Bio:  Pietro Lio received the PhD degree in complex systems and nonlinear dynamics from the School of Informatics, dept of Engineering, University of Firenze, Italy and the PhD degree in theoretical genetics from the University of Pavia, Italy. He is currently a professor of computational biology with the Department of Computer Science and Technology, University of Cambridge and a member of the Artificial Intelligence Group. He is also a member of the Cambridge Centre for AI in medicine, ELLIS (European Laboratory for Learning and Intelligent Systems), Academia Europaea, Asia Pacific Artificial Intelligence Association. His research interests include graph representation learning, AI and Medicine, Systems Biology.

Bio:  Boon Thau Loo is the RCA Professor in the Computer and Information Science (CIS) department at the University of Pennsylvania. He is also the Associate Dean for Graduate Programs, where he oversees all academic and admissions operations for doctoral, master’s and professional programs at Penn Engineering. He received his Ph.D. degree in Computer Science from the University of California at Berkeley in 2006. Prior to his Ph.D., he received his M.S. degree from Stanford University in 2000, and his B.S. degree with highest honors from University of California-Berkeley in 1999. His research focuses on distributed data management systems, Internet-scale query processing, and the application of data-centric techniques and formal methods to the design, analysis and implementation of networked systems. He is the recipient of the David J. Sakrison Memorial Prize (2006) for the most outstanding dissertation research in the Department of EECS at University of California-Berkeley, and the ACM SIGMOD Dissertation Award (2007), NSF CAREER award (2009), the Air Force Office of Scientific Research (AFOSR) Young Investigator Award (2012), Penn’s Emerging Inventor of the year award (2018), the Ruth and Joel Spira award for Excellence in Teaching (2021), and the University Lindback award for distinguished teaching (2022). He has published 160+ peer reviewed publications and has supervised sixteen Ph.D. dissertations and three postdocs. His graduated doctoral students and postdocs include three tenured professors, four current tenure-track professors, and winners of five dissertation awards. As an entrepreneur, he co-founded two companies: Netsil, a cloud microservices analytics company acquired by public cloud company Nutanix Inc., and Termaxia, an energy-efficient big data storage company acquired by Frontiir.  

Bio:  Chen Change Loy is a Nanyang Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore. He serves as the Co-Associate Director for S-Lab, NTU and Director of MMLab@NTU. He is also an Adjunct Associate Professor at the Chinese University of Hong Kong. He received his PhD (2010) in Computer Science from the Queen Mary University of London. Before joining NTU, he served as a Research Assistant Professor at the MMLab of the Chinese University of Hong Kong, from 2013 to 2018. He is the recipient of 2019 Nanyang Associate Professorship (Early Career Award) from Nanyang Technological University. He is recognized as one of the 100 most influential scholars in computer vision by AMiner. His research interests include computer vision and deep learning with a focus on image/video restoration, enhancement, and content creation. He serves as an Associate Editor of the IJCV and TPAMI. He also serves/served as the Area Chair of top conferences such as CVPR, ICCV, and ECCV. He is a senior member of IEEE.

Bio:  Wayne Luk is Professor of Computer Engineering at Imperial College. He was a Visiting Professor at Stanford University. His research focuses on theory and practice of customizing hardware and software designs for demanding applications. He is a Fellow of the Royal Academy of Engineering, the IEEE, and the BCS.

Bio:  Mohamad Sawanis Chair Professor in Westlake University, Hangzhou, China, and Emeritus Professor in Polytechnique Montreal, Canada. He is founder and director of the Center of Excellence in Biomedical Research on Advanced Integrated-on-chips Neurotechnologies (CenBRAIN Neurotech) in Westlake University, Hangzhou, China. Also, he is founder of the Polystim Neurotech Laboratory in Polytechnique Montréal. He received the Ph.D. degree from University of Sherbrooke, Canada. Dr. Sawan research activities are bridging micro/nano electronics with biomedical engineering to introduce smart medical devices dedicated to improving the quality of human life. He is co-founder and was Editor-in-Chief of the IEEE Transactions on Biomedical Circuits and Systems (2016-2019). He hosted the 2016 IEEE International Symposium on Circuits and Systems, and the 2020 IEEE International Medicine, Biology and Engineering Conference (EMBC). He was a Canada Research Chair in Smart Medical Devices (2001-2015), and was leading the Microsystems Strategic Alliance of Quebec, Canada (1999-2018). Dr. Sawan published more than 1000 peer reviewed papers and many books and patents. Among the numerous received honors, Dr. Sawan received the Chinese National Friendship Award, The Lebanese’s President Medal of Merit, the Shanghai International Collaboration Award, the Queen Elizabeth II Golden Jubilee Medal. Dr. Sawan is Fellow of the Royal Society of Canada, Fellow of the Canadian Academy of Engineering, Fellow of the IEEE, and “Officer” of the National Order of Quebec.

