Henry Chang

University of Washington, University of California San Diego

Papers

Total Citations

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About

Henry Chang is a pioneering researcher at the intersection of autonomous materials discovery and bio-inspired robotics. His work spans two transformative domains: accelerating sustainable energy solutions through AI-driven chemical synthesis, and enhancing robot locomotion through novel mechanical compliance strategies. Chang’s most impactful contribution is the development of flexible batch Bayesian optimization for autonomous organic synthesis, targeting redox flow batteries—a critical technology for grid-scale renewable energy storage. This work, published in 2025 with 15 citations, replaces slow trial-and-error methods with a closed-loop robotic system that learns and adapts, dramatically accelerating the discovery of next-generation battery materials. In parallel, Chang has made significant strides in legged robotics. His 2021 study on anisotropic compliance in robot legs (6 citations) demonstrated that directional stiffness can improve recovery from swing-phase collisions, boosting obstacle negotiation success by over 70% compared to traditional isotropic designs. His 2023 work on decentralized flexible-object transport (5 citations) introduced delayed self-reinforcement, a bio-inspired strategy that reduces object deformation without requiring inter-robot communication. Chang’s dual expertise in autonomous experimentation and adaptive robotics positions him at the forefront of efforts to create intelligent, self-optimizing systems for both materials science and physical interaction.