Prof. Witold Pedrycz
University of Alberta, Canada
IEEE Life Fellow
Biography : Witold Pedrycz (IEEE Life Fellow) is Professor in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. Dr. Pedrycz is a foreign member of the Polish Academy of Sciences and a Fellow of the Royal Society of Canada. He is a recipient of several awards including Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Society, IEEE Canada Computer Engineering Medal, a Cajastur Prize for Soft Computing from the European Centre for Soft Computing, a Killam Prize, a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society, and 2019 Meritorious Service Award from the IEEE Systems Man and Cybernetics Society.
His main research directions involve Computational Intelligence, Granular Computing, and Machine Learning, among others.
Professor Pedrycz serves as an Editor-in-Chief of Information Sciences, Editor-in-Chief of WIREs Data Mining and Knowledge Discovery (Wiley), and Co-editor-in-Chief of Int. J. of Granular Computing (Springer) and J. of Data Information and Management (Springer).
Prof. Yi-Cheng Zhang
University of Fribourg, Fribourg, Switzerland
Member of The Academy of Europe (Academia Europaea)
Speech Title: Personal Assistant (PA) Era Outlook
Abstract: Large language models have brought a new technological revolution. They have comprehensive knowledge and understanding abilities in various fields, and can learn knowledge from massive data and integrate and apply it to practical problems. Such general models can provide comprehensive and integrated knowledge support for humans in multiple fields, but they are difficult to provide personalized services that are closely related to people. Personal empowerment technology will be able to provide personalized support and services for individuals. By understanding and analyzing individual needs, preferences and behavior patterns, provide corresponding suggestions, recommendations and solutions. The future era will be an era of personal empowerment and general model integration. Combining personal empowerment and general models can provide more comprehensive and personalized services for individuals. Large language models can provide in-depth knowledge and professional advice in various fields according to individual needs and interests, and help individuals make better decisions and solve problems. The combination of personal empowerment and general models will provide more intelligent and personalized services for people, and truly become a powerful assistant in people’s daily lives.
Biography: Professor Yi-Cheng Zhang is a senior professor at the University of Fribourg in Switzerland. He is a member of the First Academic Committee of Alibaba Research Institute, and an expert of the China Information Society 50 People Forum. He has published more than 250 papers in top international journals such as RPL, PNAS, and Physics Reports, and have been cited over 32,000 times on Google Scholar, with an h-index of 65. He has authored four academic books published by Oxford University Press and has undertaken multiple international projects under the European Union's 7th Framework Programme. His major academic contribution includes the famous KPZ (Kardar-Parisi-Zhang) equation, which is one of the three major works for which his mentor, Professor Giorgio Parisi, was awarded the Nobel Prize in Physics in 2021. The Austrian mathematician Martin Haire also received the Fields Medal in 2014 for his outstanding contributions to the solution of the KPZ equation. In addition, Professor Zhang has made pioneering and foundational contributions in various fields of information sciences and complex sciences, such as Minority Game, Econophysics, and Information Physics. His research achievements have not only had a wide academic impact internationally but have also been widely applied in industries. He is one of the few top scientists who have made significant contributions in both the academic and industrial sectors.