Yash Mehta

yashsmehta95[at]gmail.com

I am a second year PhD student in Computational Cognitive Science at Johns Hopkins University. While I’m still figuring out exactly what I want to do, my research will focus on integrating cognitive science and artificial intelligence.

My academic and professional journey has been enriched by collaborations with numerous talented scientists across various research projects. My primary areas of interest include foundation models, cognition, and computational neuroscience. I’ve had the opportunity to work with several esteemed labs and mentors, details of which are provided below. Before embarking on my research career, I gained valuable industry experience as a developer at Amazon.

I am deeply committed to mentoring and actively engage with students who are passionate about research. If you’re interested in exploring research opportunities or seeking guidance, please feel free to contact me directly.

w/ Mick Bonner

w/ Pranav Rajpurkar

w/ James Fitzgerald
Jan Funke

w/ Frank Hutter

w/ Tim Lillicrap, Peter Latham

w/ Erik Cambria

News

Sep 25, 2024	Conference. Our paper on infering synaptic plasticity rules got accepted at NeurIPS 2024! 🏆
Jun 15, 2024	Talk. Gave a talk on my work at Koita Center for Digital Health at IIT Bombay.
Oct 15, 2023	Update. Started at Harvard Medical School with Pranav Rajpurkar to work on knowledge graphs for automated radiology report generation 🏥
Sep 1, 2023	Talk. “Multimodal Foundation Models @ICML’23” at SenticLab in NTU Singapore!
Aug 19, 2023	Visit. Research visit to the Flatiron Institute and PolymathicAI team - multimodal foundation models for science!
Jul 20, 2023	Conference. Attended ICML 2023 in Hawaii! 🏄🏻‍♂️🌸
Mar 23, 2023	General. My application for US immigration has been approved under EB1A category - individual of outstanding ability! 🇺🇸
Dec 1, 2022	Conference. Co-presented work on node perturbation at NeurIPS 2022 in New Orleans! ✨🎷
Oct 1, 2022	Visit. 1 month as a student researcher in Larry Abbott’s lab at the Zuckerman Institute, Columbia University! 🗽
May 27, 2022	Got Married!
May 1, 2022	Editorial. Our special issue “Future-generation personality prediction from digital footprints” was accepted at FGCS international journal! Managing guest editor 🤝
Apr 25, 2022	Conference. Presented our NAS-BenchSuite paper on neural architecture search at ICLR’22.
Jan 10, 2022	Update. Started at HHMI Janelia Research Campus working on modeling synaptic plasticity with James Fitzgerald and Jan Funke 🪰
Nov 1, 2021	Teaching. Co-created attention and transformers module with Prof. Frank Hutter. Also served as TA for Deep Learning Lab, and Deep Learning MSc. courses.
Oct 15, 2020	Update. Joined the AutoML group with Frank Hutter at University of Freiburg, Germany, to work on neural architecture search.
Jan 10, 2019	Update. Joined Gatsby Unit, UCL in London as a Research Assistant working on biologically plausiblle credit assignment algorithms with Peter Latham and Tim Lillicrap (DeepMind)! ⚡️🙌🏼
Jul 15, 2018	Update. Started working at Amazon as a software development engineer in Bangalore.
Jul 1, 2018	Update. Graduated in Computer Science from BITS Pilani Goa! 🎓
Jan 15, 2018	Update. Started undergraduate research thesis with Erik Cambria on using large language models for personality trait prediction.

Selected Publications

NeurIPS

Model-Based Inference of Synaptic Plasticity Rules

Yash Mehta, Dan Tyulmankov, Adithya Rajagopalan, James Fitzgerald, and 1 more author

In 2024

Bib PDF Code

@inproceedings{mehta2024model,
  title = {Model-Based Inference of Synaptic Plasticity Rules},
  author = {Mehta, Yash and Tyulmankov, Dan and Rajagopalan, Adithya and Fitzgerald, James and Funke, Jan},
  year = {2024},
}

ICLR

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

Bib PDF Code

@inproceedings{mehta2022bench,
  title = {NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy},
  author = {Mehta, Yash and White, Colin and Zela, Arber and Krishnakumar, Arjun and Zabergja, Guri and Moradian, Shakiba and Safari, Mahmoud and Yu, Kaicheng and Hutter, Frank},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
}

NeurIPS

Stability and Scalability of Node Perturbation Learning

Naoki Hiratani, Yash Mehta, Timothy Lillicrap, and Peter Latham

In Advances in Neural Information Processing Systems (NeurIPS) 2022

Bib PDF Code

@inproceedings{hiratani2022stability,
  title = {Stability and Scalability of Node Perturbation Learning},
  author = {Hiratani, Naoki and Mehta, Yash and Lillicrap, Timothy and Latham, Peter},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
}