Xavier Theimer-Lienhard

Research associate, LiGHT
Meditron core team: RL, reasoning, open medical LLMs

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About Me

I'm a research associate with the LiGHT Lab (Meditron) at EPFL, embedded in the Meditron program end-to-end across training, evaluation, and deployment. I started in 2023 in the sprints that produced early Meditron finetunes. As I took on more of the stack, I was asked to lead sub-projects in Meditron-Reasoning (RLHF + reasoning) and Meditron-Synthetic (safe clinical data generation).

My work focuses on making medical LLMs efficient, interpretable, and auditable: I co-designed evaluation pipelines, led RL and reasoning post-training on HPC, and built Meditree, a multi-agent inference method that mirrors clinical reasoning. Recently, I co-led Apertus-Meditron-FO, a fully open adaptation of the Swiss Apertus models for medicine, including an open medical corpus and fine-tuning of 8B/70B variants.

I hold a Master's degree in Data Science from EPFL (GPA 5.4/6) and a Bachelor's degree in Communication Systems. When I'm not iterating on training runs, I like to indulge in a little bit of running, climbing, random wikipedia articles reading sessions, café hopping (just this year i went from tea afficionado to chai lover to black coffee extremist). I have also been dubbed king of brunch by my friends.

Portrait of Xavier Theimer-Lienhard

Experience

Research Associate - LiGHT Lab (Meditron)

April 2025 - Present
  • Co-led Apertus-Meditron-FO, a fully open medical adaptation of Apertus 8B/70B.
  • Curated and standardized the Mediset instruction-tuning corpus with rationale and PMC evidence.
  • Built reproducible multi-node training workflows (Axolotl + DeepSpeed ZeRO-3) on HPC clusters.
  • Delivered consistent gains on medical benchmarks via domain-specific adaptation and careful evaluation.
  • Championed end-to-end openness: released weights, datasets, and training methods for auditability.

Short Term Scholar at Yale University - LiGHT Lab (Meditron)

Sep 2024 - April 2025
  • Led the Meditron reinforcement-learning and reasoning team (GRPO RLHF, SFT reasoning distillation).
  • Optimized training on SLURM clusters with vLLM, DeepSpeed, and Axolotl; built robust eval (MCQA, model judges).
  • Led synthetic-data generation with clinicians to create safe, representative clinical notes.
  • Mentored a student team and coordinated weekly cross-site meetings (EPFL ↔ Yale).
  • Contributed to end-to-end Meditron-3 training and evaluation; invited to Yale based on that impact.

Graduate Researcher - LiGHT Lab (Meditron)

Sep 2023 - Sep 2024
  • Developed Meditree, a multi-agent “tree-of-thought” inference method for differential diagnosis.
  • Built pipelines for structured medical-guideline ingestion and retrieval-augmented reasoning.
  • Contributed to one of the earliest medical finetunes of Llama-3 with a rapid training turnaround.

ML & Software Engineer - Irbis Consulting SA

Sep 2023 - Sep 2024 (part-time)
  • Developed an Electron application to automate bidding document creation, incorporating user feedback into iterative releases.
  • Built a deep-learning captcha solver in PyTorch and implemented a web scraper with search retrieval capabilities.

Selected Publications

News

Meta summit photo

Invited to the Meta Summit for Open Science

December 2024

Invited to the Meta Open Science Innovation Summit to share ongoing work with Llama models in Meditron, an open-source suite of medical large language models developed between Yale and EPFL, and to discuss MOOVE, Meditron's open validation and evaluation framework for reliable global health AI.

Yale short-term scholar photo

Invited as Short-Term Scholar & Postgraduate Associate – Yale School of Medicine

October 2024

Joined the Biomedical Informatics & Data Science (BIDS) department as a Short-Term Scholar and Postgraduate Associate to continue core Meditron work across training, evaluation, and publication.

Education

Contact

I'm always open to discussing new projects or collaborations. Feel free to reach out via email or connect with me online.