Abstract:

 

Dr. Alex Shkolnik obtained his Ph.D. in Computational Mathematics & Engineering from Stanford University in 2015. His thesis work centered on computational methods for models used in the quantification and management of credit risk. Alex's expertise lies in transform and Monte Carlo methods for the estimation and prediction of these risks. In particular, his ongoing focus is on the development of importance sampling techniques for complex systems encountered in finance and other research areas. Before Joining UCSB as an assistant professor, Alex was a postdoctoral scholar at the Center for Risk Management Research and the Department of Statistics at UC, Berkeley. There, his research concentrates on building models for financial markets like Repo and CDS and applying modern statistical data analysis tools to identify risk factors in global equity markets.

 

 

Dr. Michael Ludkovski is the Department Chair of the Department of Statistics and Applied Probability at UCSB. His group broadly works on numerical and control methodologies inspired by applications in quantitative finance and insurance. A particular focus is the interface between machine learning and probabilistic techniques, cross-cutting across Financial Mathematics, Actuarial Science, Applied Probability, Operations Research and Data Science communities.

 

 

Dr. Nils-Christian Detering is a tenure track assistant professor in Financial Mathematics and Probability at the University of California, Santa Barbara (UCSB). His research is mainly on asymptotic methods (large number of market participants/financial institutions) to analyse systemic risk in the financial system, often facilitating random graphs. Additional research interests are in infinite dimensional stochastic analysis and its applications to the modelling electricity markets.