Lin Gao Author

Jianwei Huang is an Associate Professor in the Department of Information Engineering at the Chinese University of Hong Kong. He received a B.E. in Information Engineering from Southeast University (Nanjing, Jiangsu, China) in 2000, an M.S. and Ph.D. in Electrical and Computer Engineering from Northwestern University in 2003 and 2005, respectively. He worked as a Postdoc Research Associate in the Department of Electrical Engineering at Princeton University during 2005-2007.He was a visiting scholar at Ecole Polytechnique Federale De Lausanne (EPFL) in June 2009 and at University of California-Berkeley in August 2010. He is a Guest Professor of Nanjing University of Posts and Telecommunications. Dr. Huang leads the Network Communications and Economics Lab, with the main research focus on nonlinear optimization and game theoretical analysis of communication networks, especially on network economics, cognitive radio networks, and smart grid. He is the recipient of the IEEE WiOpt Best Paper Award in 2013, the IEEE SmartGirdComm Best Paper Award in 2012, the IEEE Marconi Prize Paper Award in Wireless Communications in 2011, the International Conference on Wireless Internet Best Paper Award 2011, the IEEE GLOBECOM Best Paper Award in 2010, the IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award in 2009, and Asia-Pacific Conference on Communications Best Paper Award in 2009. Lin Gao is a Postdoc Research Associate in the Department of Information Engineering at the Chinese University of Hong Kong. He received the B.S. degree in Information Engineering from Nanjing University of Posts and Telecommunications in 2002, and the M.S. and Ph.D. degrees in Electronic Engineering from Shanghai Jiao Tong University in 2006 and 2010, respectively. His research interests are in the area of wireless communications and communication theory,in particular,MIMO and OFDM techniques, cooperative communications, multi-hop relay networks, cognitive radio networks, wireless resource allocation, network economics, and game theoretical models.