Mr. Philip M. Piqueira
Mr. Philip M. Piqueira is Vice President- Global Standards for UL Standards & Engagement. He is Chair of the Board of the American National Standards Institute (ANSI) , the President of the United states National Committee of the IEC. His contribution in standardization sector is remarkable, and he was the recipient of NEMA’s prestigious “Kite and Key” award in 2002 for standards leadership, ANSI’s Meritorious Service Award in 2007 for contributions to the U.S. voluntary standardization system, and the Astin-Polk International Standards Medal in 2015 for promoting trade.
Keynote Title
UL Standards Approach to Mitigate Carbon Emission
Keynote Abstract
The severity of the climate change and extreme weather have been happened frequently in past couple of years, which brings up challenges to meet 2030 targets for reduced emission reported at the 2021 UN Climate Change Conference and the Paris agreement goal of 1.5 °C. To address this challenge, here is to share a solution from standards perspective through clean energy generation, distribution, utilization, and repurposing, which is applicable globally.
Shunqing Zhang
Shanghai University
Shunqing Zhang (S'05-M'09-SM'14) received the B.S. degree from the Department of Microelectronics, Fudan University, Shanghai, China, in 2005, and the Ph.D. degree from the Department of Electrical and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, in 2009. He was with the Communication Technologies Laboratory, Huawei Technologies, as a Research Engineer and then a Senior Research Engineer from 2009 to 2014, and a Senior Research Scientist of Intel Collaborative Research Institute on Mobile Networking and Computing, Intel Labs from 2015 to 2017. Since 2017, he has been with the School of Communication and Information Engineering, Shanghai University, Shanghai, China, as a Full Professor. His current research interests include energy efficient 5G/5G+ communication networks, hybrid computing platform, and joint radio frequency and baseband design. He has published over 60 peer-reviewed journal and conference papers, as well as over 50 granted patents. He has received the National Young 1000-Talents Program and won the paper award for Advances in Communications from IEEE Communications Society in 2017.
Keynote Title
Key Technologies for Integrated Communication and Sensing
Keynote Abstract
Integrated communication and sensing (ISAC) has been identified as a key enabling technologies for the sixth generation (6G) mobile communication systems. In this talk, we focus on two ISAC cases to share our research progresses. The first case is the theoretical study on channel perdition using the ISAC concept, where we align the wireless signal propagation with the physical movement to obtain more insightful channel prediction schemes. In the second case, a prototype study using ISAC concept has been developed for energy efficient wireless networks. Through the above two cases, we hope to enlarge the research scope of ISAC and pave the way for 6G communication networks.
Wenbin Dai
Shanghai Jiao Tong University
Wenbin(William) Dai, Professor at the School of Electrical Information and Electronic Engineering, Shanghai Jiao Tong University. He received the National Outstanding Youth Fund in 2020 and is the Chief-Secretary of the Shanghai Association of Automation. He has been mainly engaged in the research of next-generation distributed industrial control software, industrial informatics, and industrial edge computing. He has cooperated with Huawei to complete the world's first cloud-based PLC experiment and developed the first set of independent and controllable new-generation Industrial Control Software. As the first author, he published more than 50 papers in IEEE Transactions and conferences, published 2 monographs, and co-published 1 monograph. He is the PI of 3 projects of the NSFC and the Ministry of Science and Technology's Key R&D Program, and won the title of Top Young Talent in Shanghai and Tang Zhongying Young Scholar. At the same time, he is a registered expert of the IEC TC65B Distributed Industrial Control Software Standards Committee, serves as the chairman of the IEEE edge computing standard working group and presides over the formulation of three IEEE international standards for edge computing. He currently serves as the associate editor of IEEE T-II, IEEE-IES Adcom Voting Member, IEEE-IES TC-II chair, and technical program chair of several IEEE-IES flagship conferences such as IEEE ICIT 2022, IEEE ISIE 2023, IEEE INDIN 2025.
