About
Bayesian statistics, risk modeling, and institutional analysis.
I work on Bayesian modeling, macro-financial risk, and institutional analysis.
Working principle
Good research should be usable: the method should be clear, the tradeoffs visible, and the claims proportionate to the evidence.
How The Work Is Organized
Methods & Modeling
3Work centered on Bayesian methods, inference, modeling assumptions, and technical statistical structure.
Risk & Macroeconomics
2Research on macroeconomic vulnerability, actuarial design, risk transfer, tail behavior, and markets.
Law, Policy & History
12Essays and analysis on law, state formation, dissent, public policy, and historical institutional structure.
Profile
Background and work.
I am a Ph. D. student in Probability and Statistics at George Mason University (2025–2029), working across stochastic processes, stochastic differential equations, statistical machine learning, and Bayesian modelling. Previously, I completed an M.Sc. in Stochastics and Data Science at the University of Turin (2021–2024). My training includes functional analysis, probability, Bayesian statistics, stochastic modelling, statistical ML, stochastic differential equations, databases, algorithms, and additional coursework in option pricing and mathematical economics.
My thesis focused on Bayesian non-parametrics, using the Dependent Dirichlet Process to model and predict crisis probabilities in an economy. Professionally, I have built and optimized actuarial pricing and reserving workflows for FIA/MYGA products using GGY AXIS, along with Python-based diagnostics and scenario tooling.
Selected Experience
Roles that shaped the work.
Assistant Manager
Hildene Capital Management, LLC • Gurugram, India
Actuarial Intern
KPMG • Milan, Italy
Actuarial Analyst
Metlife • Noida, India