AQFC2015

On Reliable Quantification and Mitigation of Extremal Risks

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    Department of Systems Engineering and Engineering Management

                       The Chinese University of Hong Kong

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Date: Friday, Dec 16, 4:30 pm – 5:30 pm

Venue: ERB 513, The Chinese University of Hong Kong

Title: On Reliable Quantification and Mitigation of Extremal Risks

Speaker: Prof. Henry Lam, Department of Industrial Engineering and Operations Research, Columbia University

 

Abstract:

Model-based quantification of extremal risks often involves asymptotic analysis or carefully designed computation schemes to speed up naive Monte Carlo. While these approaches have shown to be powerful in many problems, they could face challenges in attaining reliable guarantees when informing decisions or integrating with data. We discuss some of these challenges and possible remedies, touching upon the interplay of rare-event and extremal bound computation with optimization, input calibration uncertainty and statistical learning theory.

Biography:

Henry Lam is an Associate Professor in the Department of Industrial Engineering and Operations Research at Columbia University. His research interests include uncertainty quantification, data-driven optimization, rare-event and risk analysis, and Monte Carlo methods. His works have been recognized by several venues such as the NSF CAREER Award, NSA Young Investigator Award, JP Morgan Chase Faculty Research Award and Adobe Faculty Research Award. Henry serves on the editorial boards of Operations Research, INFORMS Journal on Computing, Applied Probability Journals, Stochastic Models, Manufacturing and Service Operations Management, and Queueing Systems, and as the Area Editor in Stochastic Models and Data Science in Operations Research Letters. He holds a PhD degree in statistics from Harvard University and BS degree in actuarial science from the University of Hong Kong.

Everyone is welcome to attend the talk!

SEEM-5201 Website: http://seminar.se.cuhk.edu.hk

Email: seem5201@se.cuhk.edu.hk

Date: 
Friday, December 16, 2022 - 16:30 to 17:30