AI-enabled design
Data-driven inverse design and intelligent manufacturing methods for complex engineering systems.
MECHANICS · INTELLIGENCE · MANUFACTURING
Liuchao Jin
Postdoctoral Fellow at The Chinese University of Hong Kong
I study how machine intelligence and advanced manufacturing can be used to design materials and structures with purposeful mechanical behavior.
ACADEMIC JOURNEY
Training and appointment
A foundation in mechanical engineering, developed through research in intelligent manufacturing and mechanics.
- 2026—PresentHong KongCurrent
Postdoctoral Fellow
The Chinese University of Hong Kong
- 2022—2026Hong Kong
PhD in Mechanical & Automation Engineering
The Chinese University of Hong Kong · Hong Kong PhD Fellowship Scheme
- 2018—2022Chengdu
BEng in Mechanical Engineering
Sichuan University - Pittsburgh Institute
RESEARCH THEMES
Engineering across scales
My research connects algorithms, mechanics, and fabrication to move from a design question to a manufacturable, experimentally validated structure.
Architected materials
Metamaterials and structures engineered for impact resistance, energy absorption, and adaptive response.
Adaptive fabrication
3D/4D printing, smart materials, soft robotics, and energy harvesting from concept to prototype.
SELECTED WORK
Recent research
Machine learning-based inverse design for functional materials
Methods, challenges, and engineering applications.
Co-first author
Inverse design of impact-resistant metamaterials
Machine-learning-enabled design of heterogeneous structures.
Corresponding author
From artificial to embodied and physical intelligence
A smart-manufacturing perspective on the next generation of intelligence.
Corresponding author