Hugo Hakem

Biography

I completed the French grandes écoles programme, beginning with classes préparatoires at Lycée Aux Lazaristes, where I received training in mathematics, physics and chemistry. I then integrated CentraleSupélec, continuing my education in the natural sciences while gaining exposure to bioengineering. I subsequently moved to the United States to pursue a Master of Engineering in Bioengineering at the University of California, Berkeley. During this time, I developed a strong interest in computational biology, which led me to spend a year as a research intern at the Broad Institute of MIT and Harvard. I first worked in the Carpenter–Singh Lab, developing deep learning and explainable AI methods to study how genetic and chemical perturbations affect cell morphology using Cell Painting data. I then joined the Cellarium AI Lab, where I contributed to the development of a foundational single-cell RNA-seq model incorporating perturbation data. I am now eager to develop computational tools that leverage machine learning and interpretability to understand gene regulation across biomolecular scales and how these regulatory programs evolve under perturbations.

Research Interests

I am motivated by tool-building and deeply interested in artificial intelligence and concepts of emergence. My research aims to develop scalable machine learning models that operate across modalities and conditions to uncover the complex relationships between biomolecular scales, and to understand how these relationships can be perturbed to achieve desired phenotypic outcomes. These goals are closely aligned with drug target identification and, more broadly, with de novo drug design using generative models. In parallel, I place strong emphasis on reproducibility and interpretability, and seek to develop computational tools that are both reusable and genuinely insightful for the broader research community.

Professional Career

Education

Contact Information