Summary
Vinu Vikraman is an assistant professor and data scientist with over a decade of experience applying advanced statistical and machine learning methods to astrophysics and biomedical imaging problems. He has led international scientific collaborations and produced high-impact results—co-authoring dozens of journal papers—while building scalable analysis pipelines deployed on 70–128 node clusters to process hundreds of millions of simulated and observed galaxies. His technical toolkit includes Python, MCMC, Random Forests, clustering and image segmentation, and he has delivered reusable software such as the PyMorph galaxy image pipeline and other research packages. Equally comfortable mentoring students and running distributed computations, he has translated complex astronomical theory into reproducible, production-ready code and even helped rule out a popular modified gravity model using observed data. Based in Arlington, MA, he brings a rare blend of deep domain expertise in cosmology and practical software engineering for large-scale scientific computing.
13 years of coding experience
6 years of employment as a software developer
Master's degree, Physics, Master's degree, Physics at Mahatma Gandhi University
Ph. D., Astrophysics, Ph. D., Astrophysics at IUCAA Pune