Chirag Agarwal is an Assistant Professor at University of Virginia in the School of Data Science. Before joining UVA, he was a postdoctoral fellow at Harvard University. He received his Ph.D. in Electrical and Computer Engineering from University of Illinois at Chicago. Dr. Agarwal researches on developing Trustworthy Machine Learning Frameworks that go beyond training models for specific downstream tasks and satisfy trustworthy properties, such as explainability, fairness, and robustness.

He has authored in top-tier machine learning and computer vision conferences and leading scientific journals. His research has received Spotlight and Oral presentations at NeurIPS, ICML, CVPR, and ICIP. Dr. Agarwal has received industrial grants from Adobe, Microsoft, and Google to support his work on Trustworthy Machine Learning. His algorithm are used to understand industry-scale models in Amazon for surfacing important data points and showing that deploying an industry scale model trained only on half the data as surfaced does not lead to performance degradations.

Dr. Agarwal is the founder of the Agyeya Research Foundation, which focuses on democratizing research by supporting open collaboration in ML research and training the next generation of AI students in India.

For more details about him and his research, please check out his CV.