Beng Chin OOI

Lee Kong Chian Centennial Professor
Department of Computer Science
School of Computing
National University of Singapore
Computing 1, Computing Drive, Singapore 117417

ooibc AT comp.nus.edu.sg
Tel: +65-6516 6465
Office: COM1, #03-22

2008may

Courses    Professional Activities    DBSystem Lab     Publications     Source Codes     Research Students     CV    简历

Bio:

Beng Chin is currently the Lee Kong Chian Centennial Professor and an NGS faculty member at the National University of Singapore (NUS), and a former dean of School of Computing (2007-2013). He is an adjunct Chang Jiang Professor at Zhejiang University, and a visiting Distinguished Professor at Tsinghua University. He is the lead PI of Singapore Blockchain Innovation Programme (SBIP). 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, 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. He was a recipient of 2013 Singapore National Day's Public Administration Medal (PPA) (Silver).

Beng Chin's research focuses on the fundamental data and systems abstractions of modern data-driven applications. His research interests include database (DB) systems, distributed (DDB) and blockchain systems (DBxBC), machine learning and large scale analytics (DBxAI), in the aspects of system architectures, performance issues, security, accuracy and correctness. He works closely with the industry (eg. National University Hospital, Ng Teng Fong General Hospital, Tan Tok Seng Hospital and Singapore General Hospital, on AI- and data-driven healthcare analytics, and banks and investment firms on financial analytics), and exploits latest technology (eg. 5G, AI, blockchain) for disruption and innovation in various data- and AI-driven domains, including healthcare, finance and smart city. He led the design and implementation of Apache SINGA, the first Apache Top Level Project on distributed deep learning, BlockBench, the world first benchmarking framework for blockchain systems, COOL, a fast AI- and data- driven cohort OLAP engine, and Falcon, a privacy-preserving, efficient and incentive-aware federated learning platform for data collaboration.

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, 2021 NUS University Research Recognition Award and 2013 NUS Outstanding Researcher 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 93 and citations of 30,800.

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, 2017-2020. He is serving as an editor of Communications of ACM (CACM) and a member of ACM Publications Board.

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, 2012-2023. He is serving as an overseas Council Member of China Computer Federation (CCF).

Beng Chin had participated in the last four once-every-five-years database self assessment meetings: Claremont, Berkeley 2008, Beckman, Irvine 2013, Seattle 2018, and Boston, 2023. He had delivered keynotes at CNCC'16, CHINC'18, CNCC'18, VLDB'18, NDBC'19, DASFAA'21, IEEE ICDE'22 etc.

Beng Chin is serving as a non-executive and independent director of ComfortDelgro, VICOM and AlDigi Holdings, a member of Hangzhou Government AI Development Committee (AI TOP 30), Suzhou AI Strategy Committee, and Suzhou Industry Park AI Applicational Innovation Committee. He was an advisor to Huobi on its Huobi Chain, and Cynopsis Solutions.


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 (DBxX) 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 therefore be efficient, scalable, extensible and easy to use. Details of his research projects could be found in DBSystem web site.

His view and philosophy on administration and setting up a strong database systems group could be found in 2011 SIGMOD Record interview.


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