🧠 AI Research · ENS Paris-Saclay (MVA) & CentraleSupélec Generative Models · Representation Learning ⚙️
MSc in Mathematics, Vision & Learning (MVA) with a background in applied mathematics and data science.
I work on generative models and representation learning, with a bias toward building systems that actually run; clean experiments, reproducible pipelines, honest benchmarks.
Currently finishing my master's and looking for Applied Scientist / Research Engineering roles in foundation models or generative AI 🚀
Replacing IID Gaussian noise with structured processes (Simplex, Matérn, rank-based Gaussianization) to control denoising difficulty and improve anomaly separability.
Building principled diagnostics to understand why noise geometry shifts AUROC — not just that it does.
Probing internal feature geometry in Transformers and GNNs via t-SNE, PPCA, KL trajectories.
Interested in when and how representations become interpretable across layers.
| Project | Core idea |
|---|---|
| 🦷 Structured-noise diffusion for anomaly detection | Simplex/Matérn noise → +11.6% detection on CBCT dental pathology; validated on brain MRI |
| 🔍 GPT-2 interpretability: Tuned Lens vs Logit Lens | KL trajectory analysis for prompt injection detection; Tuned Lens consistently more stable |
| ♟ GRPO fine-tuning on Ministral-3B | 4-stage curriculum (Mate-in-1 → Full Game) to stabilize sparse-reward RL for chess |
| 🧾 Knowledge distillation: Qwen2.5 14B → 1.5B | TF-IDF + NMF corpus curation + LoRA distillation for Arabic summarization |
| 📊 GPU-accelerated PPCA with missing data | Fully vectorized EM loop; benchmarked against PCA/mini-batch variants at scale |
| 📈 Online NMF for financial time series | Sliding-window factorization with stabilized dictionary evolution |
Frameworks: PyTorch · PyTorch Lightning · MONAI · Transformers · vLLM · PyG
Training: LoRA/QLoRA · DDP · Slurm · CUDA profiling · gradient checkpointing
Math: variational inference · ELBO · spectral methods · optimal transport
Finishing my MVA master's.
Actively looking for research engineering or applied scientist roles focused on:
- 🏗 Foundation models
- 🎨 Generative modeling
- 🔎 Interpretability
📎 LinkedIn: https://linkedin.com/in/omararbi