Hong Mei

Academician of the Chinese Academy of Sciences (CAS)
Fellow of the World Academy of Sciences for the Advancement of Science in Developing Countries (TWAS)
Foreign Member of the Academia Europaea
Fellow of ACM, CCF, and IEEE.

Biography:Professor Mei Hong is a distinguished computer software expert, Academician of the Chinese Academy of Sciences (CAS), Fellow of the World Academy of Sciences for the Advancement of Science in Developing Countries (TWAS), Foreign Member of the Academia Europaea, and Fellow of ACM, CCF, and IEEE. He is the Director of the Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education. Since 1992, he has been with Peking University, where he previously served as Dean of the School of Electronics Engineering and Computer Science. He has also held leading positions as Vice President of Shanghai Jiao Tong University, Vice President and Executive Vice President of Beijing Institute of Technology, Vice President of the Academy of Military Sciences, and President of the 12th Board of the China Computer Federation (CCF). Professor Mei has received numerous prestigious awards, including the First and Second Prizes of the National Technological Invention Award, the Second Prize of the National Natural Science Award, the Second Prize of the National Science and Technology Progress Award, the Ho Leung Ho Lee Prize for Scientific and Technological Progress, the Tan Kah Kee Science Award in Information Technology Science, and the IEEE Computer Society Technical Achievement Award, among others.

Xiaoping Chen

Academician of the Chinese Academy of Sciences
Professor, Chief Physician, and Doctoral Supervisor at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
Director of the Academic Committee of Tongji Hospital
Title: Medicine 4.0: The Paradigm Shift in the Digital Era

Biography:Chen Xiaoping, Academician of the Chinese Academy of Sciences, is a Professor, Chief Physician, and Doctoral Supervisor at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. He also serves as the Director of the Academic Committee of Tongji Hospital. Dedicated to the clinical treatment and basic research of hepatobiliary and pancreatic diseases over the long term, he is one of the key pioneers in the field of liver surgery in China. Academician Chen has made systematic and innovative contributions in areas such as liver cancer surgery, liver transplantation, hepatolithiasis, and portal hypertension, proposing several internationally influential surgical theories and techniques. He has led multiple national key research and development programs, major projects of the National Natural Science Foundation of China, and provincial-level research initiatives. He has published hundreds of academic papers, with several appearing in top-tier international journals such as Annals of Surgery, Hepatology, and Journal of Hepatology. As the primary recipient, he has been awarded the National Science and Technology Progress Award (Second Class), the National Technology Invention Award (Second Class), and numerous provincial and ministerial-level science and technology prizes. Currently, he serves as an editorial board member or advisory editor for several domestic and international professional journals, including Annals of Surgery and the Chinese Journal of Hepatobiliary Surgery. As a leading academic figure in Chinese surgery, he has made outstanding contributions to promoting the international development of hepatobiliary surgery in China.

Beng Chin Ooi

Foreign Member of the Chinese Academy of Sciences
Fellow of the Singapore Academy of Sciences
Fellow of the Academy of Engineering Singapore
Foreign Member of the European Academy of Sciences
Fellow of the ACM
Fellow of the IEEE
Fellow of the CCF
Title: Transforming Healthcare With AI-powered Data Systems and Analytics

Abstract: Data and AI are at the forefront of innovation, propelled by recent breakthroughs of key technologies, such as foundation models, system architecture, and cloud connectivity. The development has disrupted many existing practices and operational models, and is likely to cause further transformation and paradigm shifts. However, realizing its full potential in specialized domains, such as healthcare, remains a significant challenge, demanding innovative systems and algorithmic solutions in addition to acceptance by key stack holders. In this talk, I shall first share an end-to-end pipeline of data processing and analytics in healthcare, spanning from data cleaning, integration to AI models to deployment. I shall next present DIYHealth, which has been designed to democratize and transform healthcare, as a first step towards affordable and implementable prevention and intervention through early detection, and management of various diseases by reducing primary care to home care. The DIYHealth suite consists of a large-scale DIYHealth-900K dataset, a multimodal foundation model, DIYHealthGPT, and a benchmark, DIYHealthBench. I shall speculate on future healthcare ecosystems, where AI-powered data systems and applications may enable better and sustainable healthcare deliveries.

Biography: Beng Chin is a Qiushi Chair Professor at Zhejiang University and a professor at the School of Software Technology, Zhejiang University. Previously, he was the Lee Kong Chian Centennial Professor and served as the Dean of the School of Computing at the National University of Singapore from 2007 to 2013. He was also an adjunct Chang Jiang Professor at Zhejiang University. Additionally, he is a Distinguished Visiting Chair Professor at the National University of Singapore, a Visiting Chair Professor at Peking University, and a Visiting Distinguished Professor at Tsinghua University. Beng Chin is a fellow of the ACM 2011, CCF 2024, IEEE 2009, Singapore National Academy of Science (SNAS) 2016, and Singapore Academy of Engineering (SAEng) 2023. He is a foreign member of Academia Europaea 2022 and Chinese Academy of Sciences (CAS), 2023. Beng Chin’s research focuses on the fundamental data and systems abstractions of modern data-driven applications. Beng Chin was the recipient of the 2009 ACM SIGMOD Contributions award, 2020 ACM SIGMOD EF Codd Innovations Award, and 2024 ACM SIGMOD Systems Award, and a co-recipient of the 2011 Singapore President’s Science Award. He was also the recipient of 2012 IEEE Computer Society Kanai award, 2014 IEEE TCDE CSEE (Computer Science, Engineering and Education) Impact Award, 2016 China Computer Federation (CCF) Overseas Outstanding Contributions Award.

