Summary
AI Research Scientist with a PhD in Computer Science and Applied Mathematics from Paris-Saclay University. Passionate about machine learning, deep learning, and optimization. I’d like to use my knowledge to help improve the world.
Experience
AI Research Scientist
- Designed and implemented a non-euclidean optimizer for non-smooth optimization problems called MELMO. The work has been submitted for publication in a top-tier journal.
- Research on the integration of ML methods in metaheuristics to solve combinatorial optimization problems.
Doctoral Researcher
- Designed and implemented a delivery fleet simulator for vehicle routing with emission constraints.
- Developed and evaluated hybrid methods combining OR heuristics and reinforcement learning.
- Built reproducible Python pipelines with visualization and experiment tracking.
- Assisted teaching in CS courses; mentored students on Python and algorithms.
Research Intern
- Prototyped multi-agent reinforcement learning approaches for real-time power grid control.
- Collaborated with research engineers to define environments, metrics, and baselines.
Research Intern
- Studied multi-agent reinforcement learning policies in modeled labor markets with game-theoretic structure.
Education
PhD, Computer Science & Mathematics
- Subject: Algorithms hybridizing AI and OR for supply-chain impact management.
- Supervisors: Prof. Dominique Barth and Dr. Yann Strozecki.
Master, Mathematics and Artificial Intelligence
Bachelor, Mathematics and Computer Science
Skills
Programming
- Python (PyTorch, JAX, scikit-learn, visualization)
- Julia
- C/C++
- SQL
- git
Machine Learning
- Reinforcement learning
- Supervised learning
- NLP/LLM
- RAG
Optimization
- Mathematical optimization
- Operations Research
- Metaheuristics
Computer Science
- Algorithms
- Data structures
- Parallel computing
- Databases
- Cloud computing (AWS, GCP basics)
Languages
- Persian (Native)
- French (Bilingual)
- English (Bilingual)
- Chinese (HSK3: Basic)
- Spanish (Basic)