About me

I am Staff Scientist, Machine Learning at Stellaromics where I develop computational and machine learning approaches for analyzing high-resolution, three-dimensional spatial transcriptomics data generated by Stellaromics’ novel spatial biology platform. I work on core algorithms and machine learning models for converting raw, terabyte-scale bio-imaging data into spatial gene expression information. In addition, I develop deep generative machine learning models that simulate raw imaging data that we use to test and benchmark our computational methods.

Prior to Stellaromics, I was Principal Scientist at Immunitas Therapeutics where I built a computational platform for identifying novel drug targets in immuno-oncology. I also implemented computational strategies for identifying clinical biomarkers of drug efficacy emerging from the company’s phase 1 clinical trial of IMT-009, a novel immune checkpoint inhibitor.

I am driven to transform the world’s vast and growing collections of high-dimensional genomics data into insights that drive progress in human health.