Innovative data scientist, developer and AI engineer integrating advanced analytics and AI to accelerate discovery and provide business impact. Proven leader in building scalable systems, automating complex pipelines, and developing operational tools that drive value across business applications and technology sectors.
Experience
At Elephas Biosciences, I've spent the last several years as Principal AI Scientist & Developer architecting multi-modal analytics pipelines that leverage custom assay data to predict drug response in ex vivo tumor models. As technical lead, we achieved over 96% training accuracy and 87% concordance with validation samples — work that directly enabled the company's first Lab Derived Test. I also led the statistical framework (adapting a TOST approach) for validating that test's method transfer across international sites.
Earlier, at GeoVisual Analytics, I built and trained deep-learning computer vision models for agricultural analytics using drone imagery — multi-modal systems fusing custom image data, weather feeds, and geolocation. Those bespoke models delivered best in class accuracy on harvest timing and yield forecasts across production sites in California and Arizona.
My start in industry was at Essen BioScience (Sartorius), where I designed segmentation and denoising algorithms for automated live-cell imaging.
Education & Credentials
I hold a PhD in Biomedical Engineering from The University of Texas at Austin (2016), where I was an NIH T32 Bioinformatics Fellow — my dissertation focused on photoacoustic imaging for cardiovascular applications. I also completed the Post Graduate Program in AI Agents for Business Applications at UT Austin's McCombs School of Business (2026), an accelerated program for designing, deploying, and governing agentic AI solutions.
Selected Publications
- Dana N. et al., "Prediction of immunotherapy response using live tumor fragments from routine clinical biopsies" — Manuscript in review (link)
- Ramasubramanian T.S. et al., "A live tumor fragment platform to assess immunotherapy response in core needle biopsies" — Journal of Translational Medicine 2025 (link)
- Dana N. et al., "Development and characterization of cytokine-based classifiers to predict response to immunotherapy using an ex vivo live tumor fragment platform" — SITC 2025 Poster (link)
- Dana N. et al., "Optimization of dual-wavelength intravascular photoacoustic imaging of atherosclerotic plaques using Monte Carlo optical modeling" — Journal of Biomedical Optics, 2017 (link)