Dr. Tanvi Banerjee is an associate professor in the Department of Computer Science and Engineering at Wright State University, where she also serves as the codirector of the Data Science for Healthcare Lab. She holds a PhD and an MS in electrical and computer engineering from the University of Missouri.
Dr. Banerjee’s core research interest lies at the intersection of computing and medicine, where she focuses on healthcare applications that utilize wearable and non-wearable sensors for chronic disease management, including measuring stress in caregivers of dementia patients. Her work extensively employs machine learning techniques, data fusion, and big data analytics to classify complex sensor data. With an h-index of 27, her publications cover topics such as multimodal data analysis, physiological responses, and predictive modeling for conditions like sickle cell disease, dementia, and chronic pain. Throughout her career, she has secured substantial research funding, with her personal share of grants totaling approximately USD 2.5 million from prestigious institutions such as the National Institutes of Health (NIH), the Department of Energy, and the Air Force Research Laboratory (AFRL). An accomplished educator, she was honored with Wright State’s College of Engineering and Computer Science’s Teaching Award for the 2024–2025 academic year. Her leadership role in the scientific community is reflected in her position as an associate editor for IEEE Transactions on Artificial Intelligence and as local chair and program committee member for several international conferences.
An estimated 8.8 million Indians above the age of 60 live with dementia, yet most remain undiagnosed and lack access to essential resources. To bridge this gap, Dr. Banerjee’s Fulbright-Nehru research project is proposing a culturally nuanced, region-specific Dementia Assessment tool tailored for rural communities. This will enable patients to securely share high-frequency cognitive assessments with their care providers. By deploying AI models to forecast symptom progression, the tool can empower clinicians to deliver proactive interventions and personalized treatment courses, thereby ultimately transforming rural dementia care in India.