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名师讲堂:Engineering Reliable and Efficient AI with Applications to Communications
文:人力资源部教师发展中心 来源:信通学院 党委教师工作部、人力资源部(教师发展中心) 时间:2022-04-28 31066

  人力资源部教师发展中心“名师讲堂”活动特别邀请到伦敦国王学院Osvaldo Simeone教授做线上学术交流。具体安排如下,欢迎广大师生参加。

  一、主 题:Engineering Reliable and Efficient AI with Applications to Communications

  二、主讲人:伦敦国王学院 Osvaldo Simeone 教授

  三、时 间:2022年5月5日(周四)17:00-18:00

  四、参会方式:ZOOM Meeting  会议ID:966 86608666

  五、主讲内容:

  Artificial intelligence (AI) and machine learning tools are assuming increasingly central roles in engineering, with the design of next-generation wireless systems being an important case in point. In this talk, I will focus on three key desirable properties for AI modules in engineering: calibration, sample efficiency, and hardware efficiency. Calibration describes the capacity of an AI module to provide reliable measures of confidence of its decisions; sample efficiency quantifies data set size requirements; and hardware efficiency refers to the complexity of implementation in hardware. I will argue for the adoption of Bayesian meta-learning as a general framework for the design of well-calibrated and sample-efficient AI, and I will review related results and open directions for research. I will also introduce neuromorphic computing as an emerging hardware-efficient computing technology, and I will conclude with a discussion of the potential use of quantum AI for probabilistic machine learning. 

  六、嘉宾简介:

  Osvaldo Simeone, Fellow of the IET and of the IEEE.He is a Professor of Information Engineering with the Centre for Telecommunications Research at the Department of Engineering of King's College London, where he directs the King's Communications, Learning and Information Processing lab. He received an M.Sc. degree (with honors) and a Ph.D. degree in information engineering from Politecnico di Milano, Milan, Italy, in 2001 and 2005, respectively. From 2006 to 2017, he was a faculty member of the Electrical and Computer Engineering (ECE) Department at New Jersey Institute of Technology (NJIT), where he was affiliated with the Center for Wireless Information Processing (CWiP). His research interests include information theory, machine learning, wireless communications, and neuromorphic computing. Dr Simeone is a co-recipient of the IEEE Vehicular Technology Society 2021 Jack Neubauer Memorial Award, 2019 IEEE Communication Society Best Tutorial Paper Award, the 2018 IEEE Signal Processing Best Paper Award, the 2017 JCN Best Paper Award, the 2015 IEEE Communication Society Best Tutorial Paper Award and of the Best Paper Awards of IEEE SPAWC 2007 and IEEE WRECOM 2007. He was awarded a Consolidator grant by the European Research Council (ERC) in 2016. His research has been supported by the U.S. NSF, the ERC, the Vienna Science and Technology Fund, as well as by a number of industrial collaborations. He currently serves in the editorial board of the IEEE Signal Processing Magazine and is the chair of the Signal Processing for Communications and Networking Technical Committee of the IEEE Signal Processing Society. He was a Distinguished Lecturer of the IEEE Information Theory Society in 2017 and 2018, and he is currently a Distinguished Lecturer of the IEEE Communications Society. Dr Simeone is a co-author of a textbook (to be published by Cambridge University Press), two monographs, two edited books, and more than 160 research journal papers.

  七、主办单位:人力资源部教师发展中心

    承办单位:信息与通信工程学院


                    人力资源部教师发展中心

                                                               2022年4月28日


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