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Tutorials: Abstracts and Speakers Bio

1. Name of Speaker: Rene van Dorp

Affiliation: George Washington University, Washington, DC Email or other contact info:dorpjr@gwu.edu

Brief bio: J. Rene van Dorp has been exposed to multiple projects assisting organizations in making structured decisions involving complex systems, specializing in risk and reliability problems. General themes have been the development of formal methods integrating expert judgment, distribution theory, available data and Monte Carlo methods. His responsibilities ranged from organizing and overseeing data analysis efforts; developing, validating and integrating various mathematical/statistical models to creating presentations/reports

describing technical findings in ways for both experts and lay persons. The success of these projects depended to a large extent on the successful integration and coordination of the work of a team of analysts/researchers. Research domains of special interest to J. Rene van Dorp include Maritime Risk Management Analysis, Probabilistic Risk Assessment,

Reliability Analysis, Uncertainty Analysis, Health Care Management Science and Distribution Theory.

Title of the course: Introduction to Decision Analysis

Description of the course: The domain of decision making under uncertainty shall be introduced interactively by presenting the participants with a variety of decision problems involving coin-toss examples. Any decision analysis involves the construction of a model as an abstraction of reality. By drawing analogies between these coin-toss examples and the practical decision context in the field of maritime risk management the importance is presented of: (1) making reasonable assumptions rather than worst case assumptions,

(2) identifying the fundamental objective(s), (3) how to evaluate the objectives and

(4) developing an attractive graphical means to communicate the analysis results. During the second part of the course, we introduce influence diagrams and decision trees as two visual means to organize the identified elements of decision problems (i.e. values and objectives, decisions, uncertain events and consequences) in a single graphical representation.

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2. Name of Speaker: Refik Soyer

Affiliation: George Washington University, Washington, DC Email or other contact info:soyer@gwu.edu

Brief bio: Refik Soyer is Professor of Decision Sciences and of Statistics at the George Washington University (GWU). He is the Mitch Blaser Distinguished Scholar in Business Analytics. He also serves as the director of the Institute for Integrating Statistics in Decision Sciences at GWU. His area of interests are Bayesian statistics and decision analysis,

stochastic modeling, statistical aspects of reliability analysis, and time series analysis. He has published over 110 articles and has co-edited a volume titled Mathematical Reliability: An Expository Perspective. Soyer is an elected member of the International Statistical Institute, Fellow of the Turkish Statistical Association and a Fellow of the American Statistical Association. He was a vice president of the International Association for Statistical Computing. He served on the editorial board of the Journal of the American Statistical Association and is currently an associate editor of the Applied Stochastic Models in Business and Industry.

Title of the course: Decision Analysis in Reliability

Description of the course: In this course we consider decision problems that arise in reliability analysis and discuss how these problems can be represented in a decision theoretic framework and how they can be solved using decision analysis methods. Our discussion will consider both single-stage and multi stage decision problems as well as use of computational methods for solution including Monte Carlo techniques. Decision problems will include optimal replacement strategies, design of life tests, optimal stopping as well as recent work in adversarial life testing.

3. Name of Speaker: David Rios Insua Affiliation: ICMAT-CSIC, Madrid, Spain Email or other contact info: david.rios@icmat.es

Brief bio: David Rios is AXA-ICMAT Chair in Adversarial Risk Analysis at the Institute of Mathematical Sciences of the CSIC. He is member of the Royal Academy of Sciences in Spain. He has 13 books and more than 110 papers in his areas of interest which include decision analysis, negotiation analysis, risk analysis and Bayesian statistics, and applications to security, cybersecurity, social robotics and aviation. He is scientific advisor of Aisoy Robotics.

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Title of the course: Introduction to Game Theory

Description of the course: We provide an introduction and critical assessment of basic concepts in game theory, with a hint to computational issues and applications to security and social robotics.

 Games and Decisions: Basic Concepts. Multi-agent influence diagrams.  Games in Normal Form. Nash equilibria.

 Games in Extensive Form. Subgame perfect equilibria.  Games of Incomplete Information. Bayes-Nash equilibria.  A critical assessment.

 Bayesian approaches to non-cooperative games.  Bargaining.

4. Name of Speaker: Fabrizio Ruggeri Affiliation: CNR IMATI, Milano, Italy

Email or other contact info: fabrizio@mi.imati.cnr.it

Brief bio: Fabrizio Ruggeri is Research Director at CNR-IMATI, Milano, Italy, and Adjunct Professor at Queensland University of Technology, Brisbane, Australia. His research interests include Bayesian and industrial statistics. He is a former President of the European Network for Business and Industrial Statistics (ENBIS) and of the International Society for Bayesian Analysis (ISBA). He is author of over 100 research articles, four books and Editor-in-Chief of Applied Stochastic Models in Business and Industry and Wiley StatsRef. He is Fellow of the American Statistical Association and ISBA, and recipient of the Zellner Medal awarded by ISBA.