Bio:  Dinggang Shen is a Professor and a Founding Dean with School of Biomedical Engineering, ShanghaiTech University, Shanghai, China, and also a Co-CEO of United Imaging Intelligence (UII), Shanghai. He is a Fellow of IEEE, AIMBE, IAPR, and MICCAI. He was also a recipient of the Distinguished Investigator Award from The Academy for Radiological & Biomedical Imaging Research, USA (2019). He was Jeffrey Houpt Distinguished Investigator and a Full Professor (Tenured) with The University of North Carolina at Chapel Hill (UNC-CH), Chapel Hill, NC, USA, directing The Center of Image Analysis and Informatics, The Image Display, Enhancement, and Analysis (IDEA) Lab, and The Medical Image Analysis Core. He was also a tenure-track assistant professor in the University of Pennsylvanian (UPenn), and an Instructor in the Johns Hopkins University. His research interests include medical image analysis, computer vision, and pattern recognition. He has published more than 1600 peer-reviewed papers in the international journals and conference proceedings, with H-index 133 and over 75K citations. He serves as an Editor-in-Chief for Frontiers in Radiology, as well as an editorial board member for eight international journals. Also, he has served in the Board of Directors for MICCAI Society in 2012-2015, and was General Chair for MICCAI 2019.

Bio:  Dr. Steinegger is an Assistant Professor at the Seoul National University, where he is affiliated with the Biology department, Institute of Molecular Biology and Genetics, Artificial Intelligence Institute, and the Bioinformatics Graduate School. His research group focuses on developing big data and machine learning algorithms to analyze genomic and proteomic sequence data. The group is best known for bioinformatics software to cluster (Linclust), assemble (Plass), search (MMseqs2) sequences and to predict protein structures (AlphaFold2/ColabFold), search (Foldseek), and compress (Foldcomp) them. These software packages are used by researchers worldwide and have been installed hundreds of thousands of times. Dr. Steinegger is an expert on large-scale sequence data analysis and method development and advocates for open science and open source.

Bio:  Dacheng Tao is currently a Professor of Computer Science, Peter Nicol Russell Chair and an Australian Laureate Fellow in the Sydney AI Centre and the School of Computer Science in the Faculty of Engineering at The University of Sydney. He was the founding director of the Sydney AI Centre. He mainly applies statistics and mathematics to artificial intelligence and data science, and his research is detailed in one monograph and over 200 publications in prestigious journals and proceedings at leading conferences. He received the 2015 and 2020 Australian Eureka Prize, the 2018 IEEE ICDM Research Contributions Award, and the 2021 IEEE Computer Society McCluskey Technical Achievement Award. He is a Fellow of the Australian Academy of Science, AAAS, ACM and IEEE.

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Bio:  Dr. He Wang is a tenure-track assistant professor in the Center on Frontiers of Computing Studies (CFCS) at Peking University, where he founds and leads Embodied Perception and InteraCtion (EPIC) Lab. His research interests span 3D vision, robotics, and machine learning, with a special focus on embodied AI. His research objective is to endow robots working in complex real-world scenes with generalizable 3D vision and interaction policies in a scalable way. He has published more than 40 papers in top conferences and journals of computer vision, robotics, and learning, including CVPR/ICCV/ECCV/TRO/ICRA/IROS/NeurIPS/ICLR/AAAI. His pioneering work on category-level 6D pose estimation, NOCS, receives the 2022 World Artificial Intelligence Conference Youth Outstanding Paper (WAICYOP) Award and his work also receives ICRA 2023 outstanding manipulation paper award finalist and Eurographics 2019 best paper honorable mention. He serves as an associate editor of Image and Vision Computing and serves as an area chair in CVPR 2022 and WACV 2022. Prior to joining Peking University, he received his Ph.D. degree from Stanford University in 2021 under the advisory of Prof. Leonidas J. Guibas and his Bachelor's degree from Tsinghua University in 2014.

