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About

Hatem Fakhruldeen is a pioneering researcher at the intersection of robotics, artificial intelligence, and autonomous laboratory automation, with a particular focus on accelerating discovery in chemistry and materials science. His work addresses a critical gap in scientific automation: while liquid-handling workflows have long benefited from robotic systems, solid-state chemistry has remained stubbornly difficult to automate. Fakhruldeen's most influential contribution, "Modular, multi-robot integration of laboratories" (2023, 92 citations), demonstrates how coordinated robotic systems can execute complex solid-state workflows, including powder X-ray diffraction, with minimal human intervention. His ARChemist architecture (2022, 43 citations) provides a robust software framework enabling truly autonomous robotic chemistry systems. Beyond hardware integration, Fakhruldeen has pioneered intelligent sensing and manipulation capabilities, developing biomimetic solid dispensing using dual-arm robots, deep learning-based viscosity estimation that surpasses human performance, and adaptive grippers tailored for chemical laboratory environments. His robot skill-learning approaches for tasks like sample scraping further demonstrate his commitment to practical, deployable automation. Collectively accumulating over 250 citations, his body of work is reshaping how researchers conceive of the self-driving laboratory, making autonomous scientific discovery increasingly achievable.