李小平，广东工业大学计算机学院院长，国家高层次人才，校百人计划特聘教授、二级教授、博士生导师，IEEE高级会员、CCF（中国计算机学会）杰出会员、ACM会员，CCF 协同计算专委副主任、中国仿真学会智能仿真优化与调度专委会常务委员。 主持的科研项目包括：国家重点研发计划项目2项、国家重点研发计划课题2项、国家自然科学基金7项、国家自然科学基金重点项目1项、国家863计划1项、国家科技支撑计划1项、江苏省重点研发计划1项等。 2009年入选教育部新世纪优秀人才支持计划、2019年和2012年入选江苏省“六大人才高峰” 培养对象、2008年入选江苏省高校“青蓝工程”优秀青年骨干教师培养对象。 在IEEE Transactions on Computers、IEEE Transactions on Parallel and Distributed Systems、IEEE Transactions on Services Computing、Science in China Series F: Information Sciences、IEEE Transactions on Automation Science and Engineering、IEEE Transactions on Cybernetics、IEEE Transactions on Systems, Man and Cybernetics: Systems、 IEEE Transactions on Evolutionary Computation、IEEE Transactions on Cloud Computing、IEEE Transactions on Network and Service Management、OMEGA、Information Sciences、European Journal of Operational Research、Future Generation Computer Systems、Journal of Grid Computing、 Journal of Supercomputing 、Journal of Network and  Computer Applications、Expert Systems with Applications、Integrated Computer-Aided Engineering、Cluster Computing、Computers & Industrial Engineering、International Journal of Production Research、International Journal of  Computer Integrated Manufacturing、Engineering Optimization、International Journal of Advanced Manufacturing Technology、Chinese Journal of Electronics、中国科学、计算机学报、软件学报、电子学报、通信学报、ICSOC、ICPADS、ICWS、SMC、CASE、CSCWD等高水平国际国内期刊或国际会议上发表论文100余篇。获江苏省科学技术二等奖1项。

主要研究方向：云计算，调度优化、服务计算、云制造、复杂生产调度优化、智能算法。 

           2009.3-2010.3，National Research Council, Canada，访问学者；
           2003.1-2004.12，清华大学，自动化系，博士后；
           1999.3-2002.8，哈尔滨工业大学，计算机应用技术专业，获博士学位；
          1996.9-1999.3，哈尔滨理工大学，计算机应用技术专业，获硕士学位；
          1989.9-1993.7，哈尔滨科技大学，计算机及其应用专业，获学士学位。

          2023.1-，广东工业大学，计算机应用技术，二级教授，校百人特聘教授，博士生导师；

          2009.4- 2024.4，东南大学，计算机应用技术，二级教授，特聘教授，博士生导师；
          2007.4-2009.4，东南大学，计算机应用技术，副教授，博士生导师；
          2005.2-2007.4，东南大学，计算机应用技术，副教授，硕士生导师；
          2003.9-2005.2，哈尔滨理工大学，计算机应用技术，副教授，硕士生导师；
          1998.9-2003.8，哈尔滨理工大学，计算机应用技术，讲师；
          1993.8-1998.8，哈尔滨理工大学，计算机应用技术，助教。

       云计算，调度优化 , 服务计算, 智能制造， 工业软件

Dr. Xiaoping Li  is a distinguished professor in Guangdong University of Technology. He is an IEEE Senior member and a  Distinguished member of China Computer Federation (CCF). He received his B.Sc. and M.Sc. degrees in Applied Computer Science from the Harbin University of Science and Technology in 1993 and 1999, respectively, and the Ph.D. degree in Applied Computer Science from the Harbin Institute of Technology in 2002.  From Jan. 2003 to Dec. 2004, he did postdoctoral research at the Department of Automation at Tsinghua University, Beijing, China. From Mar. 2009 to Mar. 2010, he was a visiting professor at the National Research Council, London, Ontario, Canada. He is a full professor at the School of Computer Science and Engineering, Southeast University, Nanjing, China. He is the author or co-author over more than 100 academic papers, some of which have been published in international journals such as IEEE Transactions on Computers、IEEE Transactions on Parallel and Distributed Systems、IEEE Transactions on Services Computing、Science in China Series F: Information Sciences、IEEE Transactions on Automation Science and Engineering、IEEE Transactions on Cybernetics、IEEE Transactions on Systems, Man and Cybernetics: Systems、 IEEE Transactions on Evolutionary Computation、IEEE Transactions on Cloud Computing、IEEE Transactions on Network and Service Management、OMEGA、Information Sciences、European Journal of Operational Research、Future Generation Computer Systems、Journal of Grid Computing、 Journal of Supercomputing 、Journal of Network and  Computer Applications、Expert Systems with Applications、Integrated Computer-Aided Engineering、Cluster Computing、Computers & Industrial Engineering、International Journal of Production Research、International Journal of  Computer Integrated Manufacturing、Engineering Optimization、International Journal of Advanced Manufacturing Technology、Chinese Journal of Electronics、, ICSOC, ICPADS, ICWS, SMC, CASE, CSCWD. His research interests include Scheduling in Cloud Computing, Scheduling in Cloud Manufacturing, Service Computing, Big Data and Machine Learning.