About me

I’m Adib Hasan, a research engineer at a stealth startup, where I build large-scale retrieval-augmented generation (RAG) systems and optimize LLM inference for speed. I am interested in statistical learning theory, risk modeling, and algorithm design.

I hold a double major in Mathematics and Computer Science and a master’s in Computer Science from MIT, where I was advised by Dr. Mardavij Roozbehani and Prof. Munther Dahleh. My MEng thesis focused on learning latent weather representations using variational inference – essentially, pretraining a weather LLM but with variational approximation to overcome data scarcity.

In between my bachelor’s and master’s, I spent two years as a quant researcher managing multi-million dollar crypto portfolios and leading a team of four. You can find more on my LinkedIn.

Outside of work, I cook to avoid starvation (proof), read dead philosophers, and lift heavy objects to maintain the illusion of control.