Award-winning data scientist, physicist, and technology entrepreneur who seamlessly blends analytic and research knowledge honed in the academic realm with real-world technical and industry expertise.
As Informationist and Data Scientist at Knowledgent, the data and analytics firm, specializes in applying advanced analytics and data science concepts and techniques, including machine learning (Regression, Neural Nets, SVMs, Clustering, PCA, Anomaly Detection, etc.), to help client organizations gain actionable insights and competitive advantage.
Currently leveraging predictive analytics expertise to deliver data-driven models that improve patient outcomes, decrease costs, and increase operational efficiency for healthcare and life sciences organizations.
Previously in Research & Development at Intel Corporation, designed and developed basis for Intel's worldwide high-volume manufacturing at the newest technology node and was recognized for computational modeling and process implementation.
Earned Ph.D. degree in Physics and multiple research fellowships from Penn State University, where he authored research published in multiple prominent peer-reviewed scientific journals, and BA degree in Physics from Cornell University.