Welcome! I'm Botan Ahmad, a Senior Data Scientist and ML Engineer specializing in Reinforcement Learning, Deep Learning, and algorithmic trading. I have extensive experience in building AI-driven solutions for various industries, including defense, finance, and space.
- 🔬 I focus on research and development in Reinforcement Learning, particularly applying cutting-edge algorithms to real-world problems like flight simulation and trading.
- 🌍 Based in Paris, France, with a background in computer science and data science from École Supérieure de Génie Informatique.
- 🏢 Currently working as an ML Engineer at Klark AI, deploying advanced AI systems across multiple customer platforms.
- 🚀 Co-founded Deepn, an algorithmic trading platform, where I developed a custom programming language called Flow to optimize trading strategies.
Here are some highlights from my public work:
A face recognition system leveraging deep learning techniques for identity verification. It employs cutting-edge computer vision and neural network approaches to ensure high accuracy and performance.
An in-memory NoSQL database designed for speed and flexibility. It provides efficient data management and retrieval, catering to use cases where traditional databases may be too slow or cumbersome.
A Dofus 1.29 emulator implemented in Java, allowing players to experience the classic MMORPG. The project is organized into login, game, and common modules, demonstrating skills in game development and server architecture.
A modern file manager for Linux, built with Kotlin and TornadoFX. It provides an intuitive interface and lightweight performance, making it suitable for users seeking a streamlined file management experience.
An event-driven asynchronous TCP network application based on Netty. Prototex is designed for real-time, bidirectional communication, with support for custom serialization, auto-reconnection, and a flexible packet registry. It emphasizes speed, security, and reliability across different platforms and devices.
- Programming Languages: Python, C++, Kotlin, Java, Rust, Matlab.
- Machine Learning & AI: Reinforcement Learning, Computer Vision, Transformers, AutoEncoders, RLlib, OpenAI Gym.
- Deep Learning Frameworks: PyTorch, TensorFlow.
- Big Data & Cloud Computing: AWS, GCP, Docker, Kubernetes, Apache Spark.
- Simulation & Embedded Systems: Unity, Unreal Engine, ROS.
- Master's in Data Science – École Supérieure de Génie Informatique (2022)
- Bachelor's in Computer Science – École Supérieure de Génie Informatique (2020)
- Actively conducting research on cutting-edge algorithms and techniques in Reinforcement Learning, staying updated with the latest advancements in the field.
- Achieved high rankings in Kaggle competitions, including the Cassava Leaf Disease Classification challenge, utilizing state-of-the-art models such as EfficientNet and Vision Transformers (ViT).
- Developed innovative solutions for flight simulation and algorithmic trading, integrating deep learning and RL techniques to solve complex, real-world problems.
I'm open to collaborating on projects involving:
- Reinforcement Learning applications in finance, robotics, or gaming.
- Deep Learning projects in computer vision or natural language processing.
- Open-source contributions related to AI research.