Qiang Yang

Fellow of the Canadian Academy of Engineering
Fellow of the Royal Society of Canada
Chief Artificial Intelligence Officer of WeBank
Professor Emeritus at the Hong Kong University of Science and Technology
Title: Future AI Challenges and Solutions by Federated Learning

Abstract: With the development of large Artificial Intelligence (AI) models, AI has entered a new era. One challenge in the practical application of large models is how to transfer the knowledge of general-purpose large models to localized small models while protecting the privacy and data security of all parties. In this talk, I will first explore several challenges faced by large AI models, then discuss how to use the "federated LLM " framework to provide some solutions.

Biography: Professor Yang Qiang is a Fellow of the Canadian Academy of Engineering (CAE) and the Royal Society of Canada (RSC), Director of Hong Kong PolyU Academy for AI, and Executive Vice President of the Chinese Association for Artificial Intelligence (CAAI). He is also a Fellow of CAAI, AAAI, ACM, IEEE and AAAS. He was the founding EiC of top international journals ACM Transactions on Intelligent Systems and Technology (ACM TIST) and IEEE Transactions on Big Data. His research focuses are the study and application of Transfer Learning, Federated Learning and AI Planning. His latest books are 《Transfer Learning》, 《Federated Learning》, 《Privacy-preserving Computing》，《AI Model Watermarks》，etc. Professor Yang is a Professor Emeritus of Hong Kong University of Science and Technology and the Chief AI Officer Emeritus of WeBank. He has also been conference or program chairs for IJCAI and AAAI. He has been honored with the 2017 ACM SIGKDD Distinguished Service Award and the 2023 IJCAI Donald E. Walker Distinguished Service Award.

Albert Y. Zomaya

Peter Nicol Russell Chair Professor of Computer Science at the University of Sydney
Fellow of the IEEE, the Australian Academy of Science, and the Royal Society of New South Wales, and an elected member of Academia Europaea and the European Academy of Sciences and Arts.
Title:Medicine, Rewired: Generative AI Meets Distributed Systems

Abstract: Medicine is entering a new era—one powered by the union of distributed systems and generative AI. This talk examines how these technologies, when combined, are transforming the way we perceive, deliver, and experience healthcare. Imagine hospitals, clinics, and research labs around the world securely sharing insights without ever moving sensitive data; algorithms that learn collaboratively to predict disease, tailor treatments, guide surgical robots, and accelerate drug discovery—all in real time. Through vivid examples—from pandemic response networks to intelligent diagnostic platforms—we’ll see how this distributed intelligence makes healthcare both smarter and more inclusive. But with this power comes new questions: Who owns the data? How do we ensure fairness, transparency, and access for all? At its heart, this talk is about more than technology—it’s about re-engineering trust, collaboration, and compassion through intelligent systems. Distributed computing and generative AI are working together to build a healthcare infrastructure that is decentralized yet deeply human, one designed to extend the reach of care and bring cutting-edge medical innovation to every corner of the world.

Biography: Albert Y. ZOMAYA is the Peter Nicol Russell Chair Professor of Computer Science at the University of Sydney and Director of the Centre for Distributed and High-Performance Computing. A global leader in parallel and distributed systems, he has authored more than 800 publications and 30 books, shaping the field’s research agenda for over three decades. He is a Fellow of the IEEE, the Australian Academy of Science, and the Royal Society of New South Wales, and an elected member of Academia Europaea and the European Academy of Sciences and Arts. Professor Zomaya previously served as Editor-in-Chief of IEEE Transactions on Computers, IEEE Transactions on Sustainable Computing, and ACM Computing Surveys. His work spans parallel and distributed computing, networking, and complex systems, with a lasting influence on both theory and practice.

Adam Dunn

Professor of Biomedical Informatics in the Sydney School of Public Health at the University of Sydney
Title:Addressing the health AI translation gap: developments in reasoning, explainability, and evaluation

Abstract: Across most application domains, reviews show a consistent disconnect between technical advances and evaluations in practice. While there are a range of factors that contribute to the gap between computer science and how AI is used in health, we are seeing interesting technical advances in areas that matter most in practice—safety, trust, fairness, and integration with workflow. Using key examples from across clinical and public health, this presentation will highlight recent advances in reasoning, explainability, and evaluation methods that are better aligned with how AI tools are used in practice. The presentation will end with recommendations for an AI research agenda targeted at bridging the health AI translation gap.

