Arindam Banerjee

Arindam Banerjee is a **Founder Professor** and **Professor** at the **Siebel School of Computing and Data Science** and the **Department of Electrical and Computer Engineering**, University of Illinois. He also holds affiliations with the **Center for Digital Agriculture** and the **National Center for Supercomputing Applications (NCSA)**. His research focuses on machine learning, deep learning, optimization, and their applications in climate science, health informatics, and geospatial data analysis.

Key research interests include neural networks, contextual bandits, adversarial learning, and foundation models. He has contributed to foundational work on neural operator theory, federated learning, and optimization guarantees for deep learning models. His interdisciplinary work bridges computer science with domains like agriculture, epidemiology, and climate modeling.

He is a **2024 ACM Fellow**, recognizing his contributions to statistical machine learning and learning systems. His recent studies include clinical trials on antiviral therapies for hospitalized COVID-19 patients, long-term health outcomes of post-COVID-19 conditions, and robust bandit algorithms for constrained resource settings.

Banerjee collaborates with global teams on sub-seasonal climate forecasting, geospatial data analysis (e.g., via TorchGeo), and multi-organ MRI studies post-COVID-19. His work emphasizes practical applications of AI in healthcare, agriculture, and environmental science.