Jatin Nainani
Explorer first, researcher second, engineer third.
I’m deeply fascinated by intelligence and reasoning, both in narrow and general contexts. My core interests lie in reverse-engineering systems like Large Language Models (LLMs) and protein Language Models (pLMs), particularly exploring their non-trivial capabilities.
My research in Mech Interp follows a simple moto - “If a neural network can consistently show nontrivial abilites, I should be able to reverse engineer it”. If a network that satisfies the above two criteria is reading this, be wary! I am coming for you.
I iterate quickly with the goal to fail fast and adjust. I love learning things that fascinate me from ground up – currently focusing on proteins. I love hiking, writing, drawing, and playing tech mods on minecraft.
My master’s thesis on understanding protein Language Models with Mechanistic Interpretability is available at biorxiv: https://www.biorxiv.org/content/10.1101/2025.08.22.671739v1
You can contact me at: nainani.jatin.0@gmail.com
Publications and In-Progress Work
Mechanistic evidence that motif-gated domain recognition drives contact prediction in protein language models
Jatin Nainani, Bryn Marie Reimer, Connor Watts, David Jensen, Anna G Green
In preparation | 📄 biorXiv
Detecting and Characterizing Planning in Language Models
Jatin Nainani, Sankaran Vaidyanathan, Connor Watts, Andre N Assis, Alice Rigg
In preparation | 📄 arXiv
Adaptive Circuit Behavior and Generalization in Mechanistic Interpretability
Jatin Nainani*, Sankaran Vaidyanathan*, AJ Yeung, Kartik Gupta, David Jensen
In preparation | 📄 arXiv
CS4: Measuring the Creativity of Large Language Models Automatically by Controlling the Number of Story-Writing Constraints
Anirudh Atmakuru*, Jatin Nainani*, Rohith Siddhartha Reddy Bheemreddy, Anirudh Lakkaraju, Zonghai Yao, Hamed Zamani, Haw-Shiuan Chang
In preparation | 📄 arXiv
Evaluating Brain-Inspired Modular Training in Automated Circuit Discovery for Mechanistic Interpretability
Jatin Nainani
📄 arXiv
Smartphone based tactile feedback system providing navigation and obstacle avoidance to the blind and visually impaired
Anish Pawar, Jatin Nainani, Priyanka Hotchandani, Gayatri Patil
Publised at IEEE ICAST 2022 | 📄 IEEE
* Denotes co-first authorship.