About me

I’m a PhD candidate in Electrical and Computer Engineering at Georgia Tech, advised by Prof. Amirali Aghazadeh. I work on AI/ML with a focus on mechanistic interpretability, agentic AI, and generative and diffusion models — and I apply these methods to scientific problems.

My research spans interpretability of protein language models, cryo-EM image reconstruction, and the analysis of NASA astrobiology data for understanding the origin of life. My recent work has appeared at ICML 2026, CVPR 2026, and in PNAS Nexus.

Research interests

• Mechanistic interpretability — understanding the internal circuits of neural networks and protein language models (ProtoMech).
• Agentic AI for science — multi-agent systems that generate and test scientific hypotheses (ASTRA, AstroAgents).
• Generative & diffusion models — inverse problems and priors for scientific imaging (cryoSENSE).
• ML for astrobiology — discriminating biotic from abiotic organics in meteorite and terrestrial samples (LifeTracer).

Selected publications

• ICML 2026 — Protein Circuit Tracing via Cross-layer Transcoders
• CVPR 2026 — cryoSENSE: Compressive Sensing on the Protein Cryo-EM Image Manifold
• PNAS Nexus (2025) — Discriminating Abiotic and Biotic Organics in Meteorite and Terrestrial Samples Using Machine Learning on Mass Spectrometry Data
• ICML 2026 Mechanistic Interpretability Workshop — Circuit Tracing in Autoregressive Protein Language Models · ProtoMech: Protein Circuit Tracing via Cross-layer Transcoders

See all publications →

See my publications and projects, or download my CV.