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Visiting Researcher

University of Maryland, College Park

Conducting research on NTK Theory to answer the fundamental question - Deeper or Wider. Making original research contributions to the field.

• Neural Tangent Kernel Theory
• Deep Learning Theory

Research Intern

AI-Vidency

Working on causality and explainable AI to analyze massive datasets. Developing a new math library for hierarchical causal modelling and inference.

• Causal Inference
• Explainable AI
• Hierarchical Causal Models

Mathematics Formalizer

Lean Community

Contributing to formal mathematics verification using the Lean theorem prover, formalizing mathematical theorems and proofs in algebraic geometry, group theory, and topology.

• Formal Proof Verification
• Mathematical Theorem Formalization
• Lean 4 Development

Proof Contributor

Metamath Community

Contributing formal mathematical proofs to the Metamath database, focusing on foundational mathematics, set theory, and algebraic structures.

• Formal Mathematical Proofs
• Set Theory Formalization
• Mathematical Foundations

Contributor

Open Source Mathematics

Contributing to open source mathematical libraries and research projects, particularly in causal inference and machine learning.

• Hierarchical Causal Models Library
• Mathematical Research Tools

Master's degree

ENS Paris-Saclay, Paris, France

Theoretical and Computational Mathematics

• Computational Statistics
• Machine Learning
• Probability Theory
• Algebraic Geometry
• Combinatorics
• Group Theory
• Topology
• Differential Geometry

Bachelor of Science

École Polytechnique, Palaiseau, France

Applied Mathematics

• Mathematics
• Physics
• Computer Science
• Statistics
• Machine Learning
• Probability Theory
• Algebraic Geometry
• Combinatorics
• Group Theory
• Topology
• Differential Geometry

Classes Préparatoires

Lycée du Parc, Lyon, France

Pure Math, Physics, and Computer Science

• Projective Geometry
• Algebra
• Combinatorics
• Group Theory
• Classical Mechanics
• Electromagnetism
• Statistical Physics
• Quantum Mechanics
• Algorithms
• Data Structures
• Graph Theory
• OCaml Programming

Excellence in Mathematics Research

École Polytechnique

Awarded for outstanding research contributions in theoretical mathematics and machine learning applications.

Neural Tangent Kernels: Depth vs Width Analysis

University of Maryland Research Papers

Investigating the fundamental trade-offs between network depth and width in neural tangent kernel theory, providing theoretical insights for deep learning architecture design.

Hierarchical Causal Models for Large-Scale Data Analysis

AI-Vidency Research Journal

Developed a comprehensive mathematical framework for hierarchical causal modeling and inference, with applications to massive dataset analysis and explainable AI systems.

Hierarchical Causal Models

Development of a comprehensive mathematical library for hierarchical causal modeling and inference, addressing the challenges of causal discovery in complex, multi-level systems.

• Open Source Library
• Mathematical Framework
• Causal Inference

DeNN-NTK: Deep Neural Networks and Neural Tangent Kernels

Research implementation exploring the relationship between deep neural networks and Neural Tangent Kernel theory, investigating the depth vs width question in neural architecture design.

• Deep Learning Theory
• Neural Tangent Kernels
• Mathematical Analysis

FPGA HDR: Hardware-Accelerated High Dynamic Range Processing

Implementation of high dynamic range image processing algorithms on FPGA hardware, focusing on real-time performance optimization and mathematical precision.

• FPGA Development
• Image Processing
• Hardware Optimization

HFT QR RL: High-Frequency Trading with Quantitative Research and Reinforcement Learning

Application of quantitative research methods and reinforcement learning algorithms to high-frequency trading strategies, combining mathematical modeling with machine learning.

• Quantitative Finance
• Reinforcement Learning
• Algorithmic Trading

SCIML: Scientific Machine Learning Framework

Development of a scientific machine learning framework that bridges traditional mathematical modeling with modern ML techniques for scientific computing applications.

• Scientific Computing
• Machine Learning
• Mathematical Modeling

OCaml Mathematical Computing

Collection of mathematical computing tools and algorithms implemented in OCaml, focusing on functional programming approaches to computational mathematics.

• Functional Programming
• Mathematical Computing
• Algorithm Design