Jai Bhagat
Profile Picture Interests Gif

jkbhagatio [at] gmail [dot] com

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Résumé

Hi, I'm Jai, welcome to my personal site!

 

I'm interested in how stuff works, and how we can best learn how stuff works. I try to take my work seriously, but not myself 😁  

I'm currently working as a Machine Learning Research Scientist at Enigma, building foundation models of the brain. Generally, my research focuses on understanding and creating intelligent systems† -- systems that make use of complex environments to achieve varied goals. Using animal nervous systems and artificial neural networks as models, I create and test theories that explain intelligent behavior as a function of processes that propagate information within these models‡.  

Previously, I completed a Ph. D. in Computational & Sytems Neuroscience at the Sainsbury Wellcome Centre (SWC) at University College London (UCL), an A.S.P. in Brain & Cognitive Sciences at Massachusetts Institute of Technology (MIT), and a B.A. in Neuroscience at Boston University (BU). I've also worked with Jack Lindsey (Anthropic) as a Bogue Fellow, Stefan Heimersheim (Apollo Research) as a MARS Scholar, and as a Data Scientist, Software Developer, and Technical Associate at SWC, UCL, the International Brain Lab, and MIT. In these roles, I've contributed to many renowned, collaborative research projects in the fields of Artificial Intelligence, Machine Learning, Neuroscience, and Neuroengineering. 


Computational Neuroscience Brain

Active Research Areas

  • Computational and Systems Neuroscience
  • Artificial Intelligence and Machine Learning
    • Alignment & Mechanistic Interpretability
    • Autonomous, Generative AI
    • Deep (Reinforcement) Learning
  • Software and Hardware Development
  • Signal Processing and Information Theory
Android Robot Brain

Additional Research Interests

  • Human & Brain Machine Interfaces
  • Neural Augmentation
  • Cybernetics and Robotics
  • Extended Reality (XR: VR, AR, MR)
  • Programming Languages
  • Computer Networking and Web Development
  • Theoretical Physics
  • Metalearning, Logic, Epistemology, and Ontology