CV

Assistant Professor, Biomedical Engineering
Boston University
(617) 353-2816
Room 413, 44 Cummington Mall, Boston, MA, 02215

Academic Appointments

• 2023-present, Assistant Professor, Biomedical Engineering, Boston University, MA, USA
• 2023-present, Faculty Member, Hariri Institute for Computing, Boston University, Boston, MA
• 2023-present, Faculty Member, Center for Systems Neuroscience, Boston University, Boston, MA
• 2023-present, Faculty Member, Neurophotonics Center, Boston University, Boston, MA
• 2016-2022, Postdoctoral Fellow, Princeton Neuroscience Institute, Princeton, NJ
• 2005-2009, Research Assistant, Brain and Cognitive Sciences, MIT, Cambridge, MA

Education

• 2009-2016, PhD Neurobiology & Behavior, Columbia University, New York, NY
• 2005, BS Physics, Fordham University, Bronx, NY

Professional Activity

• 2024, Program Committee, Cosyne
• 2024, Organizer BU Neurophotonics symposium
• 2012-present, Journal reviewer: Nature Machine Intelligence, NeurIPS, Nature, Neuroscience, eLife, Neural Computation, PNAS, PLoS Computational Biology, Science Advances, ICLR, Cosyne (Conference), Computational Cognitive Neuroscience (Conference)
• 2021, 2022, Teaching assistant, COSYNE tutorial in computational neuroscience
• 2019-2020, Seminar series committee, Princeton Neuroscience Institute
• 2017-2022, Science writer, Simons Foundation, Collaboration on the Global Brain
• 2016, COSYNE Workshop Organizer, Recurrent Spiking Neural Networks—Dynamics, Learning, Computation

Honors

• 2010, National Science Foundation Graduate Research Fellowship
• 2005, Victor F. Hess Award (top Fordham U. graduating physics student)
• 2004, National Science Foundation REU summer student (UCSD, physics)

Invited Talks

• Invited speaker, Kempner Institute Machine Learning Foundations Seminar, Harvard, May 2024
• Invited speaker, Organization for Computational Neuroscience (OCNS), 2023. Leipzig, Germany Constructing spiking networks as a foundation for the theory of manifolds as computational substrate. https://cns2023.sched.com/
• DePasquale, B. (2023). The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks. In Spiking neural networks as universal function approximators (SNUFA). Online. https://www.world-wide.org/Neuro-Informatics/SNUFA/
• Boston University, Department of Biomedical Engineering, 2022
• Cold Spring Harbor Laboratory, 2021
• Champalimaud Centre for the Unknown, 2021

Science Writing

I sometimes write about other people’s science. Below are some examples I have contributed to the Simon’s Collaboration on the Global Brain.

• A New Era for the Neuroscience of Social Behavior
• Searching for Shapes in Neural Activity
• Hippocampal Replay: Reflection on the Past or Planning for the Future
• Scoring the Brain: How Benchmark Datasets and Other Tools are Solving Key Challenges in Neuroscience
• Geometrical Thinking Offers a Window Into Computation
• In Olfactory System, a Balance of Randomness and Order