Research Interests: Operating systems, mobile computing
Office Phone: 86-10-6275 3496
Guo, Yao is a professor in the Department of Computer Science and Technology, School of EECS, and has served as the Vice Chair of Department of Computer Science since 2013. He obtained his B.S. and M.S. degrees from Peking University in 1997 and 2000, respectively, and Ph.D. from University of Massachusetts Amherst in 2007. His research interests include operating systems, mobile computing, program analysis and low-power design.
Dr. Guo has published more than 80 research papers, including top-tier conferences and journals, such as UbiComp, WWW, ASE and ISLPED. He has served in the technical program committee of various international conferences including ISLPED, MobileCloud and NAS. He has won an Honorable Mention Award from UbiComp 2016. He is a member of ACM and IEEE, and a senior member of CCF.
Dr. Guo has led and participated in more than ten research projects including NSFC, 863 projects, National Key Science & Technology Projects, etc. His research achievements are summarized as follows:
1) Security analysis and privacy protection for mobile apps: As the rapid development of mobile devices such as smartphones, one major research topic is to understand and protect the security aspects of mobile apps and protect the privacy of mobile users. He proposed security-related mobile app analysis techniques including permission analysis, UI transition analysis, clone detection, app repackage detection, third-party library detection, etc. Based on these security analysis techniques, he has proposed many security and privacy protection techniques including remote attestation, purpose-based access control, UI-based access control, split execution of sensitive components, etc.
2) Performance optimization of OS/Browser: Performance optimization is an eternal topic for computer systems, especially for operating systems. He has studied the compiler parameters that may affect the performance of Linux kernel, as well as the mobile Android operating system, and proposed profile-based techniques to optimize OS kernel performance automatically. He also proposed techniques to optimize the performance of more and more frequently used web browsers.
3) Power and energy optimization of mobile systems: The standby time is one of the main obstacles of smartphones since their introduction. He has proposed a series of techniques to model and analyze mobile app energy consumption on smartphones, including an online energy estimation model, a profile-driven power estimation method, standby energy analysis, as well as a couple of power estimation tools. He also proposed energy optimization techniques such as transaction-based DVS and instrumentation-based adaptive sensor energy optimization.