Bio:  Yu Wang, professor, IEEE fellow, chair of the Department of Electronic Engineering of Tsinghua University, dean of Institute for Electronics and Information Technology in Tianjin, and vice dean of School of information science and technology of Tsinghua University. His research interests include the application specific heterogeneous computing, processing-in-memory, intelligent multi-agent system, and power/reliability aware system design methodology. Yu Wang has published more than 80 journals (60 IEEE/ACM journals) and 200 conference papers in the areas of EDA, FPGA, VLSI Design, and Embedded Systems, with the Google citation more than 17,400. He has received four best paper awards and 12 best paper nominations. Yu Wang has been an active volunteer in the design automation, VLSI, and FPGA conferences. He will serve as TPC chair for ASP-DAC 2025. He serves as the editor of important journals in the field such as ACM TODAES and IEEE TCAD and program committee member for leading conferences in the top EDA and FPGA conferences.

Bio:  Dr Qi Wu is an Associate Professor at the University of Adelaide and was the ARC Discovery Early Career Researcher Award (DECRA) Fellow between 2019-2021. He is the Director of Vision-and-Language at the Australia Institute of Machine Learning. Australian Academy of Science awarded him a J G Russell Award in 2019. He obtained his PhD degree in 2015 and MSc degree in 2011, in Computer Science from the University of Bath, United Kingdom. His research interests are mainly in computer vision and machine learning. Currently, he is working on the vision-language problem, and he is primarily an expert in image captioning and visual question answering (VQA). He has published more than 100 papers in prestigious conferences and journals, such as TPAMI, CVPR, ICCV, ECCV. He is also the Area Chair for CVPR and ICCV.

Bio:  Jianyi Yang is a Professor in Shandong University. He has received a few prestigious rewards including the National Science Fund for Distinguished Young Scholars. His research interests include protein and RNA structure prediction. He has made significant contributions to the development of many widely used tools, such as trRosetta and I-TASSER. He has published over 60 papers in journals such as Nature Methods, PNAS, with >14000 citations.

Bio:  Yang You is a Presidential Young Professor at the National University of Singapore. He is on an early career track at NUS for exceptional young academic talents with great potential to excel. He received his PhD in Computer Science from UC Berkeley. His advisor is Prof. James Demmel, who was the former chair of the Computer Science Division and EECS Department. Yang You's research interests include Parallel/Distributed Algorithms, High Performance Computing, and Machine Learning. The focus of his current research is scaling up deep neural networks training on distributed systems or supercomputers. In 2017, his team broke the world record of ImageNet training speed, which was covered by the technology media like NSF, ScienceDaily, Science NewsLine, and i-programmer. In 2019, his team broke the world record of BERT training speed. The BERT training techniques have been used by many tech giants like Google, Microsoft, and NVIDIA. Yang You’s LARS and LAMB optimizers are available in industry benchmark MLPerf. He is a winner of IPDPS 2015 Best Paper Award (0.8%), ICPP 2018 Best Paper Award (0.3%), AAAI 2023 Distinguished Paper Award (0.14%), and ACM/IEEE George Michael HPC Fellowship. Yang You is a Siebel Scholar and a winner of Lotfi A. Zadeh Prize. Yang You was nominated by UC Berkeley for ACM Doctoral Dissertation Award (2 out of 81 Berkeley EECS PhD students graduated in 2020). He also made Forbes 30 Under 30 Asia list (2021) and won IEEE CS TCHPC Early Career Researchers Award for Excellence in High Performance Computing. For more information, please check his lab’s homepage at https://ai.comp.nus.edu.sg/

Bio:  Prof. Xiaoyang Zeng received the Ph.D. (Hons.) degrees from Chinese Academy of Sciences in 2001. Then joined Fudan University as Post-Doctor researcher from 2001 to 2003. Prof. Zeng has been with Fudan University as a faculty since 2003, where he is currently chair professor, also the vice dean of the School of Microelectroincs. He has been served as the TPC Member of ISSCC and ASSCC, also elected as the Co-chair of the Circuit & System Division and the Fellow of the CIE. His research fields include information security chips, base-band processing technologies for wireless communication; mixed-signal IC designs and ultra-low power IC Methodology. Prof. Zeng has over 200 academic papers in publication and applied for 120 patents.

