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About

Manjari Gupta is a computer science researcher whose work spans artificial intelligence, deep learning, and intelligent systems, with a particular focus on human activity recognition (HAR) and video-based analysis. Her most influential contribution, a comprehensive 2022 review of deep learning-based HAR on benchmark video datasets, has garnered 85 citations and has become an essential reference for researchers navigating the rapidly evolving landscape of AI-driven behavior analysis, scene understanding, and event recognition. Building on this foundation, her 2024 work, "STAR-3D," introduces a holistic framework for classroom activity recognition, applying sophisticated 3D video analysis to monitor and interpret student and teacher engagement — a timely innovation with meaningful implications for educational technology. Her intellectual roots extend to the early 1990s, where she explored reinforcement learning and distributed adaptive control systems for quadruped mobile robots, demonstrating a longstanding commitment to autonomous and emergent intelligence. This early robotics research foreshadowed the broader AI themes that define her contemporary scholarship. Across three decades, Gupta's work reflects a consistent drive to build intelligent systems capable of understanding and responding to complex, real-world human environments.