Biography:Adam Dunn (PhD 2007) is Professor of Biomedical Informatics in the Sydney School of Public Health at the University of Sydney. He has a broad research focus across artificial intelligence (AI) in health, including clinical applications using patient data, public health applications using data from the community and the online information they engage with, and clinical research applications using data from and about clinical trials. Prof Dunn is Deputy Editor npj Digital Medicine, Editor-in-Chief npj Digital Public Health, and Senior Program Committee for WebConf, ICWSM, and WebSci.

Jian Yang

Distinguished Professor and Doctoral Supervisor at Beijing Institute of Technology (BIT)
Title:Research Progress on Embodied Intelligent Surgical Navigation for Endoscopy

Abstract: In endoscope-guided minimally invasive surgery, three critical challenges remain: the difficulty in identifying critical structures like tumor-feeding vessels, the limitation of 2D imaging in visualizing deep anatomy, and the lack of quantitative methods to account for complex tissue deformation. To address these issues, our team established a research framework integrating image guidance with spatial perception. We developed high-precision, fully self-developed optical navigation components and a multi-source light-field fusion sensing approach, creating a navigational endoscope for intraoperative co-localization of instruments and lesions. Furthermore, we pioneered methods for 3D reconstruction, see-through visualization, and robust scene perception from 2D endoscopic images, overcoming the cross-modal gap to 3D understanding. Translated into practice, this research has resulted in a skull-base surgical navigation endoscopy system—the first domestic system in China with fully self-developed optical navigation cores to receive Class III medical device registration from the NMPA. It significantly enhances intraoperative visualization, reduces operative risk, and provides reliable support for precise surgery in complex anatomical regions.

Biography:Yang Jian is a Distinguished Professor and Doctoral Supervisor at Beijing Institute of Technology (BIT). He is a recipient of the National Leading Talent Program, Chief Scientist of the National Major Project on New Generation Artificial Intelligence, and Chief Scientist of the National Key Research and Development Program. He also serves as a Member of the Academic Committee of the School of Information and Electronics at BIT, and Responsible Professor of the National First-Class Discipline "Optical Engineering". He has long been engaged in teaching and research work in the fields of medical surgical robots, medical image processing, virtual reality and augmented reality, intelligent perception and navigation, human-computer interaction, and artificial intelligence. He has presided over 1 National 2030 Artificial Intelligence Major Project, 2 National Key Research and Development Programs, and 4 National Natural Science Foundation Projects, and participated in more than 10 national projects such as the 973 Program and 863 Program as a core member. He has published 175 SCI papers in internationally renowned journals such as Medical Image Analysis and IEEE Transactions on Medical Imaging, obtained 64 authorized national invention patents, among which 11 have been transformed and applied. The achievement transformation has obtained 1 National Class III Medical Device Registration Certificate and 4 National Class II Medical Device Registration Certificates. His research achievements have won 8 scientific research awards at or above the provincial and ministerial level, including the Second Class National Technological Invention Award, the First Class Technological Invention Award of the Ministry of Education, the First Class Science and Technology Award of the Chinese Society of Image and Graphics, the Second Class Chinese Medical Science and Technology Award, and the 24th China Patent Excellence Award.

Bin Sheng

Professor at the Department of Computer Science and Engineering, Shanghai Jiao Tong University
Title:REVERIE: Empowering Adolescent Physical and Mental Well-being through Virtual Reality Technology

Abstract: Overweight adolescents can enhance both physical fitness and mental health through physical exercise. However, they often face multiple barriers, such as lack of motivation, insufficient skills, low self-esteem, and negative peer pressure. In our research, we developed REVERIE, an advanced virtual reality (VR) fitness system specifically designed for adolescents. This system integrates deep reinforcement learning technology, focusing on exercise guidance to deliver an immersive virtual fitness experience. REVERIE comprises three core modules: a VR exercise environment, VR exercise guidance, and adaptive VR exercise rendering. To ensure the safety of the VR exercise environment, we adopted an iterative human-in-the-loop optimization process. We proposed a two-phase deep reinforcement learning approach based on templates and feedback, enabling virtual agents to master fine-grained motor skills and perform personalized adjustments. To improve the contextual rendering of VR exercises, we developed a motion-oriented immersive augmented rendering module within REVERIE. The results demonstrate that REVERIE outperforms existing methods in both safety and user experience. This study highlights the potential of VR-based exercise as an innovative approach to fitness management, effectively benefiting overweight adolescent populations.

Biography:Bin Sheng obtained his Ph.D. degree in Computer Science and Engineering from The Chinese University of Hong Kong in 2011. He currently serves as a Full Professor at the Department of Computer Science and Engineering, Shanghai Jiao Tong University. His research interests span virtual reality, machine learning, and medical data analysis. His work has been published in top-tier journals, including Nature Medicine, Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transactions on Visualization and Computer Graphics (TVCG), and International Journal of Computer Vision (IJCV). Dr. Sheng holds editorial roles as Managing Editor of The Visual Computer and Associate Editor of the Journal of Virtual Reality and Intelligent Hardware. He has also contributed significantly to conference organization, serving as Program Co-Chair of Computer Graphics International (CGI) from 2020 to 2022, and Conference Co-Chair of CGI (2023–2024) and CASA 2024. Additionally, he was AI Challenge Co-Chair for DeepDRiD (ISBI 2020), DRAC (MICCAI 2022), and MMAC (MICCAI 2023). In recognition of his contributions, he received the Outstanding Contribution Award from the Computer Graphics Society in 2023.

