معرفی
Prof. Vladimir Kaishev is a Professor of Actuarial Science at the Faculty of Actuarial Science and Insurance (FASI), Bayes Business School, City, University of London. He holds a PhD in Statistics and Information Theory from Moscow Technical University and has held visiting positions at Kyoto University, the University of Melbourne, and Heriot-Watt University. His research focuses on actuarial mathematics, risk theory, reinsurance modeling, and the application of spline functions in finance and insurance. He has supervised numerous PhD students and contributed to over 30 journal articles, conference papers, and software packages such as StMoMo and KSgeneral. His work includes advancements in ruin probability modeling, copula functions, and operational risk assessment, alongside consultancy roles for institutions like Swiss Reinsurance and the Bulgarian Actuarial Society. He is an Associate Editor of Economic Quality Control and a member of professional societies including the American Mathematical Society.
Education: MSc and PhD in Statistics from Moscow Technical University, followed by postdoctoral research at the University of Wisconsin-Madison and UCLA.
Research Interests: Multivariate Lévy processes, ruin theory, optimal reinsurance, spline functions, and stochastic modeling. His work bridges actuarial science with financial mathematics and statistical methods.
Publications: Over 40 peer-reviewed articles and book chapters, with recent focus on generalized linear models, survival analysis, and actuarial software development. His 2023 paper in Applied Mathematics and Computation introduced novel variable knot spline methods.
Awards: Received the Cass Business School Certificate for Excellence in Research in 2009 and 2013.
Consultancy & Grants: Projects include stochastic mortality modeling for the UK Office for National Statistics and economic scenario generator development for Aon-Benfield. His research has been supported by grants from the Leverhulme Trust and the Swiss Re.
Labs/Teams: Leads the Actuarial Research Center and collaborates internationally on projects such as the StMoMo R package for stochastic mortality modeling.
