Quantitative Researcher | Bayesian Statistics | Financial Markets
Core Expertise:
- Bayesian statistical methods and uncertainty quantification
- Sequential learning algorithms and regime detection
- State space modeling and probabilistic inference
Hi there! I am currently a Quantitative Researcher at Brevan Howard, where I develop and implement statistical methodologies for financial markets.
I hold a PhD in Statistics from the London School of Economics, where I specialized in Sequential Bayesian Learning for State Space Models under the guidance of Kostas Kalogeropoulos and Pauline Barrieu. My doctoral research centered on developing methodologies for parameter estimation in dynamic systems, with particular emphasis on latent variable models and time-varying environments.
Beyond my professional work, I have contributed to open-source projects and share technical insights here. I am happy to engage with fellow quantitative professionals and researchers exploring innovative applications in financial markets..
Experience
Education
Skills
Bayesian Statistics, Parameter Estimation, Prediction
Markov Chain Monte Carlo, Sequential Monte Carlo, Variational Inference/Optimization
Latent Variable Models, State Space Models, Epidemic Models, Copula
Julia, R, Python
Linux, Distributed Computing, Version Control
Critical Thinking, Adaptability, Problem Solving
Oral (Teaching, Seminars, Conferences), Written (Papers, Editing, Blogging), Project Management (PhD Thesis), Teamwork (Collaborations)
