报告内容:Building High-performance Cluster Frameworks: from Big Data Analytics to Deep Learning Systems
报告人简介: Dr. Kun Wang received two Ph.D. degrees from Nanjing University of Posts and Telecommunications, China in 2009 and from the University of Aizu, Japan in 2018, respectively, both in Computer Science. He was a Postdoc Fellow in UCLA, USA from 2013 to 2015, and a Research Fellow in the Hong Kong Polytechnic University, Hong Kong, from 2017 to 2018. He is currently a Senior Research Professor in UCLA, and also a Professor in Nanjing University of Posts and Telecommunications. His research interests are mainly in the areas of big data, datacenter, blockchain, and distributed systems with over 100 papers published in major conferences and journals, including IEEE TIP, TC, TPDS, ToN, TMC and ACM Mobicom, ACM Mobisys, IEEE ICDCS, IEEE IPDPS, as well as 12 ESI High Cited Papers. He is the recipient of four Best Paper Awards at IEEE GLOBECOM 2016，IEEE TCGCC 2018, IEEE TCBD 2019, and IEEE ISJ (IEEE Systems Journal) 2019. He serves as Associate Editor of IEEE Access, Editor of Journal of Network and Computer Applications, and Guest Editors of IEEE Network, IEEE Access, Future Generation Computer Systems, Peer-to-Peer Networking and Applications, Journal of Internet Technology, and Future Internet.