Bio:  Dr.‬ Fumin ZHANG‬ is Chair Professor and Director of the Cheng Kar-Shun Robotics Institute at the Hong Kong University of Science and Technology. He is also Dean’s Professor adjunct in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He received a PhD degree in 2004 from the University of Maryland (College Park) in Electrical Engineering and held a postdoctoral position in Princeton University from 2004 to 2007. His research interests include mobile sensor networks, maritime robotics, control systems, and theoretical foundations for cyber-physical systems. He received the NSF CAREER Award in September 2009 and the ONR Young Investigator Program Award in April 2010. He is currently serving as the co-chair for the IEEE RAS Technical Committee on Marine Robotics, associate editors for IEEE Transactions on Automatic Control, and IEEE Transactions on Control of Networked Systems, IEEE Journal of Oceanic Engineering, and International Journal of Robotics Research.‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

Bio:  Hanwang Zhang is an Associate Professor at Nanyang Technological University's School of Computer Science and Engineering. His research interests include Computer Vision, Natural Language Processing, Causal Inference, and their combinations. Due to his contribution in applied causality, he has received numerous awards including the Singapore President Award Young Scientist 2021, IEEE AI’s-10-To-Watch 2020, Alibaba Innovative Research Award 2019, Nanyang Assistant Professorship 2018, and several best paper awards.

Bio:  Yue Zhang is a tenured Professor at Westlake University. His research interests include NLP and its underlying machine learning algorithms. His major contributions to the field include psycholinguistically motivated machine learning algorithm, learning-guided beam search for structured prediction, pioneering neural NLP models including graph LSTM, and OOD generalization for NLP. He authored the Cambridge University Press book ``Natural Language Processing -- a Machine Learning Perspective''. He is the PC co-chair for CCL 2020 and EMNLP 2022, and action editor for Transactios for ACL. He also served as associate editor for IEEE/ACM Transactions of Audio Speech and Language Processing (TASLP), ACM Transactions on Asian and Low-Resource Languages (TALLIP), IEEE Transactions on Big Data (TBD) and Computer, Speech and Language (CSL). He won the best paper awards of IALP 2017 and COLING 2018, best paper honorable mention of SemEval 2020, and best paper nomination for ACL 2018 and ACL 2023.

Bio:  Bolei Zhou is an Assistant Professor in the Computer Science Department at the University of California, Los Angeles (UCLA). He earned his Ph.D. from MIT in 2018. His research interest lies at the intersection of computer vision and machine autonomy, focusing on enabling interpretable human-AI interaction. He has developed many widely used neural network interpretation methods such as CAM and Network Dissection, as well as computer vision benchmarks Places and ADE20K. He has been area chair for CVPR, ECCV, ICCV, and AAAI. He received MIT Tech Review's Innovators under 35 in Asia-Pacific Award.

Bio:  Jun Zhou is currently a Professor at UESTC. His major research interest is algorithm and processor co-design for energy-efficient intelligent sensing. Before joining UESTC, he has worked as Research Scientist and Principle Investigator at IMEC Netherlands and Institute of Microelectronics A*STAR Singapore from 2008 to 2017. He has published more than 100 papers in prestigious conferences and journals, including ISSCC, JSSC, DAC, CICC, TBioCAS, and TCAS-I. He has served or is serving as A-SSCC TPC Sub-Committee Chair of Digital Circuits & Systems, Guest Editor of JSSC, Associate Editor of TBioCAS and Associate Editor of TVLSI. He has also served as a TPC/OC Member for a number of IEEE conferences, including DAC, SOCC, ICCD, and ISCAS.

