Duration: 2020.7.9-2020.7.31 (3 weeks)
This course, Artificial Intelligence Principles and Applications, aims for providing both overview and practice techniques for artificial intelligence, specifically its theory and applications on computer vision, natural language processing, data mining, as well as robotics. In this course, theory and methods for machine learning, optimization will be given. Furthermore, lab and homework sessions will be provided on each topic. The purpose of this course is to help students develop a range of theoretical and practical skills in artificial intelligence. The summer course will provide a good opportunity to communicate with prominent researchers and learn the recent development of artificial intelligence.
The students will have the chance to learn about theory and methods for a range of fields of artificial intelligence, including computer vision, natural language processing, data mining, as well as robotics.
The students will explore the SJTU Artificial Intelligence Institute and the Key Laboratory of Artificial Intelligence Ministry of Education, both are top Chinese labs in the field of artificial intelligence, by visiting, colloquia, and potential joint projects.
By the end of summer school, students will have basic knowledge and understanding of artificial intelligence, obtain a range of theoretical and practical skills and establish contacts through social interactions that may lead to research collaborations in the future.
Students will visit world-famous artificial intelligence-related companies, including Huawei, Tencent, Ant Financial, etc, and have a clearer understanding of the development of this field.
Prof. Xiaokang YANG (IEEE Fellow)
Xiaokang Yang received Ph.D. degree from Shanghai Jiao Tong University in 2000. He is currently a Distinguished Professor of School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China. His research interests include visual signal processing and communication, media analysis and retrieval, and pattern recognition. He serves as an Associate Editor of IEEE Transactions on Multimedia and an Associate Editor of IEEE Signal Processing Letters. Prof. Yang is also a fellow of IEEE.
Prof. Hai ZHAO
Hai Zhao is a professor in the Department of Computer Science and Engineering, Shanghai Jiao Tong University. His research interests are natural language processing, machine learning, artificial intelligence. He is an ACM professional Member, a technical committee member of Chinese Information Technology in China Computer Federation, a vice director of AI technical committee in Shanghai Computer Federation. He has published more than 120 papers, including nearly 60 CCF-A/B papers. His Google scholar cited is nearly 2,200. He served as ACL 2017 Program Committee Area Chair of Tagging, Chunking, Syntax and Parsing and ACL 2018 & 2020 Program Committee Area Chair of Phonology, Morphology and Word Segmentation Area.
Prof. Hongyuan ZHA
Hongyuan Zha is a Professor at the School of Computational Science and Engineering, College of Computing, Georgia Institute of Technology and Shanghai Jiao Tong University. He earned his PhD degree in scientific computing from Stanford University in 1993. Since then he has been working on information retrieval, machine learning applications and numerical methods. He is the recipient of the Leslie Fox Prize (1991) of the Institute of Mathematics and its Applications, the Outstanding Paper Awards of the 24th International Conference on Advances in Neural Information Processing Systems (2013) and the Best Student Paper Award of the 34th ACM SIGIR International Conference on Information Retrieval (SIGIR 209). He was an Associate Editor of IEEE Transactions on Knowledge and Data Engineering.
Prof. Xiaofeng GAO
Xiaofeng Gao received the B.S. degree from Nankai University, China, in 2004, the M.S. degree from Tsinghua University, China, in 2006, and the Ph.D. degree from The University of Texas at Dallas, USA, in 2010. She is currently a Professor with the Department of Computer Science and Engineering, Shanghai Jiao Tong University, China. Her research interests include data mining and network optimization. She has won the best paper awards seven times, including DASFAA2017, ICPADS2016, etc.
