Keynote Speaker 1Yinglin Wang

Full Professor

School of Information Management and Engineering,

Shanghai University of Finance and Economics,

Shanghai, China

Title: The application of value analysis in large language models, intelligent services and other aspects.


In recent years, with the improvement of large model capabilities, value analysis tasks (including value classification and alignment, etc.) have become a focus of attention. Analyzing the value of generated content can help us effectively control the output results of large language models and avoid them from outputting harmful information. On the other hand, value classification tools can also help dialogue robots identify the value tendencies of different people, thereby providing better services to humans. Intelligent dialogue systems equipped with value classification capabilities can assist in social surveys, thus providing first-hand information for social computing (such as financial investment, customer service, decision making). This report systematically introduces the research methods and data related to value analysis in recent years, and discusses the current challenges, potential research directions and applications in the field of value analysis.


Yinglin Wang is a full professor in the School of Information Management and Engineering, Shanghai University of Finance and Economics. He was previously a full professor in the Department of Computer Science at the Shanghai Jiao Tong University. Prior to that, he was a postdoc at Shanghai Jiao Tong University. He completed his Ph.D. in pattern recognition and intelligent control from Nanjing University of Science and Technology in 1998. In 2001 and 2005, he visited the University of Hong Kong and Stanford University for cooperative research. His current research interests are broadly in machine learning, natural language processing, and large language model. His research work has been published at top NLP conferences including ACL, EMNLP and well-known journals such as KBS and IPM. He has taken charge of many research projects sponsored by NSFC and Ministry of Science and Technology of China. He is a recipient of two Shanghai science and technology progress awards.  

Keynote Speaker 2Hector Perez-Meana


Title: Computer vision applications to reduce accidents while driving.


Hector Perez-Meana received the M.S. degree in The University of Electro-communications, and a Dr. Eng. degree from Tokyo Institute of Technology in 1989. In 1991.  He was a visiting researcher at the Fujitsu Laboratories from April 1989 to July 1991.  From 1992-1997, he was a professor at the Electrical Engineering Department of the Metropolitan University of Mexico.  Then, he became a professor in the Mechanical and Electrical Engineering Department at IPN, where he was the Dean of the Graduate and Research Section from 2006 to 2010, as well as from 2016 to 2019.  He was Chair of the ISITA, 1998, of the IEEE MWSCAS, 2009, the IEEE-IWBF, 2018, and the SOMET 2021.  He received the IEICE Best Paper in 1991, the IPN Research Award in 1999 and the IPN Research Diploma in 2000.  The is a Life Senior Member of the IEEE, a member of the IEICE, member of the Mexican Academy of Science; as well as from the National Researchers System of Mexico.  He has published about 280 journal papers. He has been director of 35 PhD Thesis and 49 MSc thesis.    His research interests include adaptive systems, signal and image processing and pattern recognition.