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Hi there! I am a student and researcher working on theoretical neuroscience, machine learning, and reinforcement learning. I am currently pursuing my Ph.D. in Computation and Neural Systems (CNS) at Caltech. I completed my BASc. in Engineering Science at the University of Toronto majoring in Machine Intelligence in 2022.

I do research in UHN Krembil’s Neural Systems & Brain Signal Processing Lab under Prof. Milad Lankarany. I have worked in Turaga Lab at HHMI Janelia and in Prof. Steve Mann’s lab at the University of Toronto. For a list of my publications, see below.

I was also the co-founder and CEO of a medical analytics startup called CareTrack, and directed the Consulting Group at the University of Toronto Consulting Association (UTCA) to perform pro-bono management consulting engagements with non-profits and startups around the world from 2020-2022.

Recent video: Defense of my undergraduate thesis, “SpikeSynRL: Synaptic Level Reinforcement Learning-Derived Plasticity in Spiking Neural Networks”.

Some other representative videos:


[1] A. Bhargava, M. R. Rezaei, and M. Lankarany, “Gradient-free neural network training via synaptic-level reinforcement learning,” AppliedMath, vol. 2, no. 2, pp. 185–195, 2022.

[2] A. Bhargava and S. Mann, ”Adaptive Chirplet Transform-Based Machine Learning for P300 Brainwave Classification”, IEEE Engineering in Medicine and Biology Society Conference on Biomedical Engineering and Sciences, 2020 (Accepted & Presented)

[3] A. Bhargava, K. O’Shaughnessy, and S. Mann, ”A Novel Approach to EEG Neurofeedback via Reinforcement Learning”, Proc. IEEE Sensors, 2020 (Accepted & Presented)

[4] A. Bhargava, A. X. Zhou, A. Carnaffan, and S. Mann. “Deep Learning for Enhanced Scratch Input“, arXiv preprint arXiv:2111:15053, 2021

[5] S. Mann, C. Pierce, A. Bhargava, C. Tong, K. Desai, K. O’Shaughnessy, ”Sensing of the Self, Society, and the Environment”, Proc. IEEE Sensors, 2020 (Accepted & Presented)

[6] A. Bhargava, “Predicting Interest Level based on EEG Scan Data using Machine Learning Algorithms”, AP Capstone Project, 2018


  • [2022] Chen Fellowship: I was awarded the Chen Fellowship entrance scholarship at Caltech in the fall of 2022.
  • [2022] Caltech CNS PhD: I will be starting my PhD in Computation and Neural Systems at Caltech in the fall of 2022! I can’t wait to dive full-time into researching self-organization in neural systems through computational and theoretical work. Who knows, maybe I’ll pick up a pipette at some point!
  • [2021] Janelia Undergraduate Internship: I was selected for this internship (formerly the Janelia Undergraduate Scholars program) to work under the supervision of Srinivas C. Turaga on ML-driven protein engineering systems.
  • [2021] Shaw Design Scholarship: I received the Shaw Design Scholarship from the Faculty of Engineering Science in 2020 for my engineering design work both in and out of classes at the University of Toronto.
  • [2020] NSERC USRA: I received the Natural Sciences and Engineering Research Council of Canada’s Undergraduate Student Research Award grant to fund my research for the summer of 2020 on machine learning, signal processing, brain-computer interface (BCI) technology, and biomedical engineering, supervised by Professor Steve Mann of the University of Toronto.
  • [2020] Pearson Feature: I had the opportunity to be featured on Pearson Canada’s higher education blog earlier this year for my work in research and entrepreneurship.
  • [2019] EAN Scholarship: I received the University of Toronto’s Engineering Alumni Network (EAN) Scholarship for engineering-related design, creativity and innovation.

Academic Reviews

  • 2023 — IEEE American Control Conference (ACC).
  • 2022 — MDPI Applied Sciences.

Other Projects

Outside of work, I enjoy writing and playing music, squash, reading, and rock climbing.

  • A Thousand Years: New single (reharmonization of Christina Perri’s A Thousand Years).
  • 500px: My photography portfolio.
  • Recent songs: Spotify playlist of my latest releases.
  • YouTube: Where I post videos about some of my projects.

The emergence of intelligence from unintelligent components is a beautiful and mysterious phenomenon. I will develop and apply computational and mathematical tools to understand, augment, and reproduce the fantastic emergent properties of artificial and biological neural networks.

me, trying to get into grad school