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Tutorial 1: Visual & Language Learning and Computing for Behavioral & Social Analysis

In the rapidly evolving landscape of artificial intelligence, visual and language learning has become a cornerstone for advancing computational methods in behavioral and social analysis. Technologies such as Artificial Intelligence Generated Content (AIGC), ChatGPT, and Metaverse become increasingly sophisticated. This tutorial will provide an in-depth exploration of the recent advances in visual and language learning and their applications or influences in behavioral and social analysis. The session is divided into four key segments, each presented by an expert speaker. Participants are expected to gain a comprehensive understanding of how visual and language learning are driving innovations especially in behavioral and social analysis.

Topic #1: Visual content generation and editing: progress and challenges (tentative)

Prof. Wangmeng Zuo
Harbin Institute of Technology, China

Bio
Wangmeng Zuo (Senior Member, IEEE) received the Ph.D. degree in computer application technology from the Harbin Institute of Technology, Harbin, China, in 2007. He is currently a Professor with the School of Computer Science and Technology, Harbin Institute of Technology. He has published over 100 papers in top-tier academic journals and conferences. According to the statistics by Google scholar, his publications have been cited more than 60,000 times in literature. His current research interests include image enhancement and restoration, image and face editing, object detection, visual tracking, and image classification. Prof. Zuo has served as an Associate Editor for the IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.
Webpage: http://homepage.hit.edu.cn/wangmengzuo


Topic #2: ChatGPT: Past, Present and Future (tentative)

Prof. Xiaocheng Feng
Harbin Institute of Technology, China

Bio
Xiaocheng Feng received the PhD degree in computer science from the Harbin Institute of Technology, in 2017. He is currently a Professor at Harbin Institute of Technology. He has published over 50 papers in top-tired international conferences and journals such as ACL, AAAI, IJCAI, TKDE, and Chinese Science. His papers have been cited more than 5,600 times, and one of his papers was selected as one of the Top10 Highly Cited Papers in Paper Digest EMNLP 2020. He has served as a (senior) member of the program committee of international conferences such as NIPS, ICML, AAAI, IJCAI, and ACL. His current research interests include natural language processing, text generation, and machine translation.
Webpage: https://homepage.hit.edu.cn/fengxiaocheng


Topic #3: Continual learning with pretrained fundamental models (tentative)

Prof. Xiaopeng Hong
Harbin Institute of Technology, China

Bio
Xiaopeng Hong (Senior Member, IEEE) received his Ph.D. degree in computer application technology from Harbin Institute of Technology, P. R. China, in 2010. He is a professor at Harbin Institute of Technology (HIT), P. R. China. He had been a distinguished research fellow at Xi'an Jiaotong University, P. R. China, and an adjunct professor at the University of Oulu, Finland. Xiaopeng had been a PI of over 10 projects such as the National Key R&D Program Projects, PRC, and Infotech Oulu Postdoctoral funding project. He has authored over 80 articles in journals and conferences such as IEEE T-PAMI, CVPR, ICCV, and AAAI. His studies about subtle facial movement analysis was reported by International media like MIT Technology Review. He was the co-author of a ‘top paper award’ paper in ACM Multimedia 2023 and also the 2020 ‘IEEE Finland Section best student conference paper’. His current research interests include incremental learning, visual surveillance, and micro-expression analysis.
Webpage: https://homepage.hit.edu.cn/hongxiaopeng


Topic #4: 3D Point Cloud Data Quality Enhancement for Metaverse (tentative)

Dr. Xingtao Wang
Harbin Institute of Technology, China

Bio
Xingtao Wang obtained his B.S. degree in Mathematics and Applied Mathematics, as well as his Ph.D. degree in Computer Science, from the Harbin Institute of Technology (HIT) in Harbin, China, in 2016 and 2022, respectively. In 2023, he served as an Assistant Research Fellow at the School of Artificial Intelligence, HIT, and currently holds the position of Associate Researcher. His research focuses on computer graphics, digital twins, and panoramic vision.
Webpage: https://homepage.hit.edu.cn/xtwang

Tutorial 2: Cohesive Subgraph Search in Social Networks

With the advent of a wide spectrum of social application, social networks are attracting increasing interests from researchers. Cohesive subgraph search is an essential task in social network analysis, useful for various applications such as community detection, fraud detection, and recommendation systems. In this tutorial, we first highlight the importance of cohesive subgraph search in various applications and the unique challenges that need to be addressed. Then, we introduce recent cohesive graph models including k-core, k-truss, k-cliques, and review the state-of-the-art research work for these models in both static and dynamic graphs. Finally, we discuss the future directions.

Speaker #1

Prof. Yuanyuan Zhu
Wuhan University, China

Bio
Yuanyuan Zhu is currently a full professor in the School of Computer Science at Wuhan University in China. She received the PhD degree in computer science from the Chinese University of Hong Kong in 2013. Her research interests include social network analysis, graph database management, etc. She has published over 40 of papers in top-tier conferences and journals, including VLDBJ, TKDE, PVLDB, ICDE, CIKM, etc. She serves as program committee members for a number of top-tier conferences including VLDB、ICDE、KDD、AAAI、IJCAI、SIGIR and invited reviewers for journals including TKDE and WWW Journal. He received the ACM SIGMOD China Rising Star Award in 2020 and Global Top Chinese Young Scholars in Artificial Intelligence (Baidu) 2023.


Speaker #2

Prof. Xinrui Wang
Shandong University, China

Bio
Xinrui Wang is an assistant professor in the School of Computer Science and Technology at Shandong University. She got her PhD degree in Computer Software and Theory from Harbin Institute of Technology, under the supervision of Prof. Hong Gao. Before that, she received her bachelor’s degree from Harbin Institute of Technology. Her current research interests include social network analysis, big data management, etc. As the first author, she has published papers in internationally renowned journals and conferences including TKDE, VLDB, ICDE, DASFAA, Information Sciences, etc.