French Research Scientist with PhD in Bioinformatics, pioneering research into AI cognition and human-AI collaboration frameworks. Currently advancing breakthrough innovations at Institut Roche while developing FAIR 2.0 principles and next-generation AI supervision methodologies.
I am a passionate research scientist dedicated to advancing the frontiers of artificial intelligence, human-AI collaboration, and next-generation data principles. My recent work focuses on pioneering research into AI cognition and developing frameworks for effective human-AI partnerships.
PhD in Computational Biology (2010)
University of Strasbourg - Graduated with highest honors
Master's in Bioinformatics and Statistics (2006)
Université Paris-Sud
AWS Certified Solutions Architect
AWS Certified Developer
Amazon Web Services Professional Certifications
Design and Interpretation of Clinical Trials Certificate
Johns Hopkins University (2016)
Method for Characterising a Molecule
International Patent USPTO/INPI (2009-2010)
Method for Characterising Three-Dimensional Objects
International Patent USPTO/INPI (2009-2010)
High-fidelity synthetic data generation of clinical datasets
Patent P38713-EP (2024)
Scientific Project Manager at Institut Roche, Paris, France (since 2021)
Leading breakthrough innovations in data structuring, FAIR 2.0 principles, and
human-AI collaboration frameworks. Pioneering research into AI cognition and
developing next-generation methodologies for effective AI supervision and partnership.
Beyond my professional work, I am deeply fascinated by astronomy, consciousness studies, adaptive planning, and the philosophy of memory. These interests not only fuel my curiosity but inspire my research and creative endeavors.
My research spans the intersection of computational biology, artificial intelligence, and data science, with a particular focus on advancing human-AI collaboration and next-generation data principles. Recent work includes pioneering research into AI cognition, the evolution of FAIR data principles to FAIR 2.0, and the development of frameworks for effective human-AI supervision.
Genome curation, pathway analysis, and data modeling for biological systems understanding.
Pioneering research into AI psychology, unit prompt effects, and human-AI supervision frameworks for enhanced collaboration.
Advancing the next evolution of FAIR data principles, semantic modeling, and collaborative knowledge frameworks.
Scalable infrastructure design, AWS certified solutions for research computing.
Human-AI Supervision and Cognitive Enhancement
Pioneering empirical research investigating how minimal textual interventions ("unit prompts") can dramatically alter AI reasoning patterns. This quantitative study explores psychology-like responses in Large Language Models.
Next-generation collaborative research framework
Comprehensive framework advancing FAIR data principles to FAIR 2.0, emphasizing collective knowledge creation and enhanced collaborative research methodologies for the modern scientific landscape.
Framework for effective AI collaboration
Practical framework for optimizing human-AI supervision dynamics, providing evidence-based guidelines for effective AI collaboration and cognitive enhancement in professional environments.
npj Digital Medicine
Novel MIIC-SDG algorithm for generating synthetic health data using multivariate information framework and Bayesian networks. Introduces Quality and Privacy Scores (QPS) metric to quantitatively assess the trade-off in synthetic data generation methods.
Genetics
Comprehensive data integration framework for model organism databases, establishing standardized protocols for cross-species genomic data harmonization and interoperability across research platforms.
Protein Science
Democratizing phylogenetic analysis through user-friendly tools and comprehensive databases, enabling researchers worldwide to perform genome-scale evolutionary studies without specialized computational expertise.
Nucleic Acids Research
Comprehensive update on the Gene Ontology resource, detailing new developments in ontology structure, annotation processes, and computational tools that continue to advance functional genomics research worldwide.
Nature Genetics
Revolutionary framework for modeling causal relationships in biological processes, extending Gene Ontology to capture complex molecular interactions and pathway dynamics with unprecedented precision.
Ongoing empirical research into "unit prompts" - minimal interventions that dramatically alter AI cognition and reasoning patterns. Pioneering quantitative study investigating psychology-like responses in Large Language Models.
Unified LLM Interface
Write once, run everywhere
Production-ready unified LLM interface with 6+ providers (OpenAI, Anthropic, Ollama, MLX, HuggingFace). Features universal tool calling, structured outputs, embeddings, streaming, and OpenAI-compatible API server.
Comprehensive platform for continued pre-training and instruction fine-tuning of large language models using MLX on Apple Silicon. Features real-time training dashboards, model comparison, LoRA/DoRA fusion, quantization, and interactive testing.
Modular Python library for voice interactions with AI systems, providing text-to-speech (TTS) and speech-to-text (STT) capabilities with interrupt handling, voice activity detection using WebRTC VAD, and seamless integration with any text generation system.
Comprehensive evaluation of 44 open source language models across creative writing, logic puzzles, counterfactual reasoning, and programming tasks. Tested on Apple M4 Max with detailed performance analysis.
White paper developing the next evolution of FAIR (Findable, Accessible, Interoperable, Reusable) data principles, advancing collective knowledge and collaborative research practices.
Through photography, I explore the intersection of science and art, capturing moments that reflect my perspective on the world. From astronomical phenomena to intimate portraits, each image tells a story of curiosity and wonder.
I'm always open to discussing research collaborations, innovative projects, or simply sharing ideas about the fascinating intersections of science, technology, and art.