David Holcman

David Holcman is a Professor at the École Normale Supérieure de Paris (ENS), leading the Group of Data Modeling, Computational Biology, and Predictive Medicine at the Institut de Biologie de l'École Normale Supérieure (IBENS). His research focuses on integrating computational methods, mathematical modeling, and AI to advance neuroscience, medicine, and biophysics. Key contributions include the Narrow Escape Theory (2004), polymer physics in chromatin organization (2010), and stochastic modeling of neural networks.

Research Interests: His work spans computational methods for analyzing large biological datasets, EEG-based brain state prediction during anesthesia/coma, and modeling microdomains in neurons and glia. Recent efforts emphasize real-time algorithms, hybrid simulations, and machine learning for medical applications.

Awards & Grants: Recipient of the ERC Proof of Concept Grant 2025 (predictive anesthesia algorithms) and ANR grant 2023 (neurophysiology and anesthesia). Collaborations include teams at the University of Cambridge, Oxford, and UCSF.

Students & Alumni: Notable advisees include Dr. Nathanael Hoze (Tenure Track at INSERM), Dr. Stanley E. Strawbridge (Sheffield University), and Kanishka Basnayake (Phillips’ Prize winner). The lab actively recruits students for interdisciplinary programs in applied mathematics and biology.

Lab & Affiliations: The lab, established in 2006, maintains ties with Churchill College (UK) and focuses on predictive medicine, computational neuroscience, and biophysical modeling. Recent breakthroughs include DeepCellMap for microglial analysis and EEG-based brain state prediction tools.