Chen Chen

professor of Cardiology, Chief Physician and Doctoral Supervisor of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Title:AI and cardiovascular diseases

Abstract: Advanced computing technologies, including artificial intelligence (AI), computational simulation, and extended reality, are reshaping cardiovascular medicine. These tools mark the onset of a new era of computational acceleration and promote a shift from reactive treatment to proactive health management. AI enables accurate image interpretation, disease risk stratification, and data-driven drug discovery. Computational simulations support virtual surgical planning and the design of personalized cardiovascular devices. Virtual clinical trials further enhance precision and accelerate medical technology development. Together, these innovations enable efficient data processing and real-time clinical decision support, driving cardiovascular medicine toward more predictive, preventive, and personalized models. Future progress will depend on closer integration between medicine and engineering, advances in explainable AI, and seamless multimodal data integration. These directions are critical for innovation in cardiovascular health management, interdisciplinary talent cultivation, and the creation of an intelligent and equitable health ecosystem.

Biography:Chen Chen is a professor of Cardiology, Chief Physician and Doctoral Supervisor of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. She mainly engaged in the pathogenesis of cardiovascular diseases and related translational research. Under the continuous funding of the National Natural Science Foundation of China Outstanding Young Science Foundation Project, the Joint Fund Key Project and the Hubei Provincial Natural Science Foundation Innovation Group Project, she has conducted in-depth researches on the therapeutic target discovery for heart failure. She has revealed multiple non-canonical mechanisms of miRNAs, such as transcriptional activation and translation activation, in different subcellular organelles leading to heart failure mediated by mitochondrial dysfuntion. Meanwhile, she developed antisense oligonucleotides and rAAV-based delivery strategies for miRNA therapies against heart failure and MASH, and antibody drug therapies for myocarditis. She has published more than 50 SCI papers with more than 3700 citations with the H-index of 34, and was selected as one of the top 2% of global scientists for the single recent year for four consecutive years (2021-2024). Her research was included in a number of domestic and international guidelines. She has won 2 first prizes of provincial and ministerial natural science awards and the 11th Jiang Bining Award in 2021. She has obtained 10 authorized national invention patents, 3 of which have been converted. She also won 2 Excellence Awards in the China Medical Device Innovation and Invention Competition in 2023 and 2024.

Ming Lv

Director of Technical Solutions for Smart Healthcare, Baidu Intelligent Cloud Group (ACG)
Title: Transforming Healthcare with the ERNIE Model

Abstract: Currently, we are standing at a pivotal historical moment where large-scale model technology is reshaping the healthcare industry. This speech will first analyze how, under the guidance of the national AI strategy, large-scale models have triggered innovations in AI computing paradigms and engineering restructuring, using Baidu's PaddlePaddle and ERNIE large-scale models as examples to elucidate the core approaches to full-stack technology development. Next, it will delve into specific scenarios in hospitals and the biomedical and pharmaceutical sectors, exploring the challenges and value of constructing medical vertical large-scale models, sharing practical applications of large-scale models in disease-assisted diagnosis and treatment, scientific research, and patient health management, and showcasing their full-chain innovative explorations in the life sciences field, from basic research to drug development. Finally, we will look ahead together, focusing on the evolution of complex reasoning capabilities in large-scale models, post-training technology routes, and the application restructuring they drive. We will emphasize how to overcome core challenges such as multimodal fusion and the construction of clinical reasoning chains, ensuring that large-scale models serve clinical diagnosis and treatment and patients' full-cycle health management safely and efficiently, while exploring cutting-edge interdisciplinary applications at the intersection of medicine and engineering, jointly ushering in a new chapter in medical intelligence.

Biography: Ming Lv is the Director of Technical Solutions for Smart Healthcare, Baidu Intelligent Cloud Group (ACG). With nearly 20 years of experience in artificial intelligence and internet-based digital services, she has deep expertise in AI innovation and application scenarios within the healthcare and life sciences industries. Currently serving as Director of Technical Solutions for the Innovative Healthcare Department at Baidu Intelligent Cloud, she previously held positions as Senior Architect at IBM (China) and Dean of the Corporate Research Institute at STCN Healthcare. Her technical focus spans artificial intelligence architecture, large language model technologies and their applications, big data and cloud computing, as well as the application of large models in healthcare.

Lei Bi

Associate Professor at Shanghai Jiao Tong University, PhD Supervisor.

