I’m a Machine Learning Engineer / Data Scientist with a strong mathematical background and passion for building models that not only fit, but explain.
My focus lies at the intersection of probabilistic modeling, time series forecasting, and statistical inference.
- Stochastic Processes – Poisson, Wiener, Brownian motion, Gaussian processes
- Time Series Analysis – ARIMA, HMMs, spectral methods, Kalman filtering
- Bayesian Inference & Statistical Learning – MCMC, variational inference, hypothesis testing
- Model Selection & Hyperparameter Optimization – Bayesian optimization, grid/random search, CV
- Machine Learning Engineering – pipelines, reproducibility, deployment
I enjoy designing interpretable models, simulating complex dynamics, and squeezing insight from noisy data.
