Kritarth Dandapat

University at Buffalo, State University of New York

Papers

Total Citations

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About

Kritarth Dandapat is an emerging researcher at the cutting edge of materials science and artificial intelligence, with a focus on accelerating the discovery of multimetallic catalysts through the integration of robotics and agentic AI systems. His work addresses one of the most formidable challenges in computational materials science: the combinatorial explosion of the design space that arises as catalyst compositions, processing conditions, atomistic structures, and microstructures grow increasingly complex. Dandapat's most notable contribution introduces a paradigm shift away from conventional single-stream active learning approaches, proposing instead a multi-modal, AI-driven framework capable of navigating vast parameter spaces with greater efficiency and autonomy. By coupling robotic experimentation with intelligent agent-based decision-making, his research envisions a future where catalyst discovery is dramatically expedited, reducing the time and resources traditionally required to identify high-performing materials. Though early in his career, Dandapat's 2025 work has already begun attracting scholarly attention, accumulating citations that signal growing community interest. His research holds significant promise for fields ranging from clean energy to chemical manufacturing, where optimized catalysts are essential to sustainable technological progress.