Biography: Lei Bi is an associate professor with the Institute of Translational Medicine at the Shanghai Jiao Tong University. Prior to that, he was a lecturer with the School of Computer Science at the University of Sydney and was a research fellow at the Australia Research Council Training Centre for Innovative BioEngineering. He received his PhD degree from the University of Sydney. His current research focus is on multi-modality medical image analysis and visualization, and he collaborates alongside with hospital and industry partners to translate the research outputs into clinical applications. His research has produced excellent results including more than 60 papers in leading venues in the field such as in Medical Image Analysis, IEEE TMI, CVPR, MICCAI etc and accumulated over 5900 citations. He has received competitive research grants from government and industries such as the ARC DECRA, DAAD AINet Fellowship, Australian Tour de Cure early career research grant. Currently, he is a guest editor for NPJ Digital Medicine, an associate editor for Frontiers in Radiology, an associate editor for the Journal of Visual Computer.

Yanyan Chen

Professor-Level Senior Engineer, Director of the Big Data & AI Office, Vice Dean of the Institute of Digital Intelligence, Tongji Hospital, Huazhong University of Science and Technology.

Biography: Chen Yanyan, PhD is a professor-level Senior Engineer and serves as Director of the Big Data & Artificial Intelligence Office and Vice Dean of the Institute of Digital Intelligence at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. She is a Standing Committee Member of the Medical AI Committee of the Chinese Hospital Association, Deputy Chair of the Medical Informatization Committee of the Chinese Women Physicians Association, a Member of the Smart Healthcare Committee of the Chinese Association of Integrative Medicine, and Deputy Chair of the Information Management Committee of the Hubei Hospital Association. She holds CDMP, CISA, PMP, and ITIL certifications. Dr. Chen has led seven research projects, including grants from the National Natural Science Foundation of China, and received the Second Prize of the Hubei Provincial Science and Technology Progress Award. Her work focuses on healthcare big-data governance and translational clinical AI.

Yong Gao

Chief Physician, MD, Director of Orthopedics at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology.

Biography: Professor Yong Gao is professor and Chief Physician of Orthopedics at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology; MD and Director of the Information & Data Center; former Visiting Scholar at the University of Michigan Medical Center. Holds executive and committee roles including Standing Member of the Information Management Committee of the Chinese Hospital Association, Member of the Medical AI Committee of the Chinese Hospital Association, Vice Chair of the Hospital Information Committee of the Hubei Society of Health Statistics and Informatics, Vice Chair of the Health Information & Internet Medicine Committee of the China Medical Education Association, Secretary-General of the Hubei Society for Intelligent Medicine, and Member of the National Expert Committee on the Clinical Application of Antitumor Drugs. Honors include “Top 100 County Hospital Presidents in China,” “Hubei Model Worker—Jingchu Role Model—Most Beautiful Health and Family Planning Worker,” and “Top Ten Doctors of Jingzhou.”

Neng Huang

Director, ERNIE Model Data Ecosystem Center

Biography: Currently serving as the Head of the Data Ecosystem Center for Baidu’s ERNIE Large Language Model, Neng Huang specializes in the field of AI-driven data assets. He is committed to promoting the inclusive development of large language model technologies through value-driven data mining and ecosystem construction. His work focuses on full-chain innovation in data collection, governance, circulation, and scenario-based applications, providing high-quality data support for ERNIE’s training and facilitating breakthroughs in AI technology and its industrial implementation. Neng Huang holds both Master’s and Bachelor’s degrees in Computer Science from Huazhong University of Science and Technology. He has previously worked at leading IT companies such as Microsoft and JD.com, accumulating extensive experience in internet commercialization across domains including marketing, cloud computing, and intelligent healthcare.

Hai Li

Chief Physician, Master's Supervisor, Director of the Information Center and Deputy Director of the Thyroid and Breast Surgery Department at Wuhan Central Hospital.

Biography: Dr. Li Hai is a Chief Physician and Master's Supervisor at Wuhan Central Hospital, serving as the Director of the Information Center and Deputy Director of the Thyroid and Breast Surgery Department. He holds multiple important academic positions, including Standing Director of the National Health Industry Enterprise Management Association, Standing Committee Member of the 1st Integrated Rehabilitation Professional Committee for Multiple Primary and Unknown Primary Tumors of the Chinese Anti-Cancer Association, and Committee Member of the Interventional Minimally Invasive Thyroid Branch of the China Medical Education Association. At the provincial and municipal levels, he concurrently serves as Vice Chairman of the Youth Committee of the Breast Cancer Professional Committee of the Hubei Anti-Cancer Association, Vice Chairman of the Breast and Thyroid Professional Committee of the Hubei Microcirculation Society, Vice Chairman of the Youth Physicians Branch of the Wuhan Medical Doctor Association, and Committee Member of the Yangtze River Academic Belt Breast Cancer Group (YBCSG), actively promoting cross-regional academic exchanges.

