On December 31, 2021, [Mingli Lecture 2021 Issue 78] was honored to invite Professor Song Jie, associate dean of the School of Engineering of Peking University, to give a report entitled "Allocation of Perishable Resources Based on Online Contextual Learning". The report was held in Conference Room 418 of the main building. More than 20 teachers and students, including Secretary Yan Zhijun, Deputy Dean Zhao Xian, Professor Li Guo, and Associate Researcher Zhu Bin of the School of Management and Economics, attended the lecture. The moderator is Associate Professor Zhang Yuli, Department of Management Engineering, School of Management and Economics.

Prof. Song Jie proposes a new class of online learning matching problem from the healthcare platform, that is, randomly arriving customers must be matched with perishable resources in order to maximize the total expected return. This match explains the differences between different customer resource pairings. Professor Song Jie also designed an online algorithm for situational learning and resource allocation based on perishable resources. Professor Song Jie's work in this report belongs to the online resource allocation flow in the service system, which can be further extended to other service applications. The report received enthusiastic response and was well received by teachers and students.

Attachment: Profile of Professor Song Jie

Song Jie, Deputy Dean of the School of Engineering, Peking University, Doctoral Supervisor of the Department of Industrial Engineering and Management, Distinguished Professor of the "Changjiang Scholars Award Program" of the Ministry of Education. In 2004, he graduated from the School of Mathematical Sciences, Peking University, majoring in applied mathematics. In 2010, he obtained a doctorate in management science and engineering from the Department of Industrial Engineering, Tsinghua University. He has conducted postdoctoral and visiting scholar research at Georgia Tech, University of Wisconsin-Madison, and Columbia University. The research direction is stochastic optimization modeling and algorithm design, and its application in resource optimization allocation and operation management of complex service systems such as medical services, energy management and national strategic reserves. He is the editorial board member of three international SCI journals including IEEE Automation Science and Engineering, and the chairman of the management committee of the IEEE RAS International Medical Automation Society. Won the 2013 IEEE Robotics and Automation Society Best Paper Award. 2020 IEEE TASE Journal Annual Best Paper Award. 2021 IISE Transactions Best Paper Honorable Mention Peking University 2016, 2017 Excellent Teaching.