Bio:Beng Chin is Lee Kong Chian Centennial Professor and NGS faculty member at the National University of Singapore (NUS). He is an adjunct Chang Jiang Professor at Zhejiang University, a visiting Distinguished Professor at Tsinghua University, and the director of NUS AI Innovation and Commercialization Centre at Suzhou, China. He obtained his BSc (1st Class Honors) and PhD from Monash University, Australia, in 1985 and 1989 respectively. Beng Chin is a fellow of the ACM 2011, IEEE 2009, and Singapore National Academy of Science (SNAS) 2016.Beng Chin’s research interests include database systems, distributed and blockchain systems, machine learning and large scale analytics, in the aspects of system architectures, performance issues, security, accuracy and correctness. He works closely with the industry (eg. National University Hospital, Jurong Health, Tan Tok Seng Hospital and Singapore General Hospital, on healthcare analytics and prediabetes prevention, and banks and investment firms on financial analytics), and exploits IT and technology such as 5G for disruption and innovation in various application domains, such as healthcare, finance and smart city. He initiated Apache SINGA, the first Apache Top Level Project on distributed deep learning, and BlockBench, the first benchmarking framework for private blockchain systems. Beng Chin was the recipient of ACM SIGMOD 2009 Contributions award, co-recipient of the Singapore President’s Science Award, the recipient of 2012 IEEE Computer Society Kanai award, 2013 NUS Outstanding Researcher Award, 2014 IEEE TCDE CSEE (Computer Science, Engineering and Education) Impact Award, 2016 China Computer Federation (CCF) Overseas Outstanding Contributions Award, and 2020 ACM SIGMOD EF Codd Innovations Award. He was a recipient of VLDB’14 and VLDB’19 Best Paper award, 2020 ACM SIGMOD Research Highlight Award. He has H-index of 83 and citations of 25,000+. Beng Chin has served as a PC member for international conferences such as ACM SIGMOD, VLDB, IEEE ICDE, WWW, and SIGKDD. He had served as Vice PC Chair for ICDE’00,04,06, PC co-Chair for SSD’93 and DASFAA’05, PC Chair for ACM SIGMOD’07, Core DB PC chair for VLDB’08, and PC co-Chair for IEEE ICDE’12, IEEE Big Data’15, BOSS’18, IEEE ICDE’8, VLDB’19 Industry Track, and ACM SoCC’20. He was an associate editor of VLDB Journal, Springer’s Distributed and Parallel Databases and, IEEE Transactions on Knowledge and Data Engineering, Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (TKDE)(2009-2012), founding co-Editor-in-Chief of Elsevier Journal of Big Data Research (2013-2015). associate editor of IEEE Transactions on Cloud Computing (TCC) and the founding editor-in-chief of ACM /IMS Transactions on Data Science (2018-2021). He is serving as an editor of Communications of ACM (CACM). He had served as a co-chair of the ACM SIGMOD Jim Gray Best Thesis Award committee 2008-2011, a trustee of VLDB endowment 2006-2017, as its secretary 2010-2013, and president 2014-2017, and as an Advisory Board Member of ACM SIGMOD, 2012-2017. He is serving as an overseas Council Member of China Computer Federation (CCF). Beng Chin is serving as a non-executive and independent director of ComfortDelgro (listed on SGX). a member of Hangzhou Government AI Development Committee (AI TOP 30) and Suzhou Industry Park AI Development Committee. Beng Chin had participated in the last three once-every-five-years database self assessement meetings: Claremont, Berkeley 2008, Beckman, Irvine 2013, Seattle 2018. Research and Systems:Beng Chin’s research focuses on the fundamental data and systems abstractions of modern data-driven applications. His works attempt to lay the foundation for the design and implementation of systems that are not only efficient, robust, but also scalable and secure. Beng Chin focuses on end-to-end pipeline supporting all data processing steps, from data cleaning, through data curation with human-in-the-loop (crowd sourcing) and big data processing, all the way to complex (machine learning and deep learning based) data analytics. The work produces a large-scale cloud software system that significantly improves on prior research-focused systems, with rigorous algorithmic and theoretical results. With the ubiquity of Big Data and fusion of applications and technologies, the projects are related in many aspects. Beng Chin approaches research problems and system design with the philosophy that all algorithms and structures should be simple, elegant and yet efficient so that they are implementable, maintainable and scalable in actual applications, and all systems must be efficient, scalable, extensible and easy to use. Details of his research projects could be found in DBSystem web site. His view on administration and setting up a strong database group could be found in 2011 SIGMOD Record interview. |