Liu Jun

Deputy Director, Senior Engineer

Biography: Liu Jun is a Senior Engineer and MBA graduate from Huazhong University of Science and Technology. He holds multiple leadership roles in China's digitalization and standardization sectors, including positions in the China Enterprise Digitalization Alliance and the Chinese Association of Drug Abuse Prevention and Treatment. He led the development of Hubei's first fully monitored intelligent pharmaceutical production line, recognized with a Provincial Science and Technology Progress Award. His previous experience includes senior positions at Wuhan Jianmin Pharmaceutical, Wuhan Aimin Pharmaceutical, and other major industrial firms.

Yufei Ren

Deputy Director of the Computer Center, Senior Engineer, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.

Biography: He is currently Deputy Director and Senior Engineer of the Computer Center at Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology (HUST), concurrently serving as Deputy Director of the Institute of Information Medicine at HUST and Vice Chairman of the Youth Committee of the Health Information Special Committee of Hubei Provincial Health Statistics and Information Association. With over 15 years of in-depth experience in the research and development of hospital information systems and the formulation of health information standards, he has presided over 4 provincial and ministerial-level scientific research projects (including those funded by the National Health Commission) and published more than 30 academic papers. He took the lead in formulating 2 national health industry standards as the first drafter and participated in drafting 14 others. He also serves as Associate Editor-in-Chief of Construction and Application of Chinese Medical Terminology System published by People's Medical Publishing House. He has won one Third-Class Prize of the Chinese Medical Science and Technology Award and one Third-Class Prize of the Hospital Technological Innovation Award of the Chinese Hospital Association.

Minghuan Wang

Professor and Chief Physician, Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.

Biography: Dr. Wang Minghuan is a Professor and Chief Physician in the Department of Neurology at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. A recipient of numerous prestigious honors, he has been selected for the National High-Level Young Talents Program, awarded the Hubei Provincial Outstanding Youth Fund, and recognized among the first cohort of the Hubei Provincial Outstanding Young Talents. He is also an inaugural member of the Chinese Stroke Association's "Stroke Future Leaders Program." Dr. Wang has secured significant research funding, serving as Principal Investigator for one Key R&D Project and one Young Scientist Project from the Ministry of Science and Technology, as well as three grants from the National Natural Science Foundation of China. He contributed to the Neurology textbook, part of the National Health Commission's "14th Five-Year Plan" teaching materials. With over 30 published SCI papers that have garnered more than 4000 citations, he has authored six ESI Highly Cited Papers. His professional appointments include Vice Chairman of the Brain Neuroscience Committee at the China Pharmaceutical Innovation and Research Development Association, and holding memberships in several specialized committees within the Chinese Society for Neuroscience, Chinese Medical Doctor Association, and Chinese Stroke Association.

Zhang Li

Director of the Department of Ultrasound Medicine, Director of the Ultrasound Research Laboratory, Deputy Director of the Institute of Cardiovascular Diseases at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology.

Biography: Professor Li Zhang is a distinguished physician-scientist specializing in cardiovascular ultrasound at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), where she holds multiple leadership roles including Director of the Department of Ultrasound Medicine and Deputy Director of the Institute of Cardiovascular Diseases. She is a Fellow of both the American Society of Echocardiography (FASE) and the American College of Cardiology (FACC), and has been recognized with prestigious awards including the National Excellent Young Scientists Fund. Professor Zhang leads significant clinical and research initiatives in ultrasound artificial intelligence, molecular ultrasound, and medical device innovation. She has authored over 110 SCI-indexed papers in top-tier journals such as Circulation, European Heart Journal, and Nature Communications. Her contributions have earned her several high-profile honors, including the 2024 Chinese Medical Science and Technology Youth Award and multiple Hubei Provincial Science and Technology Progress First Prizes.

Tong Zhang

Associate Researcher at Pengcheng Laboratory
PhD Supervisor, Adjunct PhD Supervisor at Southern University of Science and Technology
Secretary General of the CCF Digital Medicine Subcommittee.

Biography: Dr. Tong Zhang is an Associate Researcher at Pengcheng Laboratory, PhD Supervisor, and Adjunct PhD Supervisor at the Southern University of Science and Technology. He also serves as the Secretary General of the CCF Digital Medicine Subcommittee and is recognized as a High-Level Overseas Talent introduced by Shenzhen. Dr. Zhang received his PhD from the University of Sydney, Australia, and completed his postdoctoral fellowship at King’s College London. His research focuses on post-training of multimodal large models and spatiotemporal analysis. He has led and participated in multiple key national and provincial research projects, including the National Natural Science Foundation of China Regional Joint Fund and the Guangdong Natural Science Foundation General Projects. Dr. Zhang has published more than 50 papers in top international journals and conferences such as IEEE journals, Lancet sub-journals, AAAI, ACM-MM, and MICCAI, with two papers selected as ESI Highly Cited Papers and over 2,800 citations on Google Scholar. He has been invited to give special academic reports at leading global universities and research institutions, including the Technical University of Munich, Peking University, and Sun Yat-sen University. He received the 2022 Shenzhen Artificial Intelligence Excellence Service Award and led his team to win the championship of the ImageCLEF-24 International Medical Image Captioning Competition.