Bio:  Prof. S. Kevin Zhou obtained his PhD degree from University of Maryland, College Park and currently is a Distinguished Professor and Founding Executive Dean of School of Biomedical Engineering, University of Science and Technology of China (USTC). He was a Principal Expert of AI and a Senior R&D Director at Siemens Healthineers Research. Dr. Zhou has published 260+ book chapters and peer-reviewed journal and conference papers, registered 150+ granted patents, and written and edited 6 research monographs. The two recent books he led the edition are entitled "Deep Learning for Medical Image Analysis, SK Zhou, H Greenspan, DG Shen (Eds.)" and "Handbook of Medical Image Computing and Computer Assisted Intervention, SK Zhou, D Rueckert, G Fichtinger (Eds.)". He has won multiple awards including R&D 100 Award (Oscar of Invention), Siemens Inventor of the Year, UMD ECE Distinguished Alumni Award, BMEF Editor of the Year, Finalist Paper for MICCAI Young Scientist Award (twice). He has been a program co-chair for MICCAI 2020 conference, an associate editor for IEEE Trans. Medical Imaging (TMI), IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI), and Medical Image Analysis, and an area chair for AAAI, CVPR, ICCV, MICCAI, and NeurIPS. He has been elected as a treasurer and board member of the MICCAI Society, an advisory board member of MONAI (Medical Open Network for AI), and a fellow of AIMBE, IAMBE, IEEE, MICCAI, and NAI.

Bio:  Mr. Zhu Feng is a Distinguished Professor of Zhejiang University, Editor-in-Chief of Elsevier Publishing Group's Comp Biol Med (IF=7.7), and Associate Editor of American Chemical Society's J Chem Inf Model (IF=5.6) in East Asia. His research work has been selected as one of the "China's 100 Most Influential International Academic Papers" by CITIC, Ministry of Science and Technology, and one of the "Top 10 Progresses in Bioinformatics in China in 2020". In the past five years, he has published more than 70 papers in Nature Protoc, Nucleic Acids Res, Adv Sci, Anal Chem, Engineering, Acta Pharmacol Sin, Mol Cell Proteomics, J Mol Biol, etc.,

Bio:  Dr. Jun Zhu is a Bosch AI Professor at the Department of Computer Science and Technology in Tsinghua University and an IEEE Fellow. He was an Adjunct Faculty at the Machine Learning Department in Carnegie Mellon University (CMU) from 2015 to 2018. Dr. Zhu received his B.E and Ph.D. in Computer Science from Tsinghua in 2005 and 2009, respectively. Before joining Tsinghua in 2011, he did post-doctoral research in CMU. His research interest lies in machine learning and applications in text and image analysis. Dr. Zhu has published over 100 papers in the prestigious conferences and journals. He is an associate editor-in-chief for IEEE Trans. on PAMI. He served as senior area chairs for ICML, NeurIPS, and ICLR. He was a local co-chair of ICML 2014. He is a recipient of several awards, including ICLR Outstanding Paper Award, IEEE CoG Best Paper Award, XPlorer Prize, IEEE Intelligent Systems "AI's 10 to Watch" Award, MIT TR35 China, CCF Young Scientist Award, and CCF first-class Natural Science Award. His team has won several first-place awards in international competitions, including all the three tasks in NeurIPS 2017 adversarial attack and defense for deep learning and the intelligent decision task in ViZDoom 2018.

Bio:  Chengqing Zong received his Ph.D. degree from the Institute of Computing Technology, Chinese Academy of Sciences (CAS), in March 1998. From May 1998 to April 2000, he worked at the National Laboratory of Pattern Recognition (NLPR), Institute of Automation, CAS, as a post-doctor research fellow, and he has been working with NLPR since finishing his post-doctoral program. In 1999 and 2001, Dr. Zong twice worked in the Advanced Telecommunications Research Institute International (ATR) of Japan, as a guest researcher. In 2004, he visited CLIPS-IMAG, France, as visiting scholar. Now he is a professor, IEEE Fellow, ACL Fellow, AAIA Fellow, CAAI Fellow and CCF Fellow. His research interests include machine translation, text data mining and cognitive language computing. He has authored/co-authored more than 200 papers. His book Statistical Natural Language Processing is very popular in NLP community of China, and the book Text Data Mining has received widespread attention. He served the top-tier international conference ACL 2015 as PC Co-Chair and ACL 2021 as General Conference Chair, and also the Asian Federation on Natural Language Processing (AFNLP) as president from 2019 to 2021. Now he is Vice-President-elect of Association for Computational Linguistics.