About
A research practice built around rigorous models, clear arguments, and decision-useful explanation.
I work across statistical modeling, macro-financial risk, and institutional analysis, with an emphasis on making complex technical and policy questions legible without flattening them.
Working principle
The strongest research output is not just correct. It is structured enough to guide decisions, explain tradeoffs, and remain legible to serious readers outside one narrow specialty.
How The Work Is Organized
Methods & Modeling
2Work 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
9Essays and analysis on law, state formation, dissent, public policy, and historical institutional structure.
Profile
Practice, not just biography.
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