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Current Position

  • Aug. 2022 -
    Postdoctoral Fellow
    Cold Spring Harbor Laboratory
    • Advisor: Tony Zador
    • Neural networks for single-cell transcriptomic analysis
    • Theory of neuromodulation; neuro-inspired AI

Education

  • July 2022
    PhD, Bioengineering
    University of Pennsylvania
    • Advisor: Konrad Kording
    • Dissertation: Machine Learning as Tool and Theory for Computational Neuroscience
  • 2016
    M.S., Mechanical Engineering
    Northwestern University
    • Exited PhD program in order to switch disciplines of study
    • Advisor: Sinan Keten
    • Topic: Self-assembly & bio-inspired engineering at the nanoscale
  • 2013
    B.A., Physics
    Williams College

Teaching Experience

  • 2021
    Organizational TA for CIS-522, "Deep Learning"
    University of Pennsylvania
    • Helped organize course infrastructure, train TAs, and develop interactive Python course materials
    • Available at https://github.com/CIS-522/course-content
  • 2020
    Neuromatch Academy Course Developer (NMA-CD)
    Neuromatch Academy
    • Developed interactive Python course materials for W3D3 "Causality" and W1D4 "Machine Learning GLM"
    • Available at https://academy.neuromatch.io/nma2020/course-materials
  • 2024
    TA for Computational Biology
    Cold Spring Harbor Laboratory
  • 2020
    TA for Neuromatch Academy (NMA)
    Neuromatch Academy
    • Led 12 neuroscientists (PhDs, Postdocs, and 1 Assis. Prof.) through 15 days of NMA course materials
    • Provided mentorship for course projects
  • 2013-2014
    Chemistry Teacher, 10th and 12th grade
    Colegio Atid, Mexico City
    • Taught ~70 students across 3 classes
    • Built curriculum from scratch, adapting materials to new cultural context and IB curriculum
    • Guided independent research projects

Academic Service

  • Reviewing
    • Nature Communications
    • Nature Neuroscience
    • NeurIPS (Neural Information Processing Systems)
    • ICML (International Conference of Machine Learning)
    • COSYNE (Computational and Systems Neuroscience)
    • CCN (Cognitive Computational Neuroscience)
    • eLife
    • PLoS Computational Biology
    • Journal of Vision
    • Nature Scientific Reports
    • Cell STAR Protocols
  • Volunteer Work
    • Research Scientist Action and Advocacy Network (ScAAN), UPenn Chapter 2020
  • Student Organizations
    • Diversity Initiative for the Advancement of STEAM, Co-secretary 2022
    • Mechanical Engineering Graduate Student Society, President 2016
    • Mechanical Engineering Graduate Student Society, Social chair 2015

Conference Organization

  • 2023
    Why networks learn what they do; Insights from deep learning theory for neuroscience
    Computational and Systems Neuroscience (COSYNE) 2023

Conference Posters

  • 2024
    Interpreting networks as mixtures of experts yields an update preserving Dale's law
    From Neuroscience to Artificially Intelligent Systems (NAISys)
    • Authors: Ari Benjamin, Christian Pehle, Kyle Daruwalla
  • 2023
    Better cell typing from transcriptomic data via probabilistic models
    Computational and Systems Neuroscience (COSYNE)
    • Authors: Ari Benjamin, Xiaoyin Chen, Tony Zador
  • 2019
    Shared visual illusions between humans and artificial neural networks
    Cognitive Computational Neuroscience (CCN)
    • Authors: Ari Benjamin*, Cheng Qiu*, Ling-Qi Zhang*, Konrad P. Kording, and Alan A. Stocker
  • 2019
    Hue tuning curves in V4 change with visual context
    Bernstein Conference for Computational Neuroscience
    • Authors: Benjamin, Ari S., Pavan Ramkumar, Hugo Fernandes, Matthew A. Smith, and Konrad P. Kording
  • 2017
    Better encoding models with neural nets and boosted trees
    Computational and Systems Neuroscience (COSYNE)
    • Authors: Benjamin, Ari S., Hugo L. Fernandes, Tucker Tomlinson, Pavan Ramkumar, Chris VerSteeg, Raeed H. Chowdhury, Lee E. Miller, and Konrad P. Kording
  • 2017
    Color Tuning Curves in V4 Do Not Generalize to Natural Images
    Cognitive Computational Neuroscience (CCN)
    • Authors: Ari Benjamin, Pavan Ramkumar, Hugo Fernandes, Matthew A. Smith, and Konrad P. Kording

Conference Talks

  • 2023
    Balanced inhibition could help estimate gradients
    Computational and Systems Neuroscience (COSYNE)
    • Authors: Estelle Shen (presenting), Konrad Kording, Richard Lange, Ari Benjamin
  • 2020
    Teaching causality to neuroscientists: a case study in causal estimation
    Neuromatch Conference 3.0
  • 2020
    Learning with a wake-sleep discriminator that resembles surprise
    Neuromatch Conference 2.0
  • 2020
    A wake-sleep algorithm for sensory learning that uses a discriminator
    Year of Brain Sciences UnRetreat, Mahoney Institute for Neurosciences at UPenn
  • 2017
    Modern machine learning far outperforms GLMs at predicting spikes
    Statistical Analysis of Neural Data (SAND8)

Summer Schools and Courses

  • 2023
    Student - Analytical Connectionism
    Gatsby Institute for Computational Neuroscience at UCL
  • 2020
    TA - Neuromatch Academy (NMA)
    Computational neuroscience
  • 2017
    Student - Summer Workshop on the Dynamic Brain (SWDB)
    Allen Institute for Brain Science and University of Washington