Computational Biologist & ML Researcher
I build models that bridge AI and biology, from generative modeling to omics-driven discovery.
Researcher. Problem-solver. Creative.
I'm a researcher with a PhD in computational biology. I focus on developing generative models and graph-based approaches to understand biological systems, particularly how different omics interact in space and disease to give rise to phenotypes.
I've designed deep learning models for multi-omics integration, worked with large-scale single-cell and spatial data, and explored optimal transport to disentangle disease mechanisms and enable biological discovery.
Research & experiments I’m proud of
Designed a graph-based model using enzyme expression to infer metabolite abundance across subsystems, aiming to apply this framework to spatial transcriptomics.
Developed a spatially-aware model of ligand-receptor signaling in polycystic kidney disease (ADPKD)
I designed spVIPES, a model that disentangles biological variation. The architecture combines variational inference with a novel product-of-experts based alignment leveraging optimal transportto compare any two conditions.
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