SUMMARY
Imon Banerjee, Ph.D., conducts research in computer science focused on artificial intelligence (AI) and data mining. Her work demonstrates how AI models can reflect racial bias across multiple imaging modalities and seeks to reduce disparities in healthcare. She addresses these challenges using approaches such as model unlearning and adversarial debiasing, which help remove inaccurate, harmful or outdated patterns learned by AI systems.
Dr. Banerjee collaborates with institutions that assist underserved populations, including Emory University in Atlanta and Mountain Park Health Center in Arizona. These partnerships support the training and evaluation of AI models using representative datasets.
In addition, Dr. Banerjee develops methods to integrate multisource medical data, including imaging, structured data and clinical notes. These multimodal approaches support improvements in diagnosis and treatment. She works closely with collaborators in oncology, cardiology, pathology, neurology and radiology to develop AI tools that support clinical decision-making and prognosis.
Through the Mayo Clinic and Arizona State University Alliance for Health Care, Dr. Banerjee collaborates with faculty at Arizona State University. She has written more than 120 peer-reviewed publications and regularly presents her work at scientific conferences. Her research is widely cited, and she is actively engaged in mentoring postdoctoral fellows and graduate students. Dr. Banerjee leads multiple externally and institutionally funded research projects.
Focus areas
- Multimodal data integration. Dr. Banerjee develops methods to fuse imaging and nonimaging data to support clinical diagnosis and prognosis.
- Natural language processing. Dr. Banerjee applies natural language processing techniques to support data curation for state and national cancer registries.
- Fair and responsible AI. Dr. Banerjee focuses on developing AI models using computational debiasing to promote fairness and reduce healthcare disparities.
Significance to patient care
Dr. Banerjee's research helps healthcare professionals make better, more accurate decisions for patients. By improving how AI uses medical images, test results and clinical notes, her work supports earlier diagnosis and more-personalized treatment.
She also focuses on making sure AI tools work fairly for people of all backgrounds. By reducing bias in AI models, her research helps lower the risk of unequal care and improves trust in new technologies used in healthcare.
Overall, Dr. Banerjee's work aims to make advanced technology safer, more accurate and more representative — so patients receive the right care at the right time.
Professional highlights
- Radiological Society of North America:
- Member, Radiology Informatics Committee, 2023-present.
- Course director, Advanced Imaging AI Course, 2023.
- National Institutes of Health:
- Member, Clinical Informatics and Digital Health Study Section, 2023.
- Member, Imaging Guided Interventions and Surgery Study Section, 2023.
- Member, Informatics Technology for Cancer Research Study Section, 2023.
- Alternate chair, Special Emphasis Panel, National Cancer Institute, 2022, 2023.
- Associate editor, Nature Scientific Reports, 2022.
- Member, Graduate Admissions Committee, Computer Science Program, Arizona State University, 2022.
- Section editor, PLOS Digital Health, 2021.