Zeng Xincheng

Scientific Computing Lead, Yangtze Scientific Computing (Hubei) Information Technology Co., Ltd.
Senior AIDD Algorithm Scientist

Biography: Zeng Xincheng is a Senior AIDD Algorithm Scientist at the Yangtze River 3D Scientific Computing Center. He primarily focuses on building and optimizing scientific computing service systems across the full spectrum of drug development scenarios. With profound theoretical expertise and extensive industrial experience in molecular modeling, property prediction, and generative models, his work is dedicated to advancing the deep integration and innovative application of computational science in the biomedicine field.

Long Zheng

Distinguished Professor, Huazhong University of Science and Technology (HUST), Recipient of the National Excellent Young Scientist Fund.

Biography: Distinguished Professor and Doctoral Supervisor of Huazhong University of Science and Technology (HUST), Recipient of the National Excellent Young Scientist Fund and Hubei Provincial Outstanding Young Scientist Fund. He obtained his Doctor of Engineering degree in Computer System Architecture from HUST in 2016 and conducted academic exchange visits at the Parallel and Distributed Computing Center of Nanyang Technological University, Singapore from 2014 to 2015.His research primarily focuses on emerging fields such as large AI models, graph computing, and data streaming. He has published over 80 papers in prestigious international academic conferences and journals in the field of computer systems, including ISCA, MICRO, HPCA, USENIX ATC, DAC, and SC. He has been granted 14 national invention patents and 6 US patents.Over the past five years, he has presided over more than 10 projects, including the National Key Research and Development Program Young Scientists Project, the National Natural Science Foundation of China (NSFC) Original Exploration Program Project/General Program/Young Scientists Project, Huawei Joint Laboratory Projects, and the Zhejiang Lab Key Project. He also serves as a core member of several national-level projects, such as the National Key Research and Development Program Projects/Topics and NSFC Key Programs.He has won 4 Best Paper Awards/Nominations at important international academic conferences, including FPGA'23, APPT'21, and PACT'18, as well as the Best Presentation Award at CGO'15. His research achievements were selected for the National "13th Five-Year Plan" Science and Technology Innovation Achievement Exhibition. He led his team to win the global championship of the IEEE/MIT/Amazon GraphChallenge, the most influential graph computing competition, for three consecutive years (2021-2023), marking the first domestic victory in 2021.Some of his key technologies have been applied in enterprises and institutions such as Tongji Hospital Affiliated to Tongji Medical College of HUST, State Grid Corporation of China, Ping An Technology, Zhejiang Tmall, and Baidu PaddlePaddle. Partial prototype systems have been open-sourced at https://github.com/CGCL-codes/. His achievements have been reported by more than 30 mainstream media outlets, including People's Daily (WeChat Official Account), South China Morning Post, AI Era, and DeepTech.

Yahui Li

Director of the Editorial Department of Computer Science
Executive Director of Chongqing Computer Society
Member of China Computer Society (CCF)
Member of China Association for Artificial Intelligence (CAAI)
Youth Editorial Board Member of Academic Publishing and Communication.
Title: Integrating disciplines and creating intelligent future: the forging path for high-quality development of Computer Science

Abstract: In recent years, the academic indicators of Computer Science have been increasing year by year, and its international influence is also constantly improving. It has been included in important domestic and foreign database such as Peking University Chinese Core, CSCD (Core Library), China Science and Technology Core, Scopus, DOAJ, etc. The report will focus on introducing the measures taken by Computer Science in attracting high-quality manuscript sources, strictly controlling manuscript quality, and serving authors, hoping to provide a higher quality academic exchange platform for researchers.

Biography: Yahui Li is the Director of the Editorial Department of Computer Science, Executive Director of the Chongqing Computer Society, Member of the China Computer Society (CCF), Member of the China Association for Artificial Intelligence (CAAI), and Youth Editorial Board Member of Academic Publishing and Communication. He has been successively awarded as an outstanding editor (president)/editorial director of the "West Cow Plan," an academic renowned editor/excellent editor of Chongqing Publishing, and an outstanding management talent of Chongqing Journals. He is mainly engaged in the editing, publishing, operation, and copyright work of scientific and technological journals. He has hosted or participated in subprojects of the National Key R&D Program, Chongqing Talent Program, Chongqing Key Academic Journal Publishing Funding Project, and the "Yu Bian Ren He Fund" Project of the Chongqing University Journal Research Association. He has published multiple papers in journals such as Editorial Journal and Publishing and Copyright.

Qing Ye

Ph.D. in Management, Senior Engineer, Master's Supervisor, External Mentor at The Chinese University of Hong Kong (Shenzhen).
Title:Artificial intelligence based multispecialty mortality prediction models for septic shock in a multicenter retrospective study Medical Innovation: From Research to Publication

Abstract: Septic shock is one of the most lethal conditions in ICU, and early risk prediction may help reduce mortality. We developed a TOPSIS-based Classification Fusion (TCF) model to predict mortality risk in septic shock patients using data from 4872 ICU patients from February 2003 to November 2023 across three hospitals. The model integrates seven machine learning models via the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), achieving AUCs of 0.733 in internal validation, 0.808 in the pediatric ICU, 0.662 in the respiratory ICU, with external validation AUCs of 0.784 and 0.786, respectively. It demonstrated high stability and accuracy in cross-specialty and multi-center validation. This interpretable model provides clinicians with a reliable early-warning tool for septic shock mortality risk, facilitating early intervention to reduce mortality.

