I’m a Lebanese engineer studying data science at École Polytechnique × HEC Paris. I build machine learning systems and study how they behave on messy, real data.
My work sits between statistical learning, software engineering, and financial data.
I build and compare LightGBM, Ridge, and ElasticNet models, using cross-sectional features and time-series splits to keep future information out of training.
Explore the modeling projectsAt Murex, I worked on AI workflow prototypes in n8n before we moved to LangChain. I also worked on applied AI systems at Gaya.ai.
The engineering experienceBinomial lattices, risk-neutral option pricing, and convergence checks against Black–Scholes. I check how pricing error changes as the lattice resolution increases.
Read the pricing projectCross-sectional equity ranking, momentum portfolios, and volatility targeting. I test the resulting portfolios with exposure constraints and drawdown diagnostics.
Explore the researchI studied Computer & Communications Engineering at the American University of Beirut, graduating with High Distinction and a 4.0 GPA. I’m now in the first year of the Data Science & AI for Business MSc&T at École Polytechnique and HEC Paris.
I enjoy the whole research process: turning a question into an experiment, checking the assumptions, and understanding why a model succeeds or fails. Financial data gives me plenty of difficult questions to work on.
A couple of lines I keep coming back to: “This is the Way.” The Mandalorian and “Do or do not. There is no try.” Yoda
Where I studied, worked, and what I learned along the way.
Joining a Delta One pod to work on quantitative research, datasets, and research tooling.
Currently in M1, studying statistical learning, machine learning, and mathematics. Admitted with a scholarship.
Graduated in Computer & Communications Engineering with High Distinction and a 4.0/4.0 GPA. I also spent a lot of time tutoring engineering students.
Worked on applied AI systems, including workflow prototypes with n8n and a later move to LangChain at Murex.
Building a better tutoring experience for engineering students, from the content to the platform.
Presenting our workflow back when we were still using n8n. We later moved to LangChain.
Selected projects in machine learning, numerical methods, and financial data.
Predicting next-day residual equity returns with leakage-aware features, cross-sectional ranks, and an ensemble of models.
From momentum and volatility features to cross-sectional predictions, portfolio construction, information coefficients, and a reproducible backtest.
European and American option pricing with a risk-neutral binomial lattice, backward induction, and Black–Scholes convergence checks.
A momentum portfolio with volatility targeting, exposure constraints, and drawdown diagnostics across historical US equities.
A small random-walk experiment: change the bias, run a few paths, and compare the average with E[Sₙ] = n(2p − 1).
Story-heavy RPGs, great worlds, shooters, and racing games. If the writing, soundtrack, or mechanics are good, I'm probably interested.
Gym sessions, fitness classes, and a break from my desk.
Existentialism, Russian classics, French literature, and ambitious fantasy. I enjoy a book that stays with me after I put it down.
Building things, just for fun.
Young Miko, Omar Courtz, and occasionally some classical music.
Arabic, English, French, Spanish.
Travel, new places, art, photography, and finding the good cafés.
Four years of tutoring engineering students, plus collaborative projects and campus experiences at AUB.
Travel photos, favorite albums, a few milestones, and some things about me that did not fit on a CV.
Have a research question, a project in mind, or a book I should read? I’d love to hear from you. I’m always happy to talk ML, compare favorite games, or meet someone new.
stefanie.samaha@polytechnique.eduOr browse the code on GitHub.
