2007-2011. His research interests are in various applied/systems topics on improving the dependability of large-scale software systems, including storage systems, distributed systems and networks, and cloud computing.

Research interests (Publications)

My general research interests are in various applied/systems topics on improving the dependability of large-scale computer systems, including storage systems, distributed systems and networks, and cloud computing. By dependability, I refer to the fault tolerance, recovery, security, and performance guarantees that need to be achieved in order to maintain the correctness and performance of large-scale software systems. My research approach emphasizes system design and implementation, backed by extensive empirical experiments and possibly theoretical analysis. My current focused areas are:

• Dependable storage systems: We explore practical data management mechanisms that can address the dependability of different types of storage architectures, including clouds, data centers, disk arrays, SSDs, and memory, in the face of failures, stragglers, and attacks.
• Dependable network measurement and stream processing: We explore new data structures and machine learning techniques, so as to achieve accurate network-wide measurement at scale as well as fast and robust data analytics for continuous data streams.