Biography:Ph.D. in Management, Senior Engineer, Master's Supervisor, External Mentor at The Chinese University of Hong Kong (Shenzhen). Deputy Director of the Big Data and Artificial Intelligence Office, and Deputy Section Chief of the Information Management Department at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. Research Focus: Medical big data, machine learning, artificial intelligence, e-health, large language models, and related fields. Research Experience: Has led and participated in over 10 research projects. Published more than 20 papers in recent years in journals including npj Digital Medicine, Internet Research, Electronic Markets, Information Processing & Management, Journal of Medical Systems, Frontiers in Public Health, and JMIR mHealth and uHealth.

Mai Wang

Director of the Editorial Office of Health Data Science (English edition), Director of the General Management Department at the National Research Institute of Health Data Science, Peking University, and Director of the Education and Communication Laboratory at the Smart Healthcare Research Center, Institute for Advanced Study in Information Science and Technology, Peking University (Zhejiang), with the rank of Senior Research Fellow.
Title:Health Data Science Drives Medical Innovation: From Research to Publication

Abstract: This report focuses on the current research and applications of Health Data Science and Medical Artificial Intelligence in the healthcare field, and introduces the role of the Health Data Science journal in the dissemination of scientific research achievements and interdisciplinary cooperation. It sorts out the development trends of Health Data Science, and through key cases published in the Health Data Science journal—including clinical AI image diagnosis, public health big data monitoring, and smart hospital management—demonstrates data-driven medical innovation research and the value of interdisciplinary collaboration. The report will also introduce the writing characteristics of interdisciplinary forum articles, as well as the journal's indexing status, manuscript submission directions, and scientific research cooperation opportunities.

Biography:Wang Mai currently serves as Director of the Editorial Office of Health Data Science (English edition), Director of the General Management Department at the National Research Institute of Health Data Science, Peking University, and Director of the Education and Communication Laboratory at the Smart Healthcare Research Center, Institute for Advanced Study in Information Science and Technology, Peking University (Zhejiang), with the rank of Senior Research Fellow. Health Data Science is sponsored by Peking University and undertaken by the National Research Institute of Health Data Science, Peking University. Academician Qimin Zhan serves as the founding Editor-in-Chief. Selected into the "High-Start New Journals" program of China's Excellent Action Plan for Science and Technology Journals in 2020, the journal was reselected into the "English Journal Tier Program" in 2024. It has been indexed by renowned international databases including ESCI, PubMed, Scopus, and DOAJ, and is also included in the Chinese Core Journal of Science and Technology and the Chinese Science Citation Database (CSCD).

Liwen Xu

Lecturer at the Furong Laboratory, Central South University
Title:Multi-omics intelligent computing reveals tumor-immune interactions

Abstract: In recent years, cancer immunotherapy has made remarkable progress as an essential component of precision medicine. However, the complexity of tumor–immune system interactions—particularly their roles in immune evasion and drug resistance—remains a major challenge in both scientific research and clinical practice. To address these challenges, the speaker has proposed a series of approaches based on deep learning and large language models, focusing on key areas such as tumor genomic immune regulation, intercellular communication, and DNA–protein interactions. These efforts aim to gain deeper insights into the mechanisms of tumor–immune interactions, providing more precise and interpretable biological understanding for cancer immunotherapy.

Biography:Liwen Xu, Lecturer at the Furong Laboratory, Central South University. Selected for the Youth Talent Support Program of the China Association for Science and Technology (2023). Serves as Secretary-General of the Hunan Society of Bioinformatics and Chair of the Academic Exchange Committee of the Hunan Society of Biomedical Engineering. She has presided over the National Natural Science Foundation of China (Youth Program) and the China Postdoctoral Science Foundation (General Program), and has served as a subproject leader for the Hunan Provincial Key R&D Program. In addition, she has participated as a key member in nine national and provincial-level projects, including the National Key R&D Program of China and the Joint Research Project of the Macao Science and Technology Development Fund and the National Natural Science Foundation of China. Her main research focuses on AI-driven multimodal machine learning models for precision cancer immunotherapy. As first or corresponding author (including co-corresponding), she has published 12 papers in leading international SCI journals such as Nature Communications, Cancer Research, Briefings in Bioinformatics, and Big Data Mining and Analytics. Her publications include one ESI Highly Cited Paper, with a single paper cited up to 544 times. Her representative work, “TIP” provides a convenient computational platform for analyzing tumor immune phenotypes, enabling immunologists and clinical researchers to perform rapid, efficient, and comprehensive analyses. To date, it has been accessed and used more than 28,000 times across 70 countries and regions, and was highlight reported by the Journal Cancer Research.