Sanjay Purushotham wins NSF CAREER award for AI & healthcare

Today, a plethora of technologies, from image recognition tools to chatbots, are powered by machine learning. A key component to the technique's success is data -- and lots of it. For doctors and hospitals who hope to use machine learning to improve healthcare, that need for copious data presents a problem: medical data is protected by privacy laws and often exists in incomplete or diverse forms -- from doctor's notes to medical scans -- that make it difficult for machine learning models to use it effectively.

"Using data better to aid medical decisions is a grand challenge of the 21st century," says Sanjay Purushotham, an assistant professor in information systems at UMBC. "We need innovations in existing techniques to take full advantage of artificial intelligence in healthcare."

Together with his students, Purushotham is tackling that challenge. He recently received a prestigious NSF CAREER award to support his team's efforts to develop new ways to train health-focused machine learning models. 

Purushotham has been contributing his expertise in computer science to collaborations with doctors and hospitals for almost ten years. The NSF CAREER award will help Purushotham further that research in a new direction, and ultimately, his team hopes their work will improve medical treatments and reduce costs, benefiting patients around the world

Read more about his research in this UMBC News article. 

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