Department of Biomedical Informatics
Stony Brook, NY 11794
Prateek Prasanna is an Assistant Professor in the Department of Biomedical Informatics at Stony Brook University and directs the Imaging Informatics for Precision Medicine (IMAGINE) Lab. He received his PhD in Biomedical Engineering from Case Western Reserve University, Ohio, USA. Prior to that, he obtained his master's degree in Electrical and Computer Engineering from Rutgers University and bachelor's degree in Electrical and Electronics Engineering from National Institute of Technology, Calicut, India. Dr. Prasanna's research focuses on building clinically translatable machine learning tools that leverage multiple data streams of imaging, pathology, and genomics to derive actionable insights for enabling better treatment decisions. His research involving development of companion diagnostic tools for thoracic, neuro, and breast imaging applications has been published in venues such as MICCAI, CVPR, ECCV, NeurlPS, Radiology, Medical Image Analysis, IEEE-TMI, etc, and has won several innovation awards.
- Computational Imaging Biomarkers for Precision Medicine: We develop radiomics, pathomics, and deep learning techniques to analyze complex tissue structures, enabling biologically and clinically grounded computational models for predicting treatment response in cancer and other diseases.
- Generative AI for Disease-Aware Medical Image Synthesis: We integrate domain insights, such as expert eye gaze patterns and radiomic features, into generative AI models to generate anatomically accurate medical images, improving diagnostic accuracy and interpretability through disease-aware image synthesis.
- Adaptive Learning and Domain Generalization in Radiology and Digital Pathology: We develop techniques such as meta-learning and knowledge distillation frameworks to handle domain shifts and enhance image segmentation and classification.
- Explainable AI for Medical Image Analysis: We integrate expert insights with deep learning to enhance interpretability in radiology and pathology, developing human-in-the-loop methods that provide meaningful explanations while ensuring robust clinical performance.
Publications: https://scholar.google.com/citations?hl=en&user=uyA1Q18AAAAJ&view_op=li…