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Amin Nejatbakhsh

Postdoctoral Researcher of Theoretical Neuroscience

Flatiron Institute

About Me

I am a Flatiron Research Fellow in the Center for Computational Neuroscience and a Visiting Scholar at NYU. I completed my Ph.D. in the Center for Theoretical Neuroscience at Columbia University primarily advised by Liam Paninski.

I work on statistical modeling of neural data and the overarching goal of my research is to causally understand biological and artificial recurrent neural networks and dynamical mechanisms therein. I’m interested in a wide range of topics including machine learning, statistics, causal inference, dynamical systems, neuroscience, and computer vision. In ML and statistics, I’ve worked on applied optimal transport, partial information decomposition, switching linear dynamical systems, causal dynamical systems, and covariance estimation. In computer vision, I’ve built automated tools for the segmentation, detection, and tracking of cells in microscopy images and videos. I’ve also developed statistical atlas construction methods for capturing structural variability across a population of animals. I’ve also extended non-negative matrix factorization (NMF) to deformable NMF and applied it to calcium demixing in non-stationary videos. In computational neuroscience, I’ve developed and applied functional and interventional connectivity estimation techniques. I’m currently working on representational similarity analysis for comparing neural representation across animals, species, and neural networks. Visit my Google Scholar for a list of my publications.

Apart from my academic life, I’m very much into sports and dancing. I play soccer in a NYC league and occasionally play basketball, swim, bike and run. I’m currently learning figure skating and I’m part of a Persian dance group called GISU.

Interests

  • Neuroscience
  • Probability & Statistics
  • Dynamical Systems
  • Optimization
  • Machine Learning
  • Computer Vision

Education

  • Ph.D. in Neuroscience, 2022

    Columbia University

  • M.A. and M.Ph. in Theoretical Neuroscience, 2019

    Columbia University

  • B.Sc. in Computer Engineering, Minor in Pure Mathematics, 2016

    Sharif University of Technology

News

 
 
 
 
 

Jun 2024 – Present
Honored to be awarded the 2024 Leon Levy Fellowship in Neuroscience by The New York Academy of Sciences.
 
 
 
 
 
 
 
 
 
 

Mar 2024 – Present
I gave a lecture in the Neuroinformatics class at NYU on Multiple Object Tracking. Check out the slides.
 
 
 
 
 

Sep 2023 – Present
Our paper titled Estimating Noise Correlations Across Continuous Conditions With Wishart Processes has been selected for a poster presentation at NeurIPS 2023. This is my first, first-author paper at NeurIPS! Let’s go!
 
 
 
 
 

Apr 2023 – Present
Our paper titled Learning Probabilistic Piecewise Rigid Atlases of Model Organisms via Generative Deep Networks has been selected for an oral presentation at IPMI 2023. Excited to share this work with the community.
 
 
 
 
 

Nov 2022 – Present
I presented a poster at SfN22 titled Controlled switching linear dynamical systems: a framework for perturbative interrogation of RNNs. Very pleased to have a large audience attending my poster.
 
 
 
 
 

Nov 2022 – Present
I received the Flatiron Research Fellowship and I’ll be working with Alex Williams at the Flatiron Institute. Exciting times are ahead!
 
 
 
 
 

Sep 2022 – Present
I defended my thesis, and I’m a DOCTOR now! Grateful for the enriching and exciting Ph.D. experience at Columbia.

Recent Publications

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Contact

  • 160 5th Ave, New York, NY, 10010, United States
  • Once entered the building take the elevators to the 3rd floor
  • DM Me