The link of the event can be found here. Thursday June 25, 2020 16:00 – 17:00 (Greece) Predicting and Preparing for Disruptive Events Discussion around how disruptive events like COVID19
Thursday June 25, 2020
16:00 – 17:00 (Greece)
Predicting and Preparing for Disruptive Events
Discussion around how disruptive events like COVID19 can be anticipated and what design decisions need to be made in order to create resilient infrastructure
Moderator: Dora Varvarigou, Professor NTUA, Chairman BoD EYDAP S.A.
Theodora Varvarigou is a professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA). She received the B. Tech degree in Electrical Engineering from NTUA in 1988, the MS degrees in Electrical Engineering (1989) and in Computer Science (1991) from Stanford University, California.
She received her Ph.D. degree from Stanford University as well in 1991. She has worked as a researcher at AT&T Bell Labs, USA and as an Assistant Professor at the Technical University of Crete, Chania, Greece. Prof. Varvarigou has great experience in cutting edge technologies, such as Cloud computing, multimedia content processing, semantic web, social networking technologies etc.
She has published more than 200 papers in leading international journals, conferences and books. She has participated and co-ordinated numerous EC projects. From 2008-2012, she held the chair of the postgraduate program “Engineering Economic Systems” of NTUA. Since June 2019 she was elected as the Chairwoman of the Board of Directors of EYDAP.
|Speaker: Dimitris Bertsimas, Associate Dean of Business Analytics, Boeing Professor of Operations Research, MIT
Dimitris Bertsimas is the current Associate Dean of Business Analytics, Boeing Professor of Operations Research and faculty director of the Master of Business analytics at MIT. He received his SM and PhD in Applied Mathematics and Operations Research from MIT in 1987 and 1988 respectively. He has been MIT faculty since 1988. His research interests include optimization, machine learning and applied probability and their applications in health care, finance, operations management and transportation. He has co-authored more than 200 scientific papers and four graduate level textbooks.
He is the editor in Chief of INFORMS Journal of Optimization and former department editor in Optimization for Management Science and in Financial Engineering in Operations Research. He is also a member of the National Academy of Engineering since 2005, an INFORMS fellow, and have received numerous research awards including the Morse prize (2013), the Pierskalla award for best paper in health care (2013), the best paper award in Transportation (2013), the Farkas prize (2008), the Erlang prize (1996), the SIAM prize in optimization (1996), the Bodossaki prize (1998) and the Presidential Young Investigator award (1991-1996).
He has consulted widely in a variety of industries and has cofounded several very successful companies. In 1999, he co-founded Dynamic Ideas, LLC, which developed machine learning methods for asset management. In 2002, the assets of Dynamic Ideas were sold to American Express. From 2002-2010, he was the head of the quantitative asset management group of Ameriprise Financial, responsible for $12 billion of assets. In 2001, he cofounded D2 Hawkeye, a data mining health care company and responsible for its machine learning capabilities. The company was sold to Verisk Health in 2009. In 2011 he cofounded Benefits Science Technologies LLC, a company that designs health care benefits, Savvi Financial LLC, a financial advice company and Alpha Dynamics LLC, an asset management company. In 2015 he cofounded P2 Analytics LLC, a consulting company and in 2018 Interpretable AI, a machine learning company.
|Speaker: Saurabh Amin, Associate Professor, MIT
Saurabh Amin is Associate Professor in the Department of Civil and Environmental Engineering (CEE), Massachusetts Institute of Technology (MIT). He is also a member of the Laboratory for Information and Decision Systems and the Operations Research Center at MIT. His fields of expertise include stochastic control, game theory, and optimization in networks. His research focuses on the design and implementation of high confidence network control algorithms for infrastructure systems.
He works on robust diagnostics and control problems that involve using networked systems to facilitate the monitoring and control of large-scale critical infrastructures, including transportation, water, and energy distribution systems. He also studies the effect of security attacks and random faults on the survivability of networked systems, and designs incentive-compatible control mechanisms to reduce network risks. Dr. Amin received his Ph.D. in Systems Engineering from the University of California, Berkeley in 2011.
His research is supported by NSF CPS FORCES Frontiers project, NSF CAREER award, Google Faculty Research award, DoD-Science of Security Program, AFOSR, and Siebel Energy Institute. In 2020, he received the Ole Madsen mentoring award from MIT CEE in recognition of his conspicuous contributions to mentoring and educating students outside the classroom.
(Thursday) 4:00 pm - 5:00 pm GMT+3