Bridging the gap between theoretical AI research and practical applications
Master's student at ENS Paris-Saclay, I combine rigorous mathematical foundations with hands-on engineering expertise to push the boundaries of artificial intelligence. My research focuses on developing innovative AI solutions that address real-world challenges.
Specialized knowledge in AI, mathematics, and engineering
Deep learning, reinforcement learning, and neural networks with focus on theoretical foundations and practical implementations.
Analysis and modeling of chaotic dynamics, with expertise in reservoir computing and time series prediction.
Development of embedded systems and integration of AI algorithms with hardware components.
Experience in designing experiments, analyzing results, and publishing findings in academic contexts.
A selection of my most significant contributions to AI and engineering
Developed a scalable framework for audio processing achieving 98.95% compression while maintaining high signal quality. Reduced memory usage from 132GB to 4MB through innovative sparse coding techniques.
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Novel approach to chaos analysis using topological data analysis
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Interested in collaboration or have questions about my research?