Sparkle Russell-Puleri, PhD, is currently an Associate Director in the R&D Data Sciences team at Janssen Pharmaceuticals (Johnson & Johnson). In her role, Sparkle is responsible for working across the data science organization to drive high-impact adoption and execution of strategic data science initiatives across a diverse array of therapeutic areas. Prior to rejoining the J&J family of companies, Sparkle worked in personalized medicine as a Senior Data Scientist within the Ophthalmology program at Genentech/Roche. Specifically, her global projects involve applying machine learning techniques to electronic health records and clinical imaging data to predict retinal disease progression.
Prior to Genentech/Roche, Sparkle worked on developing machine learning algorithms to optimize patient selection and monitor pre and post-op recovery at Johnson & Johnson, Medical Device Companies, and as a Process Engineer at Procter & Gamble. Sparkle received her BS/MS in Chemical Engineering at New York University and her Ph.D. in Biomedical Engineering at The City College of New York. Her research was focused on finding fluid shear stress-induced biomarkers for atherosclerosis.
Sparkle’s passion for increasing diversity in the Machine Learning space has driven her to co-organize the first New in ML workshop co-located at Neural Information Processing Systems (NeurIPS) 2019, which was extended to the 2020, International Conference on Machine Learning (ICML).Sparkle Russell-Puleri, PhD, is currently an Associate Director in the R&D Data Sciences team at Janssen Pharmaceuticals (Johnson & Johnson). In her role, Sparkle is responsible for working across the data science organization to drive high-impact adoption and execution of strategic data science initiatives across a diverse array of therapeutic areas. Prior to rejoining the J&J family of companies, Sparkle worked in personalized medicine as a Senior Data Scientist within the Ophthalmology program at Genentech/Roche. Specifically, her global projects involve applying machine learning techniques to electronic health records and clinical imaging data to predict retinal disease progression.
Prior to Genentech/Roche, Sparkle worked on developing machine learning algorithms to optimize patient selection and monitor pre and post-op recovery at Johnson & Johnson, Medical Device Companies, and as a Process Engineer at Procter & Gamble. Sparkle received her BS/MS in Chemical Engineering at New York University and her PhD in Biomedical Engineering at The City College of New York. Her research was focused on finding fluid shear stress-induced biomarkers for atherosclerosis. Sparkle’s passion for increasing diversity in the Machine Learning space has driven her to co-organize the first New in ML workshop co-located at Neural Information Processing Systems (NeurIPS) 2019, which was extended to 2020, International Conference on Machine Learning (ICML).