Summary
Dhineshvikram Krishnamurthy is a Data Scientist II based in Philadelphia with 11 years of experience applying machine learning and imaging analytics to pediatric and fetal neuroimaging. He has a strong track record of turning advanced research methods—UNet segmentation, deep-learning localization, graph-theory fMRI analysis—into deployed pipelines that sped fetal brain segmentation threefold and enabled real-time clinical workflows. Prior roles span academic labs and healthcare systems (CHOP, Children’s National, Penn Medicine), where he built aggregated multimodal imaging databases, automated biomarker trajectory synthesis, and delivered validated tumor and fetal imaging tools. Comfortable across Matlab, Python, cloud deployments and MEAN-stack development, he combines clinical-domain insight with production engineering discipline. Notably, his work bridges signal-processing rigor from his MS in Bioengineering with practical productization, evidenced by conference presentations and clinical deployments.
11 years of coding experience
9 years of employment as a software developer
Master of Science - MS, Bioengineering and Biomedical Engineering, 3.9/4.0, Master of Science - MS, Bioengineering and Biomedical Engineering, 3.9/4.0 at The University of Texas at Arlington
Bachelor of Engineering - BE, Bioengineering and Biomedical Engineering, 3.2/4.0, Bachelor of Engineering - BE, Bioengineering and Biomedical Engineering, 3.2/4.0 at College of Engineering, Guindy