信息工程学院关于举办“人工智能技术”专题学术报告的通知

为贯彻国家AI发展战略、顺应科技教育趋势、跟踪学科前沿，提高学院学术影响力，为师生普及AI基础知识、打破技术壁垒，同时扩大师生视野、提高师生学术创新能力，我院将开展“人工智能技术”专题学术报告。

一、活动时间

2025年11月27日（周四）10:00

二、活动地点

北校区 明德园创新大厦101报告厅

三、报告主题

Equalization with Reservoir Computing

四、报告内容

We discuss an example of using neural networks to solve a communication problem. The focus is on developing a systematic approach to come up with the right structure of neural networks, which reflects the domain knowledge of the engineering problem, instead of spending computational resources to “re-learn” such structures. We discuss how to set the architecture of the neural networks, initial parameters, and training methods without the commonly used trial-and-error approach. The goal of this talk is to give an example of a principled design to apply machine learning techniques to specific engineering problems, which we argue is the key to the current research effort in general AI+X problems.

五、参加人员

1.信息工程学院师生代表；

2.在“青春长大”系统中参与报名的学生。

六、注意事项

1.活动后续将在“青春长大”系统发布，欢迎广大同学积极报名参加；

2.请参会人员于9:45前入场，将手机调至静音状态，保持现场秩序和会场安静；

3.在提问交流环节，参会人员请密切关注主持人指引，有序举手发言，确保互动环节高效、有序进行。

七、主讲人简介：

Lizhong Zheng is the Andrew (1956) and Erna Viterbi Professor at the Department of Electrical Engineering and Computer Science at MIT. He works in the general area of information theory, statistical inference, data processing, wireless communications, and networks. Lizhong Zheng received the B.S. and M.S. degrees from the Department of Electronic Engineering at Tsinghua University and the PhD degree from the Department of Electrical Engineering and Computer Science at UC Berkeley. He joined the faculty of Electrical Engineering and Computer Science at MIT in 2002. He is currently a visiting professor at the Hong Kong University of Science and Technology (HKUST). He received the NSF CAREER Award, AFOSR Young Investigator Award, the IEEE Information Theory Society Paper Award. He is an IEEE Fellow. He is currently the Editor-in-Chief for the IEEE Transactions on Information Theory.

供图供稿：研究生科学技术协会 赵轩