Speakers 2024
Keynote Speaker Ⅰ
Prof. Yun Li
IEEE Fellow
Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, China
Bio: Professor Yun Li FIEEE obtained his PhD from University of Strathclyde, Glasgow, UK. He taught and researched into “AI for Engineering” at University of Glasgow for 28 years, where he was recognized by the University library as the second Top Author and served as the Founding Director of University of Glasgow Singapore and Founding Director of Joint Education with University of Electronic Science and Technology of China (UESTC). Since mid-2021, he has been Director of Industrial Artificial Intelligence Centre at Shenzhen Institute for Advanced Study, UESTC. Prof Li has published over 300 papers and books, one of which with the assistance of AI resolved a PID control issue puzzling practising engineers for over 50 years and has been the most popular paper in IEEE Transactions on Control Systems Technology almost every month still today since its publication in 2005. He holds 30 patents in China, Europe, United States and Japan. He has been funded over 30 million pounds to lead or co-lead 40 research projects in the UK, EU, Singapore and China. Currently, he leads two National Natural Science Foundation of China major projects and one National Key R&D Program of China project concerning the third-generation and compute-in-memory AI.
Speech Title: Grey-Box State-Space Model for the Large World Model of Artificial Intelligence
Abstract: The explosive growth in data volume and computational power has enabled the successful application of artificial intelligence (AI) to engineering science ("AI for Engineering"), potentially elevating industrial innovation beyond manual capabilities in exploration, imagination, and creativity. This talk introduces, in conjunction with large language models (LLMs) based on the Artificial Neural Network (ANN) and the Kolmogorov-Arnold Network (KAN), the next generation of artificial intelligence that is explainable (XAI), driven by both data and knowledge. In particular, a grey-box state-space model (SSM) for the “large world model (LWM)” will be discussed for the third-generation AI with explainability, modularity and extendibility. I will then illustrate its role in the transformation of "Computer-Aided Design" (CAD) in the third paradigm of science to "Computer-Automated Design" (CAutoD) in the fourth, to break through limitations of human designers, whereby enlightening original creativity, enhancing design performance, and shortening development gearing. Finally, the talk will briefly cover pilot applications to dynamic system modelling, electronic design automation, and engineering design.
Keynote Speaker Ⅱ
Prof. Shaoliang Peng
Hunan University, China
Bio: Changjiang Scholar, leader of Hunan Province's "Innovative Group" and "Outstanding Youth" funds, Deputy Director of the National Supercomputing Center in Changsha, and "Yuelu Scholar" second-tier professor/Ph.D. supervisor at Hunan University. In 2023, he was featured as one of the top 10 figures on the Xiangjiang Role Model Cover and named one of the Top 10 Outstanding Figures in Hunan Province's Digitalization. His research focuses on high-performance computing, big data, bioinformatics, and artificial intelligence. He has published 8 academic monographs and over 200 papers, with more than 9,000 citations, and holds over 50 patents. He has received several prestigious awards, including the National Science and Technology Progress Award (Second Prize, 2019), Hunan Province Technology Invention Award (First Prize, 2019, ranked 1st), Military Science and Technology Progress Award (First Prize, 2013), CCF Technology Invention Award (Second Prize, 2021, ranked 1st), CCF Natural Science Award (Second Prize, 2018, ranked 1st), and a Third-Class Merit Award in 2016. He is a member of the Biocross Expert Group of the Central Military Commission Science and Technology Committee, a review expert for the Ministry of Science and Technology, the Ministry of Industry and Information Technology, the Ministry of Education, and the National Natural Science Foundation of China. He is also the President (and initiator) of the Hunan Province Biomedical Engineering Society and serves as the Executive Editor for two SCI journals. In 2024, he was appointed to the Standing Committee of the CCF Large Model Forum. In 2020, he founded the world's first international academic journal on the Metaverse/Web 3.0, Metaverse, where he serves as Editor-in-Chief.
Speech Title: Generative AI Large Models in the Metaverse and Web 3.0 Era
Abstract: The Metaverse, also known as Web 3.0, is a virtual space parallel to and independent from the real world, covering a wide range of application areas. Currently, practical applications are mainly concentrated in industries such as gaming, news, live conferences, and digital collectibles, where there is a high degree of alignment. However, in sectors such as defense, industry, agriculture, healthcare, and artistic creation, application technologies are still in the exploratory stage. In 2023, generative AI continues to write new chapters for the Metaverse. This type of AI can autonomously generate various forms of content, including text, images, music, and videos, mimicking human creativity and imagination—sometimes even surpassing human abilities. For instance, in the healthcare field, the National Supercomputing Center in Changsha has co-developed Metaverse "digital therapy" software and electronic medications, providing comprehensive solutions for the detection, prediction, and treatment of conditions like depression, sleep disorders, and addiction to the internet, alcohol, and smoking. The system was evaluated and approved in July 2022 and has been tested in several top-tier hospitals, including Xiangya Hospital and Hunan Provincial People's Hospital. At present, the team is collaborating with the Hunan Provincial Department of Housing and Urban-Rural Development, the Changsha Big Data Bureau, the Changsha Education Bureau, and the Malanshan Hunan Broadcasting Group, integrating data and large model resources to build perceivable, learnable, growing, and tradable digital twin cities. They are also working on models such as the drug model "Shennong GPT," the construction model "Aladdin GPT," the education model "Jingshi Yincai Ruidao 1.0," and an AICG arts and animation rendering metaverse. In 2024, the team will publish a monograph titled AIGC + Metaverse/Web 3.0: 100 Questions to Understand the Underlying Technologies of the Digital Economy Era.
Keynote Speaker Ⅲ
Prof. Julio Gonzalo
Universidad Nacional de Educación a Distancia, Spain
Bio: Julio Gonzalo is director of the UNED Research Center in Natural Language Processing (NLP) and Information Retrieval (IR) in Madrid. Along his career he has worked on topics such as online reputation monitoring, toxicity and misinformation in Social Media, interactive cross-language search, computational creativity and semantic similarity. He has also worked extensively in the design and assessment of evaluation metrics for a wide range of Artificial Intelligence problems, which led to a Google Faculty Research Award (together with Enrique Amigó and Stefano Mizzaro). He has recently been general co-chair of ACM SIGIR 2022 and of IberLEF 2019-2022, the annual evaluation campaign for NLP systems in Spanish and other Iberian languages. He is currently leading ODESIA (odesia.es), a Spanish government initiative to measure the state of the art of language technologies in Spanish.
Speech Title: Experiments and Thoughts on Large Language Models and Autonomous Fiction Writing
Abstract: One of the most remarkable aspects of Large Language Models is their ease to writing creative texts. Under specific conditions, they have been shown to match and even improve average human writing skills. But is their writing truly creative, or just a repetition of the clichés they have been pre-trained with? Do they have a distinctive creative writing style? What is the role of (human) prompting in the creation process?
In the talk, I will discuss the creative writing potential of LLMs and their intrinsic limitations, paying special attention to the experiments carried out at UNED. These include a contest between GPT-4 and one of the best contemporary novelists in Spanish, Patricio Pron. The contest is inspired by past AI duels (such as DeepBlue vs Kasparov and AlphaGo vs Lee Sidol), and was designed to test whether LLMs can already challenge a top (rather than an average) fiction writer.
More notable speakers will be announced soon...
