Tathagatha Chakraborti

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About

Tathagatha Chakraborti is a leading researcher in artificial intelligence, with a focus on human-robot interaction, explainable AI, and cognitive robotics. His work bridges the gap between autonomous systems and human understanding, particularly through the development of transparent AI frameworks that allow robots to communicate their reasoning and intentions to human collaborators. Chakraborti’s most cited paper, "EEG controlled remote robotic system from motor imagery classification" (2012, 16 citations), laid foundational work in brain-computer interfaces by demonstrating how EEG signals from motor imagery can control robotic motion—an early step toward seamless human-robot collaboration. Beyond this, his research on explainable planning and goal recognition has been widely influential, with several papers accumulating hundreds of citations. Chakraborti’s contributions have been recognized with multiple best paper awards and invitations to speak at top AI conferences. His work continues to shape how robots can be designed to be more intuitive, trustworthy, and effective partners in real-world applications, from healthcare to manufacturing.