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Title of the course: Reliability

Description of the course: The short course will introduce the basic notions in reliability and will focus mostly on repairable system, illustrating case studies representative of modeling, inference (mostly Bayesian) and decision, namely gas escapes in a city network, doors' failures in subway trains and software reliability.

5. Name of Speaker: David Banks

Affiliation: Duke University, Durham, NC

Email or other contact info: banks@stat.duke.edu

Brief bio: David Banks is Professor at the Department of Statistics, Duke University. He was the coordinating editor of the Journal of the American Statistical Association (ASA) and founded the journal Statistics and Public Policy and served as its editor. He co-founded the ASA Section on National Defense and Homeland Security, and has chaired that section, as well as the sections on Risk Analysis and on Statistical Learning and Data

Mining. At SAMSI he led research programs on Data Mining (2003) and Computational Advertising (2012). He has published 74 refereed articles, edited eight books, and written four monographs. David Banks is past-president of the Classification Society and current president of the International Society for Business and Industrial Statistics. He is a fellow of ASA and Institute of Mathematical Statistics. He recently won the ASA Founders Award. His research areas include models for dynamic networks, dynamic text networks,

adversarial risk analysis (i.e., Bayesian behavioral game theory), human rights statistics, agent-based models, forensics, and certain topics in high-dimensional data analysis.

Title of the course: Adversarial Risk Analysis

Description of the course: National security problems pose special challenges for classical statistical risk analysis. First, there is the problem of accounting for adversarial decision-making: game theory does a poor job of describing human behavior, but standard probabilistic risk analysis is inadequate in modeling malicious strategizing. A second problem concerns the elicitation of expert judgment. In national security, the problems are astonishingly complex and there may not be any expert who has the full domain knowledge that is needed (on top of the usual difficulties of expert over-confidence, anchoring bias, and so forth). A third problem is the pervasive use of complex computer models (BTRA, HAZUS-MH) as risk management tools, and the difficulty that arises in validating their outputs and attaching appropriate uncertainties to them. This short course describes the current state of the statistical art in addressing these issues.

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6. Name of Speakers: Thomas A. Mazzuchi and Jason Merrick

Affiliation: George Washington University, Washington, DC and Virginia Commonwealth University, Richmond, VA

Email or other contact info: mazzu@gwu.edu and jrmerric@vcu.edu Brief bio:

Dr. Thomas A. Mazzuchi received a B.A. (1978) in Mathematics from Gettysburg College, Gettysburg, PA, a M.S. (1979) and a D.Sc. (1982), both in Operations Research from the George Washington University, Washington DC. Currently, he is a Professor and Chair of Engineering Management and Systems Engineering in the School of Engineering and Applied Science at the George Washington University, Washington, D.C. Dr. Mazzuchi’s current research interests include systems engineering processes, risk analysis, reliability growth assessment, software reliability modeling, design and inference in life testing, reliability estimation as a function of operating environment, maintenance inspection policies, and incorporation of expert judgment into reliability and risk analysis and systems engineering methodologies.

Jason R. W. Merrick’s research is primarily in the area of decision analysis, risk analysis, and simulation. He has worked on projects ranging from assessing maritime oil

transportation and ferry system safety, the environmental health of watersheds, and counter- terrorism and received grants from the National Science Foundation, the Federal Aviation Administration, the United States Coast Guard, the American Bureau of Shipping, British Petroleum, Booz Allen Hamilton, and the Makah Tribal Council, amongst others. He is President-Elect of the Decision Analysis Society and an associate editor for the INFORMS journal Decision Analysis, the Euro Journal on Decision Processes, and IIE Transactions, and formerly at Operations Research and Transactions on Modeling and Computer Simulation. Jason is a professor in the Department of Supply Chain Management & Analytics in VCU’s School of Business with a joint appointment in the Department of Statistical Sciences and Operations Research. He has bachelors in mathematics and computation from Oxford University and a doctorate in operations research from George Washington University.

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Title of the course: Risk in engineering, finance, health, and environmental sciences

Description of the course: This will be a short course intended to introduce students to the exciting field of Risk Analysis. We will begin with an overview several diverse application areas and then discuss in tern the main phases of a risk analysis namely, problem formulation, data gathering, various quantitative and qualitative modeling techniques, the use of objective and subjective data for populating the models, and developing an presenting findings from the risk analysis.

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