Prof. Cewu LU
Cewu Lu is an associate professor at Shanghai Jiao Tong University. Before he joined SJTU, he was a research fellow at Stanford Artificial Intelligence Laboratory working under Prof. Fei-Fei Li and Prof. Leonidas J. Guibas. In 2016, he was selected as the National "1000 Youth Talents Plan". In 2018, he was selected as 35 Innovators Under 35 (MIT TR35) by MIT Technology Review. In 2020, he was awarded Qiu Shi Outstanding Young Scholar. He has published more than 60 papers at top conferences and Journals, including CVPR/ICCV/PAMI,etc. His research interests fall mainly in Computer Vision, deep learning, and has made many innovative contributions in these fields. He serves as the program chair of CVM2018, and Area Chair of CVPR 2020.
Prof. Li JIANG
Li Jiang is an associate professor in the Department of Computer Science and Engineering, Shanghai Jiao Tong University. He received the Ph.D. degree from the Dept. of CS&E, the Chinese University of Hong Kong in 2010 and 2013 respectively. He received the best paper nomination in ICCAD, and got best Ph.D. Dissertation award in ATS 2014, and was in the final list of TTTC°Øs E. J. McCluskey Doctoral Thesis Award. He serves as co-chair and TPC member in several international and national conferences, such as DATE, ASP-DAC, ITC-Asia, ATS , CFTC, CTC and etc. His current research interests include Computer Architecture and algorithm design technology to accelerate AI-based application, approximate computing for energy efficiency, Hardware system design automation, reliability and performance enhancement using machine learning techniques.
Prof. Junchi YAN
Junchi Yan is currently an Associate Professor at the Department of Computer Science and Engineering and AI Institute of Shanghai Jiao Tong University. He is also the co-director for the prestigious SJTU ACM Class. His research interests are machine learning, data mining and computer vision. He serves as an Associate Editor for IEEE ACCESS, (Managing) Guest Editor for IEEE Transactions on Neural Network and Learning Systems, Pattern Recognition Letters, Pattern Recognition, Vice Secretary of China CSIG-BVD Technical Committee, and on the executive board of ACM China Multimedia Chapter. He has published 40+ peer reviewed papers in top venues in AI and has filed 20+ US patents. He has once been with IBM Watson Research Center, Japan NII, and Tencent/JD AI lab as a visiting researcher. He won the Distinguished Young Scientist of Scientific Chinese for the year 2018 and CCF Outstanding Doctoral Thesis.
Prof. Yanmin QIAN
Yanmin Qian is Associate Professor in Shanghai Jiao Tong University, China. He received his PhD in the Department of Electronic Engineering from Tsinghua University, China in 2012. From 2013, he joined the Department of Computer Science and Engineering in Shanghai Jiao Tong University. He was one of the key members to design and implement the Cambridge Multi-Genre Broadcast Speech Processing system, which won all four tasks of the first MGB Challenge in 2015. He is a senior member of IEEE and a member of ISCA, and one of the founding members of Kaldi Speech Recognition Toolkit. He has published more than 100 papers on speech and language processing with 4000+ citations, including T-ASLP, Speech Communication, ICASSP, INTERSPEECH and ASRU. His current research interests include the acoustic and language modeling in speech recognition, natural language understanding, deep learning and multi-media signal processing.
Assoc Prof. Manhua LIU
Manhua Liu is currently an Associate Professor of School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China. She received her Ph.D. degree in 2007 from Nanyang Technological University, Singapore. She joined Shanghai Jiao Tong University in 2008. Her research interests include multimodality image processing and fusion, brain image intelligent computing and analysis, fingerprint recognition, machine learning and pattern recognition. She has published more 20 SCI journal papers. Prof. Liu is a member of IEEE.
Assistant Prof. Yue GAO
Dr. Yue Gao received her Ph.D. degree for Computer Science from Cornell University in 2016. After that she joined Shanghai Jiao Tong University as an Assistant Professor. Her research lied at the intersection of machine learning and robotics.
Lab report and Assignment: 40%
Final Project Presentation: 30%
Program Director: Prof. Xiaokang YANG（email@example.com）
Program Coordinator: Assistant Prof. Yue GAO(firstname.lastname@example.org)