Jigar Doshi combines his decades of Deep learning expertise with a commitment to leveraging AI for societal good. Currently, he spends time at Artpark, Indian Institute of Science focused on utilizing Large Language Models (LLMs) in the domains of public health and climate change.  One of the project is a collaboration with ARMMAN who is on the mission to improve maternal and child health outcomes in underserved communities of India. This work was featured as one of the 5 innovative project to look forward to in Gates Notes

At Wadhwani AI, he led multiple high-impact projects, including a COVID-19 risk estimation initiative based on cell phone voice and cough recordings, low-resource early pest detection systems for cotton farmers, and accurate anthropometry solutions for newborns. His contributions in the field have been recognized widely by worldwide publications such as Time Magazine, Times of India, Gates Notes, Wired, Forbes, Fast Company, CNBC,, Indian Express, etc. 

Before Wadhwani AI, Jigar served as the Head of Machine Learning at CrowdAI, a geo-spatial startup based in California. One of his most cited works involves the development of the xView2 dataset, aimed at real-time disaster tracking. Prior to CrowdAI, he was part of the IBM Watson Research team, focusing on computer vision research related to video analytics, including activity recognition and classification.

Recently, Jigar was selected by the National Academy of Sciences (NAS) to speak in the 2024 Kavli Frontiers of Science symposia. He holds an MS in Electrical and Computer Engineering from Georgia Tech and a BS in Electrical Engineering from the New Jersey Institute of Technology (NJIT). His research at Georgia Tech centered on building multimodal deep learning models for humanoid robots.

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