Ansuman Halder

Papers

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About

Ansuman Halder is a pioneering researcher at the intersection of artificial intelligence and materials science, with a primary focus on accelerating the discovery and synthesis of metal halide perovskites (MHPs) through autonomous experimentation. His most notable contribution is the development of an AI-driven robotic platform that operates as a Materials Acceleration Platform (MAP)—a self-driving laboratory capable of synthesizing and characterizing MHPs in humid atmospheres. This work, published in 2025 and already garnering 11 citations, demonstrates a paradigm shift from traditional trial-and-error methods to closed-loop, data-driven discovery. By integrating machine learning with automated synthesis, Halder has enabled the prediction of synthesis-property relationships, significantly reducing the time and resources required to identify stable, high-performance perovskite materials for optoelectronic applications. His research addresses a critical bottleneck in MHP commercialization: their sensitivity to environmental conditions. Halder’s work exemplifies how autonomous labs can revolutionize materials science, offering a blueprint for accelerated discovery in other complex material systems. His achievements mark him as a key figure in the emerging field of self-driving laboratories.