About
I'm a Senior Applied Machine Learning researcher bridging research and production. After a PhD and postdoc in particle physics and cosmology, I moved into applied ML and system design, focusing on efficient inference for LLMs and retrieval-augmented systems.
My research focuses on making AI systems more efficient: every token processed and every millisecond of compute impacts scalability, user experience, and sustainability.
Research interests
Efficient LLM Inference
Optimizing LLM deployments for cost, latency, and sustainability: semantic caching, KV caching, and model routing.
Agentic Systems
Rethinking multi-agent systems: context engineering, memory, and tool integration.
Model Understanding
Probing transformer models internals to inform architecture decisions and model routing.
Selected publications
LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation
A modular memory framework for multi-agent systems that decomposes task trajectories into reusable units.
arXiv:2510.04851
Semantic Caching of Contextual Summaries for Efficient Question-Answering with Language Models
Reducing LLM inference costs by caching semantically similar queries and their contextual summaries.
arXiv:2505.11271
Exploring How LLMs Capture and Represent Domain-Specific Knowledge
Investigating knowledge representation in LLMs across specialized domains.
arXiv:2504.16871
Hybrid-RACA: Hybrid Retrieval-Augmented Composition Assistance for Real-time Text Prediction
EMNLP 2024 Industry Track
For earlier publications in particle physics and cosmology (H.E.S.S. Collaboration, MIMAC), see my Google Scholar profile.
Experience
Senior Applied Researcher
Microsoft – M365 Research / Efficient AI
Efficient inference of language models at scale, context engineering, agentic systems.
Applied Researcher
Microsoft
NLP, reinforcement learning, AIOps.
AI Resident
Microsoft Research – Cambridge, UK
Multi-task Bayesian optimization for RL training. Performance regression analysis tools.
Data Scientist
Booking.com – Amsterdam
Experimentation platform (A/B testing, synthetic control). Recommender systems.
Postdoctoral Researcher
CNRS / LPSC – Grenoble
Dark matter detector development (MIMAC project).
PhD in Particle Physics
Pierre and Marie Curie University – Paris
Tests of Lorentz invariance with gamma-ray observations (H.E.S.S. Collaboration).