Chang Jie Leong
Papers
2
Total Citations
31
H-Index
2
About
Chang Jie Leong is a leading figure in the digital transformation of materials science, pioneering the integration of software engineering and laboratory automation. His primary research focuses on developing robust, scalable frameworks for materials acceleration platforms (MAPs) and optimizing the precision of automated liquid handling systems. Leong’s major contribution is the creation of an object-oriented framework that enables seamless workflow evolution across diverse MAPs, a breakthrough that allows researchers to adapt and scale automated experiments without rebuilding their software infrastructure. This work, published in 2022, has already garnered 22 citations, reflecting its immediate impact on the self-driving lab community. In a complementary vein, his 2024 study on the “sticky situation” of viscous liquid transfers is a practical tour de force: by applying multi-objective optimization to aspiration and dispense rates, Leong solved a critical bottleneck in pipetting robotics, enabling accurate handling of non-Newtonian fluids. This achievement not only enhances reproducibility in high-throughput experiments but also opens new avenues for automating complex formulations. Leong’s work stands at the intersection of computer science and wet-lab practice, making him a key architect of the next generation of autonomous discovery platforms.
Research Focus
Key Achievements
Top Papers
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