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5月21日: Knowledge Transfer in Deep Learning for Limited Supervision Problems (受限监督问题深度学习中的知识迁移)
2019-05-13 11:17     (浏览次数:)

5月21日: Knowledge Transfer in Deep Learning for Limited Supervision Problems (受限监督问题深度学习中的知识迁移)

报告时间: 5月21日 上午10:30-12:00

报告地点: 众创空间一楼路演大厅


中文:唐波博士是密西西比州立大学(Mississippi State University)电子与计算机工程系(Department of Electrical and Computer Engineering)的助理教授(tenure-track assistant professor),Statistical Analysis and Intelligent Systems(SAIL)实验室主任。

唐波2016年于罗德岛大学获博士学位,2010年于中国科学院电子学研究所获硕士学位,2007年于中南大学获学士学位。目前主要从事于智能计算和机器学习以及其在无人驾驶汽车,大数据,智能电网,遥感数据挖掘等方向的研究。已在权威学术期刊和国际会议上发表论文40多篇,并担任多个期刊的特约编辑(Guest Editor)和国际会议的Session Chair。唐波获得2018年National Institute of Justice (NIJ) New Investigator/Early Career Award, 2016年中国国家留学基金委评选的“国家优秀自费留学生奖”,2016年IEEE计算与通信大会最佳论文奖(IEEE CCWC 2018 Best Paper Award),2016年IEEE 神经网络会议最佳学生论文奖(IJCNN Best Student Paper Award), 2015年IEEE Computational Intelligence Magazine Publication Spotlight Paper等

英文:Dr. Bo Tang (唐波) is currently an Assistant Professor in the Department of Electrical and Computer Engineering at Mississippi State University. He received his B.S. and M.S. degrees from Central South University in 2007, and Institute of Electronics, Chinese Academy of Sciences in 2010, respectively. From 2010 to 2012, he worked at Beijing National Railway Research Design Institute of Signals and Communications. He received the Ph.D. degree in electrical and computer engineering from University of Rhode Island (Kingstown, RI) in 2016. From 2016 to 2017, he worked as an Assistant Professor in the Department of Computer Science at Hofstra University, Hempstead, NY.

His research interests lie in the general areas of Statistical Machine Learning, Data Mining, Cyber Security, and their applications in Smart Grid, Autonomous Vehicles and Remote Sensing. In particular, he is interested in developing new statistical machine learning algorithms (e.g., Bayesian learning, transfer learning and deep learning) and building complex embedded systems (e.g., energy systems, robotics and autonomous vehicles) that are robust, adaptive and fault tolerant to uncertain environments.

Dr. Tang is also the recipient of NIJ New Investigator/Early Career Award (2018), Chinese Government Award for Outstanding Students Abroad (2016), Best Paper Award in IEEE CCWC (2018), Best Student Paper Award in IJCNN (2016), Junior Faculty Travel Award by Army Research Office (2016), Travel Award by IEEE CNAS (2015), and IEEE Computational Intelligence Magazine Publication Spotlight Paper (2015).

主办单位:众创空间 发布单位:科研处

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