Beer, Michael - University of Liverpool

个人简介

Dr. Beer joined the School of Engineering as a Professor in the Centre for Engineering Sustainability in July 2011 and became the founding Director of the Institute for Risk & Uncertainty in 2012. Since 2014 he is the Academic Director of the EPSRC and ESRC Centre for Doctoral Training in Quantification and Management of Risk & Uncertainty in Complex Systems & Environments. Dr. Beer graduated with a Masters degree (Dipl.-Ing., 1995) and with a Doctoral degree (Dr.-Ing., 2001) in Civil Engineering from the Technische Universität Dresden (TU Dresden), Germany, and received awards for excellence in both qualifications. He pursued research in several projects as a Research and Teaching Associate and as Principal Investigator at the Institute for Statics and Dynamics, TU Dresden until 2007. As a Feodor-Lynen Fellow of the Alexander von Humboldt-Foundation Dr. Beer went to Rice University as a Visiting Scholar for research collaboration with Professor Pol D. Spanos in 2003/2004. From 2007 to 2011 he was affiliated as an Assistant Professor to the Department of Civil & Environmental Engineering, National University of Singapore and contributed, in particular, to the research in the Centre for Hazards Research and in the Centre for Offshore Research and Engineering. Dr. Beer has continuously led various research projects with focus on both theoretical developments and applications. He is partner and leader for large-scale research programs with a multi-million grant volume. His research is focused on both stochastic and non-traditional uncertainty models in engineering with emphasis on reliability analysis, risk analysis and robust design. In the Centre for Engineering Sustainability this is utilised to address engineering challenges arising from environmental changes with a multi-disciplinary view. ASCE Certificate of Appreciation (ASCE CDRM 2014) Computational Intelligence in Structural Analysis and Design (Keynote Speech, IEEE 2013) Uncertainty quantification: selected approaches (Keynote Speech, APCOM 2013) Generalized models for uncertainty and imprecision in engineering (Keynote Speech, Opening Keynote Lecture - Professor Miroslav Vorechovsky 2012) Imprecise Probabilities in Engineering Systems and Structures (Keynote Speech, Plenary Lecture - ASME 2011) Fuzzy Data and Imprecise Probabilities in Engineering (Invitation to Speak, Invited Lecture - ISI 2011) Non-traditional Prospects in the Simultaneous Treatment of Uncertainty and Imprecision (Invitation to Speak, Invited Special Lecture - Professor B.H.V. Topping 2009) CADLM PRIZE 2007 - Intelligent Optimal Design (CADLM France 2007) Feodor-Lynen Research Fellowship (Competitive Fellowship, Alexander von Humboldt-Foundation 2003) Kurt Beyer Award 2001 (Dresden U of Technology & HOCHTIEF Construction AG, Germany 2002) Wilhelm Gotthelf Lohrmann Medal 1995 (Dresden University of Technology, Germany 1995) Director, Institute for Risk & Uncertainty Academic Director, EPSRC and ESRC Centre for Doctoral Training in Quantification and Management of Risk & Uncertainty in Complex Systems & Environments

研究领域

Non-traditional Uncertainty Modeling, Simulation Techniques for Processing Uncertainty, Reliability, Risk and Hazard Analysis, Robust Design

近期论文

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Multiple response surfaces method with advanced classification of samples for structural failure function fitting An approximate stochastic dynamics approach for nonlinear structural system performance-based multi-objective optimum design Approximate fuzzy analysis of linear structural systems applying intervening variables Compressive sensing based stochastic process power spectrum estimation subject to missing data Imprecise system reliability and component importance based on survival signature Learning from major accidents to improve system design Nonlinear MDOF system Survival Probability Determination Subject to Evolutionary Stochastic Excitation Reliability Analysis of Complex Systems with Uncertainties by Monte Carlo Simulation Method Robust vulnerability analysis of nuclear facilities subject to external hazards Why Modified exponential covariance kernel is empirically successful: A theoretical explanation. A Clustering Approach to a Major-Accident Data Set: Analysis of Key Interactions to Minimise Human Errors A computational tool for Bayesian networks enhanced with reliability methods A nonlinear model of failure function for reliability analysis of RC frame columns with tension failure Advanced Line Sampling for efficient robust reliability analysis An artificial neural network approach for stochastic process power spectrum estimation subject to missing data. Analysis of a major-accident dataset by Association Rule Mining to minimise unsafe interfaces Communicating risk in major incidents: The public's perception Comparative studies on assessment of corrosion rates in pipelines as semi-probabilistic and fully stochastic values Compressive Sensing for power spectrum estimation of multi-dimensional processes under missing data Editorial: Engineering analysis with vague and imprecise information Enhanced Bayesian Network approach to sea wave overtopping hazard quantification Enhanced Bayesian Networks approach to risk assessment of spent fuel ponds Human error analysis: Review of past accidents and implications for improving robustness of system design Human factors and quality control procedures: An example from the offshore oil & gas industry Learning from accidents: Analysis and representation of human errors in multi-attribute events