Topic: Building AI solutions that fit the jigsaw puzzle
Presenter: Sourabh Kulhare, Global Health Labs
Abstract:
AI has potential for tremendous impact on health care, especially for the poorest people in our world community, who are most in need of better care. But AI solutions, however well-intentioned, are guaranteed to fail at the clinic if they don’t match the specific constraints of the medical problem, because an AI solution is only one piece in a complex jigsaw puzzle. Therefore, as a necessary condition for success, we need to expand the traditional definition of “AI work” to include both understanding the non-AI pieces of the puzzle, and also translating these constraints into forces that will properly shape our AI solution.
Presenter Bio:
Sourabh Kulhare, Global Health Labs
Sourabh Kulhare is an experienced Machine Learning Research Engineer at Global Health Labs working in multidisciplinary AI research groups. He focuses on developing efficient AI systems for low-cost healthcare applications. His research interests encompass deep learning architectures, sequence modeling, domain adaptation, generative modeling, and object detection. Sourabh holds a Master’s degree (M.S) in Computer Engineering from the Rochester Institute of Technology, specializing in video summarization and natural language processing.
Linked In : https://www.linkedin.com/in/skrealworld/
Google Scholar : https://scholar.google.com/citations?user=hTZnzOQAAAAJ&hl=en