About me
I’m a researcher and instructor in Quantitative Finance, Programming, and Machine Learning / AI applied to Finance and Business. I hold a Doctorate in Quantitative Finance, where I explored market antifragility modeling through machine learning and mathematical methods.
My commitment to academia is driven by a deep passion for applying science, mathematics, and technology to address real-world problems; particularly in finance. I thrive on transforming complex concepts into accessible, engaging learning experiences through project-based teaching.
In my higher education teaching experience, I have taught Bachelor’s and Master’s-level courses such as:
Financial Modeling
Python and Data Analysis for Finance
Machine Learning and AI for Finance and Marketing
Mathematical modules including Differential Equations, Time Series Analysis, and Stochastic Processes
I aim not only to help students build knowledge and confidence to apply quantitative tools in real-world contexts, but also to bridge academia and industry through practical, data-driven learning.
My professional background includes positions at Natixis and Nexus Horizon, where I contributed to projects ranging from security management to quantitative research. Across both teaching and industry work, I emphasize applied problem-solving using real financial data to connect theory, modeling, and practice.