Building applied ML systems from raw data to deployed models, with a research focus on offline reinforcement learning for clinical decision-making.
M.Sc. graduate in Fondements et Ingénierie de l'Information et de l'Image (F3I), Université Ferhat Abbas Sétif (2024–2026), following a B.Sc. in Computer Science from the same institution.
My work sits at the intersection of reinforcement learning and healthcare — using clinical time-series data to build models that support real decisions, not just benchmark scores. I care about the full pipeline: data engineering, model development, evaluation, and getting something into a usable form.
Currently seeking entry-level roles in Machine Learning Engineering, AI Engineering, or Applied Research.
| Category | Tools |
|---|---|
| Languages | Python · SQL |
| ML / DL Frameworks | PyTorch · TensorFlow · scikit-learn |
| Data | Pandas · NumPy |
| AI / NLP | LangChain · Hugging Face Transformers |
| Infrastructure | Git · REST APIs · Docker (learning) |
Learned a personalized insulin dosing policy from real ICU time-series data (MIMIC-III), using offline RL to avoid the risk of online exploration in a clinical setting.
- Built the full data pipeline: cohort extraction, state representation, and reward shaping from raw ICU records
- Framed dosing as a sequential decision problem rather than a single-step prediction
- Stack: Python · PyTorch · Offline RL
- Repository →
Multi-model system comparing Random Forest, SVM, Logistic Regression, and neural approaches for fire risk classification, backed by a real-time weather API and interactive risk maps.
- Compared model families head-to-head rather than committing to one algorithm upfront
- Shipped as a usable tool, not just a notebook — real-time API + map interface
- Stack: Python · scikit-learn · Flask
- Repository →
Information retrieval system built from scratch over arXiv papers — inverted indexing, Boolean (AND/OR) search, phrase and proximity search, and TF-IDF ranking.
- Implemented core IR algorithms directly rather than relying on a search library
- Stack: Python · NLP · Information Retrieval
- Repository →
- Fine-tuning open-source LLMs for domain-specific clinical applications
- Extending the offline RL work toward a full decision-support prototype
- Deploying trained models as production-ready APIs