Since April 2025, I am a FCAI Research Fellow at Aalto University, a 5-year position funded by the Finnish Center for Artificial Intelligence. I work with groups

• Computational Systems Biology (Prof. Harri Lähdesmäki)
• Probabilistic Machine Learning (Prof. Samuel Kaski)

I am also a member of the ELLIS AI network, affiliated with ELLIS Institute Finland.

My interests span:

• Biology-Informed Machine Learning: blending flexible data-driven approaches and mechanistic models within Systems Biology

$\rightarrow$ For more information, you can have a look to this position piece: Position: Biology is the Challenge Physics-Informed ML needs to Evolve

• (Approximate) Bayesian Inference, Gaussian Processes and Bayesian Optimization.

I obtained my PhD in February 2022 from Ecole polytechnique, Inria and Institut Curie, under the supervision of François Fages and Annabelle Ballesta. The manuscript can be found here and the slides here. A detailed CV can be found here (Last updated: April 2025).

Besides, for a few years now, I have been cultivating a passion for indoor bouldering, with a mild success thus far 🫠

News

New work on Bayesian variable selection for Pharmacogenetics studies:

• J. Martinelli, I. Rebai, D. W. Haas, and J. Bertrand. Joint Bayesian Inference of Genetic Effect Sizes and PK Parameters in Nonlinear Mixed-Effects Models. arXiv, 2026.

New work on Time-Aware Latent Space Bayesian Optimization:

• T. A. Vu, J. Martinelli, H. Lähdesmäki. Time-Aware Latent Space Bayesian Optimization. arXiv, 2026.

A paper accepted at ICLR’26:

• X. Zhang, C. Hassan, J. Martinelli, D. Huang, and S. Kaski. In-Context Multi-Objective Optimization.

$\rightarrow$ I will present this work as a poster at ISBA 2026 in Nagoya, on June 29th.