Report Title: Green Computing: Research Landscape and Vision

Speaker: Professor Bingsheng He, Vice Dean of the School of Computing, National University of Singapore

Professor Shuhao Zhang, Huazhong University of Science and Technology

Time: 10:30, September 25, 2025

Venue: Lecture Hall B501, Feicui Science and Education Building

Report Abstract:

This report presents key insights from a national green computing research conducted in Singapore in 2024, with extensive participation from academia, industry and the government. As the computing load driven by artificial intelligence, cloud computing and edge computing grows exponentially, its environmental footprint is also expanding. This study identifies the sustainability challenges that need to be addressed urgently, and proposes strategic directions in green architecture, energy-efficient cloud design, sustainable AI and edge computing, etc. The report provides specific recommendations for industry and relevant institutions, from promoting green standards and incentive mechanisms to advancing research on low-power AI models and nature-inspired computing.

Speaker Profile (Bingsheng He):

Bingsheng He is currently a Professor and Associate Dean for Research at the School of Computing, National University of Singapore. Prior to this, he was a faculty member at Nanyang Technological University, Singapore (2010–2016), and a Researcher at the Systems Research Group of Microsoft Research Asia (2008–2010), where he mainly engaged in research on building high-performance cloud computing systems for Microsoft. He received his Bachelor's degree from Shanghai Jiao Tong University (1999–2003) and his Ph.D. from the Hong Kong University of Science and Technology (2003–2008). His current research interests include cloud computing, database systems and high-performance computing. He has received industrial-academic awards from Microsoft, NVIDIA, Xilinx, Alibaba, Webank, SenseTime and AMD, and his research work has won Best Paper Awards or been selected into Best Paper Collections in top conferences or journals such as SIGMOD 2008, VLDB 2013 (demo), IEEE/ACM ICCAD 2017, PACT 2018, IEEE TPDS 2019, FPGA 2021, and VLDB 2023 (industry)/2024. Since 2010, he has served as the Chair of many international conferences and workshops, including IEEE CloudCom 2014/2015, BigData Congress 2018, ICDCS 2020 and ICDE 2024. He also served as an Associate Editor of several international journals, including IEEE Transactions on Cloud Computing (TCC), IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE Transactions on Knowledge and Data Engineering (TKDE), Springer Journal of Distributed and Parallel Databases (DAPD) and ACM Computing Surveys (CSUR). He is a Distinguished Member of ACM and a Fellow of IEEE.

Speaker Profile (Shuhao Zhang):

Shuhao Zhang is currently a Professor at the School of Computer Science and Technology, Huazhong University of Science and Technology. His research spans stream data processing, database systems, high-performance parallel and heterogeneous computing, and focuses on a new system framework SAGE supporting large model inference and applications such as Multi-Agent and Retrieval-Augmented Generation (RAG). Before joining HUST, he served as an Assistant Professor at Nanyang Technological University (NTU) in Singapore and conducted postdoctoral research at the Technical University of Berlin in Germany, in-depth cooperation in the frontiers of distributed data management and efficient stream computing. His work is committed to key issues such as vector retrieval and approximate search, agent memory management, streaming semantic state maintenance and multi-tenant inference scheduling. He has published dozens of papers in top international conferences/journals such as SIGMOD, VLDB, ICDE, NeurIPS and EMNLP, and holds a number of international patents. Relevant results have been applied in scenarios such as the Internet of Things, green computing, smart cities and large model cloud services, promoting the real-time performance and scalability of data-driven intelligent applications. Shuhao Zhang actively serves the academic community, serving as a Program Committee Member of conferences such as SC, ICDE and CIKM, has received funding from a number of national and enterprise cooperation projects, and leads the team to build the next generation of efficient, reliable and independently controllable large model inference and data processing platform.