Anindya Das Antar

Postdoctoral Research Scholar

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Biography

Anindya Das Antar is a Postdoctoral Fellow at the Lucy Family Institute for Data & Society at the University of Notre Dame. He is a technical researcher in Human-Computer Interaction (HCI) with a focus on applied Machine Learning (ML), human-centered explainable AI (HCXAI), and responsible AI, particularly in the context of interactive human-AI alignment. Anindya develops computational models of human behavior through active collaboration with domain experts, engaging them directly in the modeling process. This approach goes beyond traditional methods, where experts are often limited to data collection. Additionally, he designs interactive tools that enable not only AI engineers but also domain experts who may lack AI expertise to investigate model capabilities and limitations. His current research explores methods for formally incorporating missing domain knowledge into AI models to better align their decisions with the expectations, values, policies, and ethical standards of expert users. He is also interested in developing tools that support interactive transfer learning and auditing AI agent-based decision-making processes, which promote AI literacy among end-users. Anindya’s work has been published in leading HCI and AI conferences and journals.

He completed his Ph.D. and Master’s degrees in Computer Science and Engineering at the University of Michigan (UM), and earned his Bachelor’s degree in Electrical and Electronics Engineering from the University of Dhaka. He received the Dean’s Award for undergraduate academic excellence and the Weinberg Institute for Cognitive Science Ph.D. Fellowship. His research has been supported by organizations such as Procter & Gamble, the Toyota Research Institute, the NIH, and the Office of Naval Research. He also holds a Rackham Graduate Teaching Certificate, a Rackham DEI certificate, and was awarded the UM CSE Service Award in 2025. Anindya aims to advance responsible AI through research, education, and tools that bridge the gap between algorithmic systems and the real-world needs, challenges, and contexts of use for users.

Department:

Lucy Family Institute For Data and Society

Advisor:

Toby Jia-Jun Li, Ph.D., Assistant Professor of Computer Science and Engineering, College of Engineering and Director of Human-Centered Responsible AI Lab;