Bilal M. Ayyub
Personal Information
Description
Bilal M. Ayyub is a Professor of Civil and Environmental Engineering and the Director of Center for Technology and Systems Management at the University of Maryland, College Park, and was a visiting fellow at the National Security Analysis Department of the Applied Physics Laboratory in 2015-16. He was a chair professor at Tongji University, Shanghai, China (2016-18). Dr. Ayyub’s main research interests and work are in risk, resilience, sustainability, uncertainty and decision analysis, applied to civil, infrastructure, energy including renewables, defense and maritime fields and climate-resilient infrastructure. Professor Ayyub is a distinguished member of ASCE and an honorary member of ASME. He is also a fellow of the Society of Naval Architects and Marine Engineers (SNAME), the Structural Engineering Institute (SEI), and the Society for Risk Analysis (2017-18 Treasurer), and a senior member of the Institute of Electrical and Electronics Engineers (IEEE). Dr. Ayyub completed research and development projects for governmental and private entities including NSF, DOD, DOT, NIST, DHS, and leading insurance and multinational corporations worldwide. Dr. Ayyub is the recipient of several awards, most recently the 2018 ASCE Alfredo Ang Award on risk analysis and management of civil infrastructure, 2019 ASCE President Medal for many efforts to bring adaptive design to the profession to help address a changing climate, 2019 ASCE Le Val Lund Award for contributions to resilience enhancement and risk reduction for lifeline-networked systems through measurement science and associated economics toward informing policy and decision-making practices, 2018 ENR Newsmaker award for passionate effort to give engineers their first formal guidance when designing infrastructure to be more resilient to weather extremes, and 2016 ASNE Solberg Award significant engineering research and development accomplishments in the field of ship survivability. He is the author and co-author of more than 650 publications in journals, conference proceedings, and reports and the editor-in-chief of the ASCE-ASME Journal on Risk and Uncertainty in Engineering Systems in its two parts on civil and mechanical engineering. In addition to 15 edited books, his eight textbooks include the following: Uncertainty Modeling and Analysis for Engineers and Scientists (Chapman & Hall/CRC 2006 with G. Klir), Risk Analysis in Engineering and Economics (Chapman & Hall/CRC 2003, 2014), Elicitation of Expert Opinions for Uncertainty and Risks (CRC Press 2002), Probability, Statistics and Reliability for Engineers and Scientists, Third Edition (Chapman & Hall/CRC 2011 with R. H. McCuen), and Numerical Methods for Engineers (Prentice Hall 1996 with McCuen, 2nd edition Chapman & Hall/CRC 2016).
Books
Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach
Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach examines the use of newly developed analytical tools for studying uncertainty analysis in engineering, control systems, and the sciences. It is the work of 38 experts who have written chapters on newly developed analytical methods - fuzzy logic, neural networks, simulation, and Bayesian techniques - and have applied them to uncertainty phenomena arising out of information and knowledge problems in the fields of engineering and the sciences. The book is divided into the following parts: Part I reports the theoretical studies on uncertainty types, models and measures; Part II reviews the applications of uncertain theoretical tools to engineering systems; Part III describes the methodologies of fuzzy-neural data analysis and forecasting; Part IV presents two chapters on fuzzy-neuro systems; and Part V describes the methodologies for fuzzy decision making and optimization and their computational methods. The Editors provide a concluding chapter on uncertainty and uncertainty modeling. This is a carefully developed book that treats the topic of uncertainty from fresh perspectives and in depth.