Adaptive & Intelligent Matter (AIM) Lab
The Adaptive & Intelligent Matter (AIM) Lab explores how materials, structures, and mechanics can be harnessed to create systems that adapt, morph, and exhibit physical intelligence. By integrating nonlinear mechanics, metamaterial design, and soft robotics, we seek fundamental principles that enable mechanical intelligence—where adaptation and decision-making arise from the intrinsic dynamics of matter rather than from digital control. Our research spans multistable morphing structures, bio-inspired soft machines, and AI-driven inverse design of robotic systems. Through the convergence of solid mechanics, applied mathematics, and robotic materials, the AIM Lab advances adaptive and intelligent matter—structures capable of sensing, learning, and evolving with their environments.
The Principal Investigator
Dr. Mingchao Liu (刘明超) is currently an Assistant Professor at University of Birmingham. Before move to Birmingham, he was a Presidential Postdoctoral Fellow at Nanyang Technological University in Singapore from 2022 to 2023, and a Newton International Fellow at the Mathematical Institute, University of Oxford, sponsored by the Royal Society from 2018 to 2022. He graduated from Tsinghua University in 2018 with a PhD in Engineering from the Department of Engineering Mechanics. During his Ph.D study, he spent six months in 2017 as a visiting research fellow at the University of Sydney under the support of the Endeavour Research Fellowship. Prior to this, He received his B.S. in Engineering Mechanics from Shandong University in 2013.
Recent News
- 2025/10: Our paper, ‘Midveins regulate the shape formation of drying leaves.’, has been published in JMPS.
- 2025/09: Our paper, ‘Twist-Induced bifurcation and path manipulation in compressed ribbons.’, has been published in JMPS.
- 2025/08: Our paper, ‘Localization of deformation in the central hub of hub-and-spoke kirigami.’, has been published in JMPS.
- 2025/07: Our paper, ‘Harnessing Discrete Differential Geometry: A Virtual Playground for the Bilayer Soft Robotics.’, has been published in Adv. Intell. Syst..
- 2025/07: Dr. Liu has been awarded the Florence Price Award for Outstanding Early-Career Academic at the University of Birmingham Founders’ Awards 2025.
- 2025/06: Our paper, ‘A tutorial on simulating nonlinear behaviors of flexible structures with the discrete differential geometry (DDG) method.’, has been published in Appl. Mech. Rev..
- 2025/06: Our paper, ‘Real-time simulation enabled navigation control of magnetic soft continuum robots in confined lumens.’, has been published in JMPS.
- 2025/05: Dr. Liu has attended The 31st International Conference on Computational & Experimental Engineering and Sciences (ICCES2025) in Changsha, China and has been awarded the ICCES Outstanding Young Researcher Award.
- 2025/05: Dr. Liu was invited to write a Preview article for Newton.
- 2025/05: Our paper, ‘Achieving symmetric snap-through buckling via designed magnetic actuation.’, has been published in Sci. Adv..
- 2025/05: Our paper, ‘Localized tension–induced giant folding in unstructured elastic sheets.’, has been published in PNAS and Highlighted in the News of the University of Birmingham.
- 2025/04: Dr. Liu has been awarded the Mike Crisfield Prize for best presentation by UK Association for Computational Mechanics (UKACM).
- 2025/04: Dr. Liu attended the IUTAM Symposium on Data Driven Mechanics at Cambridge as an invited speaker and presented “Mechanics-Aided Machine Learning for the Design of Snap-Actuated Jumping Robots”.
- 2025/04: Our paper, ‘Transient asymmetry during elastic snap-through: The interplay between imperfections and oscillations.’, has been published in Phys. Rev. E.
- 2025/03: Dr. Liu attended the Euromech Colloquium 647 at Glasgow as an invited speaker and presented “Adaptive Folding Matter: From Natural Morphogenesis to Tunable Meta-Ribbons”.
- 2025/03: Dr. Liu has been awarded the Highly Commended for Outstanding Impact by an Early Career Researcher by the University of Birmingham.
- 2025/03: Our paper, ‘Morphing matter: from mechanical principles to robotic applications.’, has been awarded the Most Influential Paper Award in Soft Science.
- 2025/02: Our paper, ‘Inverse Design of Snap-Actuated Jumping Robots Powered by Mechanics-Aided Machine Learning.’, has been published in IEEE Robot. Autom. Lett..