The lab is affiliated with Mayo Clinic, Arizona and Arizona State University. Our members are computer scientists and clinical professionals with passion for AI.
At BanerjeeLab, we are pioneering the fusion of unstructured medical data—including radiology and pathology images, 3D anatomical models, and clinical notes—to develop advanced AI models that support clinical diagnosis, treatment planning, and precision medicine.
🎯 Our Focus
We are particularly interested in the longitudinal inference of patient data—understanding disease progression over time—and building pathways to deploy AI tools at the point-of-care. Our goal is to empower clinicians with real-time, data-driven insights for prevention, screening, and treatment of cancer and cardiovascular diseases.
🔬 Core Research Areas
AI Fairness in Healthcare
Multimodal Data Fusion
Clinical translation of AI models
Anomaly Detection
Large Language Models (LLMs)
Vision-Language Models (VLMs)
MedAI Journal club every week – joint with Stanford University, Emory University and NIH.
Collaborations: We have several multi-institutional research projects in collaboration with multiple academic centers and industries in US (including Stanford, Emory, MIT, Duke, SUNY Buffalo, Moffitt Cancer Center, UCSF, Philips healthcare, Carl Zeiss, Genetech, Arterys Inc) and Europe (CNR, Université Paris Descartes, HES-SO Valais) related to NLP and prediction. The application area of the developed methodologies spans from breast cancer, liver cancer, prostate cancer up to cardiovascular diseases, sepsis.
Competencies: Natural Language Processing, Computer Vision, Medical image analysis, deep learning, machine learning, Predictive modeling.
Open graduate student support and postdoc position in both Computer vision and NLP: please send CV and a letter of research interest to imon.banerjee[at]asu.edu
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