About Us

Mission Statement The Knowledge Representation team at HKUST VisLab transforms human knowledge into computable artifacts, bridging AI with critical professional domains including scientific discovery, advanced manufacturing, medical practices, and social governance.

The Challenge AI's impressive capabilities can degrade in specialized fields. Three fundamental barriers emerge: AI struggles to leverage fine-grained domain knowledge, lacks controllability for high-stakes decisions, and fails to integrate with established workflows. These limitations expose AI's inherent trade-off: breadth and depth cannot be simultaneously maximized.

Current Solution Domain-Specific Representations (DSRs) offer a path forward---formal artifacts that encode specialized knowledge for AI systems. Yet creating effective DSRs demands intensive collaboration between domain experts and computer scientists, making the process labor-intensive, case-specific, and thereby costly.

Our Vision We are pioneering the democratization of DSRs. Through intelligent algorithms that automate the design, deployment, and communication of DSRs, we're building an ecosystem where human knowledge from diverse sources empowers diverse machines---making specialized AI accessible to all.

News

  • Our paper has received the 2026 Sun Tseng-ch'i Research Award for Intelligent Automation.
  • Our team has been awarded funding from HEC Group to support our research and industrialization on domain-specific representations for site-scale heterogeneous embodied systems.
  • Our paper has received the 2025 IEEE T-ASE Best Paper Award, the journal's top annual paper honor.
  • Our team has been awarded funding from the National Natural Science Foundation of China (NSFC) to support our research on the automated design of procedural knowledge representation.

Team Members

Dr. Huamin Qu
Supervisor
Yu-Zhe Shi
Executive Director
Zixin Chen
PhD Candidate
Hanlu Ma
PhD Candidate
Chun Yin Li
PhD Student
Bruce Y. Yu
PhD Student
Yanjia Li
PhD Candidate
Danxuan Liang
MPhil Student
Yichao Luo
MPhil Student
Xinyu Zhang
MPhil Student
Zhangqian Bi
Visiting Researcher
Qiao Xu
Visiting Researcher
Mingchen Liu
Visiting Researcher
Jintao Zhu
Visiting Researcher
Guijia Zhang
Visiting Researcher
Yongxin Guan
Visiting Researcher
Wenxi Cai
Undergrad
Zhiyu Wang
Undergrad
Siyao Huang
Undergrad
Shuo Peng
Undergrad
Yijia Ma
Undergrad
Dailin Wu
Undergrad

Collaborators

Ms. Jiawen Liu
Acc. Studio
Mr. Zhicheng Li
Meituan Inc

Selected Publication

2026

Computablizing Human Knowledge for Machines through Domain-Specific Representation

Computablizing Human Knowledge for Machines through Domain-Specific Representation

Yu-Zhe Shi, Zhangqian Bi, Lecheng Ruan, Yao Wan, Huamin Qu, Qining Wang, Philip S. Yu
Under Review by IEEE. 2026.
Automated Constraint Specification for Job Scheduling by Regulating Generative Model with Domain-Specific Representation

Automated Constraint Specification for Job Scheduling by Regulating Generative Model with Domain-Specific Representation

Yu-Zhe Shi, Qiao Xu, Yanjia Li, Mingchen Liu, Huamin Qu, Lecheng Ruan, Qining Wang
Best Paper Award

2025

Targeted control of fast prototyping through domain-specific interface

Targeted control of fast prototyping through domain-specific interface

Yu-Zhe Shi, Mingchen Liu, Hanlu Ma, Qiao Xu, Huamin Qu, Kun He, Lecheng Ruan, Qining Wang
Hierarchically Encapsulated Representation for Protocol Design in Self-Driving Labs

Hierarchically Encapsulated Representation for Protocol Design in Self-Driving Labs

Yu-Zhe Shi, Mingchen Liu, Fanxu Meng, Qiao Xu, Zhangqian Bi, Kun He, Lecheng Ruan, Qining Wang

2024

Expert-level protocol translation for self-driving labs

Expert-level protocol translation for self-driving labs

Yu-Zhe Shi, Fanxu Meng, Haofei Hou, Zhangqian Bi, Qiao Xu, Lecheng Ruan, Qining Wang
Constraint representation towards precise data-driven storytelling

Constraint representation towards precise data-driven storytelling

Yu-Zhe Shi, Haotian Li, Lecheng Ruan, Huamin Qu
IEEE VIS Workshop on Data Storytelling in an Era of Generative AI (GEN4DS). 2024.
Abstract Hardware Grounding Towards the Automated Design of Automation Systems

Abstract Hardware Grounding Towards the Automated Design of Automation Systems

Yu-Zhe Shi, Qiao Xu, Fanxu Meng, Lecheng Ruan, Qining Wang
AutoDSL: Automated domain-specific language design for structural representation of procedures with constraints

AutoDSL: Automated domain-specific language design for structural representation of procedures with constraints

Yu-Zhe Shi, Haofei Hou, Zhangqian Bi, Fanxu Meng, Xiang Wei, Lecheng Ruan, Qining Wang