Keynote Speeches

Re-configuring data practices for Intelligent, Reliable and Responsible decision-making systems

Prof. Timos Sellis

Visiting Research Scientist, Meta Platforms, Inc. (formerly known as Facebook)

Adjunct Professor, School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Australia

Abstract

In this talk we will focus on how data management practices need to be re-configured in order to support Intelligent, Reliable and Responsible decision-making systems. To maximise the benefits of AI while at the same time mitigating or even preventing its risks, the international community recently began promoting the concept of Trustworthy AI (TAI) as a foundation behind such systems. TAI is based on the idea that trust builds the foundation of societies, communities, economies, and sustainable development, and that therefore individuals and societies will only ever be able to harness the full potential of AI, if trust can be established in the development, deployment, and use of this technology.

TAI is characterized by being lawful, ethical, as well as socially and technically robust. In order to achieve this, the realisation of TAI demands the fulfilment of the seven core requirements by technical and non-technical means: (#1) support of human agency and oversight, (#2) be technically robust and safe, (#3) provide privacy and data governance, (#4) be transparent, (#5) support diversity, non-discrimination and fairness, as well as (#6) societal and environmental wellbeing, and (#7) provide accountability [1]. Adjusting data management practices to achieve the above is an interesting challenge.

Bio

Timos Sellis is a Research Scientist at Meta Platforms, Inc. (formerly known as Facebook, USA) and an Adjunct Professor at Swinburne University of Technology (Australia), where between 2016 and 2020 he was a Professor and the Director of the Data Science Research Institute. He got his Diploma degree in Electrical Engineering in 1982 from the National Technical University of Athens (NTUA), Greece. In 1983 he got the M.Sc. degree from Harvard University (USA) and in 1986 the Ph.D. degree from the University of California at Berkeley (USA), both in Computer Science. He has been in the past a faculty member at the University of Maryland (USA, 1986-92), the National Technical University of Athens (Greece, 1992-2013), and RMIT University (Australia, 2013-2016). Prof. Sellis was also the Director of a new research institute he founded in Greece, the Institute for the Management of Information Systems (IMIS) of the "Athena" Research Center (www.imis.athena-innovation.gr) between 2007 and 2013.

His research interests include big data, data streams, graph data management, data integration, and spatio-temporal database systems. He has published over 300 articles in refereed journals and international conferences in the above areas, has over 17,600 citations to his work and has participated and coordinated several national and international research projects.

Prof. Sellis is a recipient of the prestigious Presidential Young Investigator (PYI) award given by the President of USA to the most talented new researchers (1990), and of the VLDB 1997 10 Year Paper Award in 1997 (awarded to the paper published in the proceedings of the VLDB 1987 conference that had the biggest impact in the field of database systems in the decade 1987-97). He was the president of the National Council for Research and Technology of Greece (2001-2003). In November 2009, he was awarded the status of IEEE Fellow, for his contributions to database query optimization, and spatial data management, and in November 2013 the status of ACM Fellow, for his contributions to database query optimization, spatial data management, and data warehousing. In March 2018 he received the IEEE TCDE Impact Award, for contributions to database systems research and broadening the reach of data engineering research.

Trusted Database Technology: A Foundation for Enabling Digital Trust

Prof. Beng Chin Ooi

Professor, Department of Computer Science, National University of Singapore, Singapore

Abstract

The advancement of technologies has caused many organizations to re-strategize and adopt digital transformation. Along with it, transactions and interactions between organizations have been digitized. However, digitalization is creating the dependency of society on increasingly complex, interconnected systems and networks, which increases our exposure to various threats such as loss of data, loss of control over the software systems and networks, mistrust due to ill-intended contents and actions, misuse of technology and so on. To bootstrap trust and support secure data sharing, cross-institution transactions and business in the digital world, various technologies are needed to empower cross-institutional collaboration with increasing trust through secure communication, transfer and exchange of digital documents and assets, verifiability, and auditability. Trusted database technology is foundational to supporting digital trust. It is required to not only ensure privacy, integrity of data, but also of the computation on the data. The design space for trustworthy database systems is vast, and there is no one-size-fit-all solution. I shall discuss design and implementation issues and requirements of a flexible trustworthy database system and our works in this area.

Bio

Beng Chin is Lee Kong Chian Centennial Professor and NGS faculty member at the National University of Singapore (NUS), an adjunct Chair Professor at Zhejiang University, China, 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. He is a fellow of the ACM , IEEE, and Singapore National Academy of Science (SNAS). Beng Chin serves as a non-executive and independent director of ComfortDelgro, a transportation company, and AlDigi Holdings, a Fintech company.

Beng Chin's research interests include database systems, distributed and blockchain systems, and large scale analytics, in the aspects of system architectures, performance issues, security, accuracy and correctness. He works closely with the industry (eg. NUHS, Jurong Health, Tan Tok Seng Hospital and Singapore General Hospital on healthcare analytics and prediabetes prevention), and exploits IT for efficiency in various application domains, including healthcare, finance and smart city.

Beng Chin was the recipient of ACM SIGMOD 2009 Contributions award, a co-winner of the 2011 Singapore President's Science Award, the recipient of 2012 IEEE Computer Society Kanai award, 2013 NUS Outstanding Researcher Award, 2014 IEEE TCDE CSEE Impact Award, 2016 China Computer Federation (CCF) Overseas Outstanding Contributions Award, and 2020 ACM SIGMOD EF Codd Innovation Award. He was a recipient of VLDB'14 and VLDB’19 Best Paper awards, and SIGMOD 2020 Research Highlight award.

Beng Chin has served as a PC member for international conferences such as ACM SIGMOD, VLDB, IEEE ICDE, WWW, and SIGKDD, and 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'18, Industry track of VLDB'19, BCDL'19 and ACM SoCC'20. He has served as the President of VLDB Endowment (2014-2017), and editor-in-chief of IEEE Transactions on Knowledge Engineering (2008-2012), Elsevier Journal of Big Data Research (2014-2016), and ACM/IMS Transactions on Data Science (2018-2021).

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