Services & Capabilities
Time series forecasting, machine learning, and statistical modeling — from theory to validated code
Time series & forecasting
My core domain. I currently work on multi-site forecasting of environmental sensor data (hourly series) as part of a research internship at INRS.
- Box–Jenkins methodology: SARIMA, SARIMAX with exogenous variables
- Long-memory and complex-cycle models (GARMA, FARIMA)
- Conditional heteroskedasticity (ARCH/GARCH)
- Rigorous backtesting: out-of-sample validation, model comparison
- Uncertainty analysis, residual diagnostics, interpretation
Machine learning & deep learning
Complete, reproducible, honest pipelines: a deep model earns its place only if it beats a solid statistical baseline.
- End-to-end pipelines: data, features, training, evaluation
- Neural networks for time series (TCN, convolutional architectures)
- Hyperparameter search and training on compute servers (HPC, Linux)
- Systematic comparison of statistical baselines vs deep learning
- Error analysis, model limitations, deployable demos (Streamlit)
Advanced statistical modeling
Mathematical tools for understanding the structure of data: dependence, frequency, variance.
- Dependence structures: copulas (theory and interactive implementation)
- Time-frequency analysis: wavelets
- Regression, exploratory analysis, dimensionality reduction
- Monte Carlo simulation
Algorithms & optimization
A solid theoretical foundation for correct, efficient implementations.
- Algorithm design and analysis, data structures
- Continuous and combinatorial optimization
- Numerical methods: numerical linear algebra, ODE/PDE solvers
- Complexity analysis, formal reasoning
Interactive scientific visualization
My signature: making mathematics visible. I write bilingual interactive articles with Manim-style animations — copulas, wavelets, GARCH, reinforcement learning.
- Animated educational articles (HTML/canvas, FR/EN)
- Interactive laboratories (e.g. live copula exploration)
- Rigorous, accessible explanations of advanced mathematical concepts
- Polished LaTeX reports and technical presentations
Scientific programming
- Python (NumPy, pandas, statsmodels, PyTorch, Streamlit)
- R (statistics, time series)
- MATLAB (numerical methods), C++ (performance)
- Git, Linux, remote computing (SSH, HPC servers), LaTeX
Work with me
What I can deliver, with a clear scope and verifiable results:
- Analysis and forecasting of your time series data (report + documented code)
- Demonstrable ML prototypes: baseline validated model demo
- Interactive visualizations to explain a concept or communicate results
- Tutoring in mathematics, probability, and statistics (university level)