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New Co-Editor-in-Chief Risk and Decision Analysis

September 19, 2014
Amsterdam, NL – Professor Nassim Nicholas Taleb has recently been announced as new Co-Editor-in-Chief of Risk and Decision Analysis, a journal about risk mathematics, risk modeling and management, published by IOS Press.

“I am extremely proud to partake in this journal, which aims to inject real-world rigor into risk theories, and help develop an atmosphere of substance in risk management. Risk is the most important topic there is – everything depends on it – and we need to help authors who focus on rigorous relevance to find a publishing venue.”, says the newly appointed Co-Editor-in-Chief.

Professors Alain Bensoussan and Charles Tapiero welcome Professor Taleb to their editorial team: “Professor Taleb is one of the most prolific researchers in Extreme Risks and their many manifestations. We’re very glad that the author of Black Swan and Anti-Fragility is joining us in our efforts.”

ABOUT PROF. NASSIM NICHOLAS TALEB
Professor Taleb has a background in complex derivatives and risk management of nonlinear payoffs. He was a trader for 21 years before becoming a full-time researcher.

Currently, Professor Taleb holds a position as Distinguished Professor of Risk Engineering at New York University’s School of Engineering. For more information, see www.fooledbyrandomness.com.

ABOUT THE JOURNAL
The journal Risk and Decision Analysis (RDA) emphasizes a theoretical and practical interdisciplinary vision of risk and its manifestations. RDA considers for publication research paper papers that contribute to a greater appreciation of risk mathematics, risk modeling and management and their broad application to general engineering, economic and financial systems, operational systems in industry and in the services, regulatory and control systems, eco-risks and urban systems, insurance, energy, safety and security, healthcare, environment, and related areas.

RDA’s focus is on mathematical and systematic approaches to risk (statistics, probability theory), Bayesian statistics and learning, stochastic modeling, stochastic and optimal control in addition to quantitative approaches to extreme risks and their management.