Anwesha

Oncologist and computational biologist bridging clinical oncology with data-driven discovery.

From Tumors to Transcriptomes

I’m an oncologist who got curious about the data behind the disease—and never looked back.

Now I spend my time wrangling genomic datasets, building reproducible pipelines, and asking questions that sit somewhere between the clinic and the command line.

How I got here

It started with seaweed and prostate cancer during my Master’s at UCD Dublin—investigating chemopreventive properties across cellular assays and omics data. That’s when I realized: the most interesting questions in cancer live in the data.

My PhD (also at UCD) took me deeper into the intersection of biology and computation. I investigated uptake mechanisms of novel surgical dyes in colorectal cancer patients, working across:

  • Medical imaging and image segmentation
  • Omics data integration
  • Confocal and fluorescence microscopy
  • Machine learning (collaborating with IBM) to classify tumor vs benign tissue for precision surgery

After my PhD, I joined a synthetic biology group at TU Darmstadt as a postdoctoral researcher, working on organ-on-chip technology. I built image analysis pipelines to classify vasculature vs tumor cells—helping the team understand the tumor microenvironment and develop better in vitro cancer models.

Each project pulled me closer to computational biology. Now I’m all in.

What I’m building now

  • NGS pipelines that are clean, reproducible, and well-documented
  • Single-cell analyses to dissect tumor heterogeneity
  • Multi-omics integrations to connect the dots across data types
  • Visualizations that make complex biology interpretable

Each project is a step in learning how to do computational biology properly—not just get an answer, but understand the method, question the assumptions, and make it reproducible.

Get in touch

If you’re working on cancer genomics, teaching bioinformatics, or just want to talk about data and biology—reach out via Email or LinkedIn.