Current position
NIH K99/R00 Scholar
Center for Theoretical Neuroscience
Zuckerman Institute, Columbia University
Jerome L Greene Science Center 3227 Broadway, New York, NY 10027
Education
2018 Ph.D. in Statistical Physics
École Normale Supérieure (Paris, FR)
Dissertation title: Inference and modeling of biological networks
2015 M.S. International Master in Physics of Complex Systems
SISSA, ICTP, Politecnico di Torino, Sorbonne Universités, Université Paris-Saclay
Final evaluation: 110/110 cum laude
2013 B.S. Physics
University of Bologna Alma Mater Studiorum
Final evaluation: 110/110 cum laude
Academic Appointments
2024 Columbia University, New York (NY), Associate Research Scientist
2020 Columbia University, New York (NY), Postdoctoral Research Scientist
2019 Institut Pasteur, Paris (France), Postdoctoral Researcher
Publications
Google Scholar *Co-first author click on the title for full text
Tuned geometries of hippocampal representations meet the demands of social memory
L Boyle*, L Posani*, S Irfan, SA Siegelbaum, S Fusi
Neuron (2024)
The representational geometry of emotional states in basolateral amygdala
P.K. O'Neil*, L Posani*, J Meszaros, P Warren, C.E. Schoonover, A. Fink, S Fusi, C.D. Salzman
BioRxiv (2023)
Minimal epistatic networks from integrated sequence and mutational protein data
S Cocco, L Posani, R Monasson
BioRxiv (2023)
L Posani, F Rizzato, R Monasson, S Cocco
PLOS Computational Biology (2023)
Adolescent thalamic inhibition leads to long-lasting impairments in prefrontal cortex function
L Benoit, E Holt, L Posani, S Fusi, A Harris, S Canetta, C Kellendonk
Nature Neuroscience (2022)
R Ocadiz-Gomez, M Trippa, L Posani, R Monasson, S Cocco, C Schmidt-Hieber
Nature Communications (2022)
M Allegra, L Posani, R Ocasio-Gomez, C Schmidt-Hieber
Neuron (2020)
Integration and multiplexing of positional and contextual information by the hippocampal network
L Posani, S Cocco, R Monasson
PLOS Computational Biology (2018)
Functional connectivity models for decoding of spatial representations from CA1 recordings
L Posani, S Cocco, K Jezek, and R Monasson
Journal of Computational Neuroscience (2017)
Statistical physics and representations in real and artificial neural networks
S Cocco, R Monasson, L Posani, S Rosay, and J Tubiana
Physica A: Statistical Mechanics and its Applications (2017)
Functional networks from inverse modeling of neural population activity
S Cocco, R Monasson, L Posani, and G Tavoni
Current Opinion in Systems Biology (2017)
Invited Talks
2024 - Department Seminar, ICM Paris Brain Institute, Paris (FR)
2024 - Department Seminar, EPFL Lausanne (CH)
2024 - Department Seminar, Icahn School of Medicine at Mount Sinai (NY)
2023 - Group Meeting, GNT Group for Neural Theory, ENS, Paris (FR)
2023 - Group Meeting, IFM, Sorbonne Université, Paris (FR)
2023 - Department Seminar, QBio Institute, Paris Sciences et Lettres, Paris (FR)
2022 - Conference Seminar, Gatsby Foundation Tri-Center Meeting, HU Jerusalem (IL)
2022 - Group Meeting, Cedars-Sinai Medical Center & Caltech (virtual)
2019 - Center Seminar, Center for Theoretical Neuroscience, Columbia University (NY)
2019 - Center Seminar, Donders Institute for Brain, Cognition and Behaviour, Radboud Univ. (NL)
2018 - Conference Seminar, ICTP Spring College, ICTP, Trieste (IT)
Conference Talks and Presentations
2024 - Poster Presentation, COSYNE 24, Computational and Systems Neuroscience, Lisbon (PT)
2023 - Poster Presentation, SfN 2023, Washington, D.C.
2023 - Selected Talk, NeuralNet 2023, Marseille (FR)
2023 - Poster Presentation, Bernstein Conference 2023, Berlin (GE)
2023 - Poster Presentation, COSYNE 23, Computational and Systems Neuroscience, Montreal (CA)
2022 - Poster Presentation, COSYNE 22, Computational and Systems Neuroscience, Lisbon (PT)
2019 - Poster Presentation, CNS 2019, OCNS 28th Computational Neuroscience Meeting, Barcelona (ES)
2018 - Selected Talk, TEX2018 M-GATE, SISSA, Trieste (IT)
2017 - Selected Talk, CNS 2017, OCNS 26th Computational Neuroscience Meeting, Antwerp (BE)
2016 - Selected Talk, Multi-scale Integration in Biological Systems, Paris (FR)
2016 - Selected Talk, Statistical Physics Methods in Biology and Computer Science, Paris (FR)
2016 - Poster Presentation, Co-evolution in proteins and RNA, Cargese (FR)
Service
2023 - Mentor, COSYNE 2024 Mentoring Forum
2023 - Workshop organizer, COSYNE 2023 Montreal: "Are neurons interpretable?", 1st most attended
2023 - Organizer, ZIPS Zuckerman Institute Post Doc Seminar series, Columbia University, New York (NY)
2022 - Workshop organizer, COSYNE 2022 Lisbon: "Is geometry all you need?", 1st most attended
2022 - Organizer, CTN Theory Center Seminar series, Columbia University, New York (NY)
Reviewer: PLOS Comp Bio, COSYNE
Teaching
2022 - Teacher, Advanced Topics in Theoretical Neuroscience, Columbia University, New York (NY)
Topics: Computational methods for neural decoding and representational geometry
2018 - Teacher, Master course in Theoretical Systems Biology, École normale supérieure, Paris (FR)
Topics: Python programming and data analysis tools for quantitative biology
Grants and Awards
2023 - NIMH: K99/R00 Transition to Independence Award (994,000 $)
2019 - Org. for Computational Neuroscience: Travel Award
2015 - PSL Paris Sciences et Lettres: Doctoral fellowship (full funding for 3 years)
2014 - IDEX Paris Saclay: Excellence Grant International Master Student (10,000 €)
Non-academic Experience
2019 - curr. Cubbit, Co-founder and Advisor
2016 - 2019 Cubbit, Co-founder and Chief Scientist
Cubbit is a technological startup focused on cybersecure geo-redundant distributed cloud storage. It has emerged as the EU leader in distributed cloud services, serving over 5,000 clients across 70+ countries. In my experience as Chief Scientist, I provided strategic leadership to the data team, overseeing critical areas such as data management and engineering, data analysis, visualization, and interpretation to drive actionable decisions. As a co-founder, I serve as an executive board member, focusing on fundraising and strategy development.
2008-current: bike traveler