Hi, I'm Chandreyi (Zini) Chakraborty

BS/MS CS @ Georgia Tech  |  AI Interpretability Research

I earned my Masters and Bachelors in Computer Science from Georgia Tech, both with machine learning concentrations. My research focuses on uncovering LLM inner workings through mechanistic interpretability, and leveraging those insights to improve model capability and efficiency.

I second-authored a paper accepted to COLM 2026 that attributes social reasoning to training data at the corpus level, working with EleutherAI. We launched a website showcasing this work.

I am a member of the Entertainment Intelligence and Human-Centered AI Lab under Dr. Mark Riedl, where I published on how LLMs understand suspense in stories (COLM 2025).

I was a Machine Learning Teaching Assistant under Dr. Mahdi Roozbahani, where I developed a Socratic LLM agent that supports TAs in responding to student questions on EdStem using retrieval-augmented fine-tuning.

On the efficiency side, I co-first-authored a paper on the quantization robustness of diffusion LLMs against autoregressive LLMs.

Previously, I worked at Bloomberg on the Terminal, building an efficient portfolio aggregation service, and before that at Deloitte, where I worked with the Tennessee state government to enhance their Eligibility Benefits Management Portal and integrate SummerEBT Appeals.