Keynote Title
Towards Universal Automation: The Future Generation of Industrial Automation Systems
Keynote Abstract
Industrial internet and edge computing bring lots of new opportunities for traditional industrial automation systems. With massive computing, storage, and communication resources available on field devices, new low-code development must be investigated to handle multiple applications on multiple edge devices simultaneously. A system-level modeling language is needed to achieve efficient and reliable design and development of industrial edge applications. In this talk, we will discuss model-driven and data-driven approaches for automatic code generation for industrial edge applications based on the IEC 61499 standard. The next-generation industrial edge computing systems rely on a system-level modeling language based on IEC61499, deterministic network and embedded virtualization technologies. The new generation of industrial edge applications can be applied to discrete manufacturing, process control, motion control and other fields, and plays an important role in automatic code generation, autonomous optimization and self-management.
Haofen Wang
Tongji University
Haofen Wang is a full professor at College of Design & Innovation, Tongji University. Prior to that, He served as CTOs for two well-known AI startups (i.e., Leyan and Gowild). He is also one of the co-founders of OpenKG, the world-largest Chinese open knowledge graph community. He has taken charge of several national AI projects and published more than 100 related papers on top-tier conferences and journals. He developed the first interactive emotional virtual idol in the world. The intelligent assistant he built has answered questions from more than one billion users when they did online shopping. He has also served as deputy directors or chairs for several NGOs like CCF, CIPS and SCS.
Keynote Title
Augmented Language Models: Key Technologies and its Applications
Keynote Abstract
With the rise of ChatGPT, large language models (LLMs) have entered a hundred-model battle. However, its limitations such as hallucination and lack of knowledge updates restrict its widespread application in various vertical sectors. This talk will focus on various augmentation technologies for LLM. First, prompt engineering is one of the key factors to guide the accurate output of LLMs. Second, I will introduce retrieval augmented generation (RAG) based on external up-to-date knowledge, which is an enabler to avoid the "serious nonsense" of LLMs. Third, note that LLMs have evolved into intelligent agents with working memory and tool using, data fabric, and service orchestration & routing are key to agent planning and even multi-agents collaboration. Fourth, multi-modality is the trend, LLMs can help associate perception and action, and eventually achieve the integration of virtual world and physical world with embodied intelligence. Finally, the talk will cover two different paradigms of LLM and its applications as well as ecosystems in different domains.
Shanfeng Zhu
Fudan University
Shanfeng Zhu is a Professor at the Institute for Science and Technology for Brain-Inspired Intelligence, Fudan University. He received his Bachelor and Master degrees in Computer Science at Wuhan University and Ph.D. in Computer Science at City University of Hong Kong in 1996, 1999 and 2003, respectively. Before joining Fudan University in 2008, he was a Postdoctoral Fellow at Bioinformatics Center, Kyoto University. He was a visiting scholar at UIUC (March 2013-March 2014), and a visiting Associate Professor at Kyoto University (July 2016-Nov 2016). He was invited to join UniProt Scientific Advisory Board in Sep 2018. And he serves as an associate editor for the journal Bioinformatics Advance published by Oxford University press. His research focuses on developing and applying machine learning and data mining methods for Bioinformatics and Biomedical Informatics, especially biomedical text mining, protein function prediction, metagenomics and precision medicine.
Keynote Title
Recent advances in AI based large-scale biomedical semantic indexing
Keynote Abstract
With the rapid increase of biomedical articles, large-scale automatic semantic indexing has become increasingly important. For example, Medical Subject Headings (MeSHs) are used by the National Library of Medicine (NLM) to index almost all 36 million citations in MEDLINE. This greatly facilitates the applications of biomedical information retrieval， text mining and knowledge discovery. Automatic MeSH indexing faces great challenges as results of 1) a large number of labels (around 30000); 2) deep semantic information of biomedical text; and 3) limited information in title and abstract. The BioASQ challenge (2013-2022) provides a realistic and practical benchmark to advance the design of effective algorithms for large-scale MeSH indexing. Over the last few years, we have developed a series of SOTA machine learning-based methods to address these challenges in large-scale MeSH indexing, such as MeSHLabeler, DeepMeSH, AttentionXML, FullMeSH, and BERTMeSH. Additionally, I will talk about the problem of large-scale biomedical semantic indexing in languages other than English.
