Yash Mehta's Website

PhD student, Johns Hopkins University.

profile_pic.jpg

Located in Baltimore, USA

Hi! I’m excited about applications of deep learning and cognitive science in healthcare. I am currently working with Mick Bonner. I was also a visiting PhD student at Harvard Medical School, supervised by Pranav Rajpurkar. Throughout my academic journey, I have gained valuable experience in various domains, including transformers, LLMs, neuroscience, and cognition.

Previously, I was a research engineer at the amazing HHMI Janelia Research Campus, working on inferring synaptic plasticity rules using deep learning with James Fitzgerald. I have worked on Neural Architecture Search in Frank Hutter’s AutoML lab in the picturesque town of Freiburg! Before that, I had an amazing time at the Gatsby Computational Neuroscience Unit at UCL, where I was working on evaluating biologically plausible perturbation-based learning algorithms to train deep networks with Tim Lillicrap at DeepMind and Peter Latham. I did my undergraduate thesis at NTU Singapore with Erik Cambria on using large language models for personality prediction. I quit my job as a software developer at Amazon to dive into the world of research ;)

I thoroughly enjoy coding and working on hard algorithmic problems. Please reach out to chat, especially, if you’re starting out your research journey!

News

Jan 22, 2024 Shifted to Baltimore, Cognitive Science department at Johns Hopkins!
Oct 15, 2023 Joined as a visiting PhD student in Rajpurkar Lab, Harvard to work on AI+health
Jul 20, 2023 Attended ICML 2023 in Hawaii! ✨🍻
Dec 1, 2022 Attended NeurIPS 2022 in New Orleans! ✨🎷
Oct 1, 2022 Visiting student researcher in Larry Abbott’s lab at the Zuckerman Institute, Columbia University
Sep 14, 2022 Manuscript on node perturbation learning accepted to NeurIPS!
May 27, 2022 Got Married! :ring: :sparkles: :sunny:
Apr 25, 2022 Presented our paper, NAS-BenchSuite in ICLR’22.
Jan 10, 2022 Started at HHMI Janelia Research Campus in the Funke Lab

Selected Publications

  1. Towards Biologically Plausible Convolutional Networks
    Roman Pogodin, Yash MehtaTimothy Lillicrap, and Peter Latham
    In Advances in Neural Information Processing Systems (NeurIPS) 2021
  2. NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy
    Yash Mehta, Colin White, Arber Zela, Arjun Krishnakumar, and 5 more authors
    In International Conference on Learning Representations (ICLR) 2022
  3. Stability and Scalability of Node Perturbation Learning
    Naoki Hiratani, Yash MehtaTimothy Lillicrap, and Peter Latham
    In Advances in Neural Information Processing Systems (NeurIPS) 2022