Human-centric & Data-driven
Decision Models | Risk Analysis | Network Resilience
Hesam Talebiyan, Ph.D.
Born and raised in Iran, I have developed a passion for employing mathematical tools and engineering insights to solve decision-making problems
in the real world. In my Ph.D. years at Rice University, I focused on modeling the decentralized nature of the decision-making process across
real-world interdependent networks such as civil infrastructure systems. Before landing at Rice, I earned a bachelor’s degree in
Civil Engineering and a master’s in Earthquake Engineering from the Sharif University of Technology. My master’s thesis is on the optimal decisions
regarding the prioritization of buildings for retrofit by minimizing the risk of the entire portfolio.
I have employed various mathematical tools, including discrete optimization techniques, machine learning methods, hierarchical statistical models, and game-theoretic concepts such as auctions and Bayesian games.
A primary element of my work has been the design of probabilistic algorithms that mimic the complexities of real-world interactions
such as socio-technical feedback loops. Another important aspect has been to make my research available to stakeholders through software development
(Rt, IN-CORE).
I am currently a Data Scientist and Emerging Risks Modeler at Moody's. In this role, I develop, validate, and
quantify the uncertainty of different models that estimate the unconventional risks to the insurers' and reinsurers' portfolios due to
natural and man-made catastrophes. I have recently joined the modeling team that develops risk assessment solutions regarding cybersecurity threats.
April, 11, 2024 New Journal Paper!
Interdependent network restoration games with incomplete information and bounded rationality [link]
Hesam Talebiyan, Leonardo Dueñas-Osorio
Risk Analysis