Lecturer:Chen Wei

Abstract:

While machine learning has made remarkable progress in artificial intelligence, it has encountered many technical challenges, such as "miracles and wonders", "AI alchemy" and "black box magic". Tackling these challenges will lead to new opportunities for machine learning. In addition, machine learning offers the potential to accelerate scientific computation by data and even discover new science, and can provide data-driven solutions for industries such as finance, logistics, and healthcare. This report will present these challenges and opportunities for machine learning, as well as the corresponding research results and future research outlook from Microsoft Research Asia.

Introduction to the Lecturer:

Wei Chen, head of the Computational Learning Theory Group at Microsoft Research Asia and part-time PhD supervisor at the University of Science and Technology of China, graduated from the Department of Statistics, School of Mathematical Sciences, Shandong University in 2006 and received PhD from the Academy of Mathematics and Systems Science Chinese Academy of Sciences in 2011. She is focused on researches about deep learning theory and algorithms, machine learning with privacy preservation, and causal learning, and has received the Breakthrough Prize in Technology from Microsoft Research Asia. She has more than 40 high-level academic papers published in top international conferences/journals on artificial intelligence and machine learning (e.g. NeurIPS, ICML, ICLR, IJCAI, AAAI, and IEEE/ACM Trans), and one academic book on distributed machine learning published. He (was/will be) invited to give lectures and presentations at AAAI17, WWW17 and ICML21, and ever served as domain chairman or senior program committee member at several machine learning conferences.

Invitee:

Wang Guanghui, Professor from School of Mathematics

Time:

10:00, June 15 (Tuesday)

Venue:

Tencent Meeting ID: 435 423 101

Hosted by the School of Mathematics, Shandong University