Speakers

Fu Haohuan, professor and vice dean of Tsinghua Shenzhen International Graduate School, serves as deputy director of the National Supercomputing Center in Shenzhen. For decades, he has dedicated himself to interdisciplinary research at the intersection of high-performance computing and geoscience, publishing over 200 papers in these fields. His work focuses on developing innovative approaches to enhance Earth system science research through high-performance computing and artificial intelligence technologies. Particularly addressing critical challenges in climate change, seismology, and Earth observation, he has successfully translated the computational power of domestic supercomputers into simulation capabilities for complex phenomena and predictive capabilities for future scenarios.
Professor Fu won three ACM Gordon Bell Prizes, the highest award in the field of high performance computing (fully-implicit atmospheric dynamic solver in 2016, non-linear earthquake simulation in 2017, and large-scale quantum circuit simulation in 2021). These research findings have significantly enhanced models’ precision in simulating extreme natural disasters and large-scale stochastic quantum circuits.
As the principal investigator, he has undertaken the National Natural Science Foundation of China (NSFC) Cross-disciplinary Outstanding Youth Fund Project and the Key R&D Program of the Ministry of Science and Technology. Other achievements and awards include: 2017 Chinese Institute of Electronics Award For Science and Technology Advancements (Only 14 worldwide), 2017 Tsinghua University's Top 10 Achievements, 2018 Jiangsu Province's May 4th Youth Medal, 2020 China May 4th Youth Medal, 2021 China Electronics Society Science and Technology Progress First Prize, 2022 Tsinghua University’s Team of Excellence(Team Leader), 2023 Outstanding Communist Party Member of Tsinghua University, 2023 Wu Wenjun Award for AI Science and Technology Advancements (Second Class), etc. In 2025, he was awarded the IEEE Fellow.

Prof. Dr. Ercan Engin Kuruoğlu is a Full Professor and Ph.D. Supervisor at the Tsinghua University Shenzhen International Graduate School (SIGS). He serves as the Principal Investigator of the Time-Varying Data Science Group, focusing his research on statistical signal processing, machine learning, and information theory. After earning his Ph.D. from the University of Cambridge, he spent two decades as a Chief Scientist at the Italian National Council of Research (ISTI-CNR) before joining Tsinghua University. An IEEE Fellow and Alexander von Humboldt Fellow, his work on non-Gaussian data and causal machine learning is widely applied across remote sensing, telecommunications, and computational biology.

Zihan Geng is an Associate Professor at the Tsinghua Shenzhen International Graduate School (SIGS), specializing in Computational Imaging and Optical Signal Processing. He earned his Ph.D. from Monash University in 2018, later working as a Senior Engineer at Huawei and an Assistant Professor at the Harbin Institute of Technology. His research fuses artificial intelligence with advanced optics to build breakthrough technologies, including a coin-sized 3D camera and ultrafast 3D tracking systems that process data 200 times faster than traditional video methods.

Dr. Chao REN is a Professor at the University of Hong Kong. She is the Director of the Msc in Sustainable Environment Design and the Associate Director of the HKU Jockey Club Enterprise Sustainability Global Research Institute. She specializes in applied climatology and climate design. Chao’s multi-dimensional, cross-disciplinary research has transferred scientific data into new knowledge to address social needs, enhance policy-making and support evidence-based designs in China, Taiwan, Singapore, The Netherlands and France since 2006. She is the Awardee of the 2023 University-level Knowledge Exchange Excellence Award and the 2022 Rosie Young 90 Medal Outstanding Young Woman Scholar at HKU. She is also the Recipient of the Timothy Oke Award for early- & mid-career scientists given by the International Association for Urban Climate in 2020.
Chao’s publication with focuses ranging from examining the relationship between urban climate and urban morphological characteristics, developing an urban climatic mapping system and a wind corridor plan, to analysing human thermal comfort and public health risk for subtropical high-density cities. Her latest book is ‘Local Climate Zone Application in Sustainable Urban Development’ published in 2024. She has been named in the World’s Top 2% of Scientists List by Stanford University (2023-25) and Top 1% Scholars by Clarivate (2025).
Chao serves as a co-Chief Editor for Urban Climate and an Editorial Advisor for Cities & Health (2018-), and is a member of Urban Climate Expert Team and the Study Group on Greenhouse Gas Monitoring and of the World Meteorology Organization. She also serves as the steering committee member of the Global Heat Health Information Network and Southeast Asia Heat Health Hub. She has also been elected as a Board Member of the International Association for Urban Climate (2017-2021). She has been involved in several international collaborative research reports, including the IPCC AR6 (Contributing Author of Chapter 6 Cities, Settlements and Key Infrastructure), Climate Change and Cities ARC3.3 (Lead Author of Chapter 2), the China report of the Lancet Countdown on Health and Climate Change (Lead Author of WGII) and the 7th Global Environment Outlook (GEO-7) (Lead Author of Chapter 2) of UN Environment Programme. Locally she serves as a Member of the Strengthen Emergency Preparedness and Response Strategic Committee of the Hong Kong Red Cross.

Mr. Miao is the CFO of Ant Health. He also leads the Globalization Office of Ant Health. Mr. Miao joined Ant Group in Oct 2018 and has held the position of Finance Director. He is appointed as CFO of Ant Health in 2024. Prior to joining Ant Group, Mr. Miao worked at KPMG, Microsoft and Royal Dutch Shell. Mr. Miao obtained his Bachelor’s degree from Renmin University of China and his MBA degree from Darden Business Scholl of University of Virginia.

Torsten Hoefler is a Professor of Computer Science at ETH Zurich, a member of Academia Europaea, and a Fellow of the ACM, IEEE, and ELLIS. He received the 2024 ACM Prize in Computing, one of the highest honors in the field. Following a Performance as a Science vision, he combines mathematical models of architectures and applications to design optimized computing systems. Before joining ETH Zurich, he led the performance modeling and simulation efforts for the first sustained Petascale supercomputer, Blue Waters, at the University of Illinois at Urbana-Champaign. He is also a key contributor to the Message Passing Interface (MPI) standard where he chaired the “Collective Operations and Topologies” working group. Torsten won best paper awards at his field’s top conference ACM/IEEE Supercomputing in 2010, 2013, 2014, 2019, 2022, 2023, 2024, and at other international conferences. He has published numerous peer-reviewed scientific articles and authored chapters of the MPI-2.2 and MPI-3.0 standards. For his work, Torsten received the IEEE CS Sidney Fernbach Memorial Award in 2022, the ACM Gordon Bell Prize in 2019, the ACM Gordon Bell Prize in Climate Modeling in 2025, Germany’s Max Planck-Humboldt Medal, the ISC Jack Dongarra award, the IEEE TCSC Award of Excellence (MCR), ETH Zurich’s Latsis Prize, the SIAM SIAG/Supercomputing Junior Scientist Prize, the IEEE TCSC Young Achievers in Scalable Computing Award, and the BenchCouncil Rising Star Award. Following his Ph.D., he received the 2014 Young Alumni Award and the 2022 Distinguished Alumni Award of his alma mater, Indiana University. Torsten was elected to the first steering committee of ACM’s SIGHPC in 2013 and he was re-elected for every term since then. He was the first European to receive many of those honors; he also received both an ERC Starting and Consolidator grant. His research interests revolve around the central topic of performance-centric system design and include scalable networks, parallel programming techniques, and performance modeling for large-scale simulations and artificial intelligence systems.