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Keynote Lecture


Decision Guidance Systems and Applications to Manufacturing, Power Grids, Supply Chain and IoT

Alexander Brodsky
George Mason University
United States

Brief Bio
Alex Brodsky is Professor in the department of Computer Science and Director of the Masters of Science Degree in Information Systems at George Mason University. He teaches classes in Database Management and Decision Guidance Systems, graduated 15 PhD students and currently advises other four. Alex’s current research interests include Decision Support, Guidance and Optimization (DSGO) systems; and DSGO applications, including to Energy, Power, Manufacturing, Sustainability and Supply Chain. He earned his Ph.D. and prior degrees in Computer Science and/or Mathematics from the Hebrew University of Jerusalem.
Alex has published over 115 refereed papers, including five that received Best Paper Awards, in scholarly peer-reviewed journals, books and conference/workshop proceedings. For his research work related to DSGO systems, Alex received a National Science Foundation (NSF) CAREER Award, NSF Research Initiation Award, and funding from the Office of Naval Research (ONR), National Aeronautics and Space Administration (NASA), National Institute of Standards and Technology (NIST), and Dominion Virginia Power.
Alex serves/ed in leadership roles in research conferences, including as Conference Chair of IEEE International Conference on Tools with Artificial Intelligence (ICTAI-2017); Program Chair of IEEE International Conference on Tools with Artificial Intelligence (ICTAI-2013); Program Co-chair of the IEEE ICDE workshop on Data-Driven Decision Guidance and Support Systems (DGSS 2012, and DGSS 2013); General Vice Co-chair of the IEEE International Conference on Data Engineering (ICDE 2012); and Conference Chair of the Fifth International Conference on Principles and Practice of Constraint Programming (CP99).
Prior to joining Mason in 1993, Alex worked at IBM T.J. Watson Research Center, at Israel Aircraft Industries and was an R&D officer in the Computer Division of Communications, Electronics and Computer Corps, Israel Defense Forces. He also has start-up and commercialization experience, and is a member of ACM, IEEE, INFORMS and INSTICC.

Decision Support Systems (DSS) are widely used to support organizational and personal decision-making in diverse areas such as engineering systems, finance, business, economics and public policy. They are becoming increasingly critical with the information overload from the Internet. While the scope of DSS is broad, Decision Guidance Systems (DGS) are a class of DSS geared to elicit knowledge from domain experts and provide actionable recommendations to human decision-makers, with the goal of arriving at the best possible course of action.
Currently, the practice of building Decision Guidance (DG) Systems resembles developing database applications decades ago before the invention of the relational Database Management Systems (DBMS). DG applications are typically one-off and hard-wired to specific problems; require significant interdisciplinary expertise to build; are highly complex and costly; and are not extensible, modifiable, or reusable. Therefore, a paradigm shift for the development of DG systems is needed. The key idea is to introduce and develop Decision Guidance Management Systems (DGMS), which would allow fast and easily-extensible development of DG applications, similar to easy development of DB applications using DBMS.
In this talk I will overview research toward this goal, including the recently developed Unity DGMS, and exemplify its use in the area of manufacturing, energy and power. I will also discuss ideas on how to use the emerging DGMS technology to translate the potential and multibillion dollar investment in Internet of Things (IoT) into business value, e.g., through (1) better predictability of demand and inventory visibility, (2) better tracking and efficiency of equipment and operating assets (3) accelerated innovation and product support, (4) improved alignment and collaboration among business functions and (5) sustainability and quality through visibility to energy and resource consumption.