Yuejiang Liu is an incoming Assistant Professor in the Department of Computer Science, supported by the Presidential Young Professorship award. He is currently a postdoctoral fellow at Stanford University, advised by Chelsea Finn and mentored by Yilun Du. He received his Ph.D. from EPFL, where he was advised by Alexandre Alahi, and also worked with Francesco Locatello, Chris Russell, and Bernhard Schölkopf. His research seeks to build intelligent agents that can perceive, reason, and act in the physical world. He is particularly interested in physical intelligence in open, dynamic environments, where agents must learn from limited data, act under partial observability, adapt to moving objects, and interact with other agents. His work spans adaptive robot policies, interactive world models, and proactive self-improvement, with the broader goal of enabling embodied agents to generalise, adapt, remember, and improve through experience. His research has been recognised with Best Paper awards at ICLR, CVPR, and RSS workshops, ICML Oral presentations, and invited talks at OpenAI, NVIDIA, and other leading institutions. Yuejiang leads the Learning for Embodied Minds and Agents (LEMA) Lab, which aims to discover simple and scalable principles of embodied intelligence while fostering a culture of rigor, curiosity, and growth. The group is actively looking for highly motivated Ph.D. students, postdoc researchers, and visiting students. For more information, please visit the lab website at https://lema-nus.github.io.