Profile picture of Lei Jiao

Lei Jiao

Assistant Professor
Computer Science
Phone: 541-346-3998
Office: 334 Deschutes Hall
Office Hours: W 12-1:30pm
Research Interests: Edge/Cloud Computing, Distributed AI/ML, Security and Privacy, Energy and Transportation, Social Networks and Multimedia

Biography

Lei Jiao is an assistant professor in the Department of Computer Science at the University of Oregon. His research has been primarily funded by the National Science Foundation, including via a CAREER award, and the industry. His publications often appear in premier journals such as JSAC, ToN, TPDS, and TMC and conferences such as INFOCOM, MOBIHOC, ICDCS, SECON, ICNP, and IPDPS. He received the Ripple Faculty Fellowship, the Alcatel-Lucent Bell Labs UK and Ireland Recognition Award, and several Best Paper Awards including IEEE LANMAN 2013 and IEEE CNS 2019. He has been on the technical program committees of many conferences such as INFOCOM (as a Distinguished Member), MOBIHOC, ICDCS, WWW, and IWQoS, and has been a regular reviewer for many journals. He has also served as the program chair of multiple symposiums/workshops with INFOCOM and ICDCS and as a guest editor of JSAC. He used to work at Nokia Bell Labs in Dublin, Ireland as a member of technical staff and at IBM Research in Beijing, China as a researcher. He received the Ph.D. (Dr. rer. nat.) degree in computer science (Informatik) from the University of Göttingen (Georg-August-Universität Göttingen) in Germany, where his research was part of EU FP7 projects.

Education

Dr. rer. nat., Georg-August-Universität Göttingen, Germany, 2014

Research Interests

Lei Jiao researches next-generation distributed computer and telecommunication systems, networks, and services. Centering around edge computing and cloud computing, his work spans multiple topics: (i) edge and cloud infrastructures; (ii) machine learning systems; (iii) security and privacy; (iv) energy and transportation; and (v) social networks and multimedia. His work uses theories and principles of optimization, control, learning and economics to lead the design, enhance the performance and characterize the limits of engineering systems, and involves system modeling, algorithm design, theoretical derivations, and experimental evaluations for system efficiency, scalability, resilience, and sustainability.