I’m Rohan, a Principal Computational Biologist working at the intersection of large-scale genomics, biostatistics, machine learning, and artificial intelligence. I earned my PhD in Computational Biology from the University of Minnesota, where I built the quantitative foundation that still shapes how I approach research questions today. At a major academic medical center, I now lead the computational side of Next Generation Sequencing projects and population-level epidemiology studies focused...
I’m Rohan, a Principal Computational Biologist working at the intersection of large-scale genomics, biostatistics, machine learning, and artificial intelligence. I earned my PhD in Computational Biology from the University of Minnesota, where I built the quantitative foundation that still shapes how I approach research questions today. At a major academic medical center, I now lead the computational side of Next Generation Sequencing projects and population-level epidemiology studies focused on breast, ovarian, pancreatic, and endometrial cancers.
Day to day, I design and develop analytical models and pipelines on Google Cloud platforms, writing in Python, R, and shell to manage, process, and interpret complex biological datasets. Reproducibility matters a great deal to me, so I follow rigorous version control practices and treat well-documented, maintainable code as part of the science rather than an afterthought. That combination of statistical rigor and engineering discipline is what allows genomic findings to hold up under scrutiny and to scale from a single study to an entire population.
Alongside my research, I tutor students and working professionals in text and image processing for deep learning and AI projects. I especially enjoy the moment when a learner stops seeing a model as a black box and begins reasoning about why it behaves the way it does: how the data should be structured, which approach suits the problem, and how to evaluate performance honestly. Whether you are getting started in NGS, bioinformatics, and computational genomics, or you are building an AI-driven analysis and want someone to think it through with you, I would be glad to support your learning and your project.
