Xin Yuan

Dr Xin Yuan

ARC Senior Research Fellow

School of Electrical and Electronic Engineering

Faculty of Sciences, Engineering and Technology

Xin Yuan, a.k.a. Vernon, is fascinated by the effects of Artificial Intelligence (AI) and autonomous machines on our contemporary daily lives and the innovations they brought to the industry. He believes that related research should not be limited to “narrow” domains. As a result, he is now enthusiastically involved in many developments of intelligent robotic systems to investigate more efficient approaches to Human-like intellectual functions. He focuses on discovering novel methods of constructing Artificial General Intelligence and Advanced Uncrewed systems.
Currently, Vernon is undertaking research at the University of Adelaide and working on discovering new approaches for the development of cognitive agent-based systems with AI and their impacts on the manufacturing, transportation and healthcare sectors. He teaches courses related to digital, electronics and autonomous systems. He has also supervised and led a long list of projects for developing advanced AI-enabled autonomous systems and applications.

Xin Yuan, also known as Vernon, is fascinated by the effects of AI on our contemporary daily lives. As a result, he is now enthusiastically involved in many developments of intelligent robotic systems to investigate more efficient approaches to AI functions and is focusing on methods of constructing Artificial General Intelligence, Autonomous Unmanned systems and Agent-based systems. He believes that, by analysing decision-making processes and behaviours of cognitive creatures, AI functions could be lifted and have more advanced impacts on our lives.

Currently, Xin Yuan is undertaking research at the University of Adelaide on a new form of cognitive architecture, which is using a parallel processing production rule-based structure. This research aims to investigate new approaches to develop cognitive agents with Artificial General Intelligence, which is to build machines with capabilities of understanding and learning intellectual tasks as a human does. There are two major challenges, which are how could we process data and information to be represented in a cognitive term, and what is the structure for making decisions as intelligent creatures. The investigation found that, in cognitive behaviours, information captured are fuzzy, and unnecessary details are ignored. Therefore, before decision-making, numerical values need to be converted into a fuzzy symbolic representation which describes the general situation in a “wordy” term. On the other hand, cognitive decision-making has a structure with IF-THEN rules at different levels. In this structure, fundamental information triggers to become knowledge and then knowledge provides an understanding of the situations. Eventually, a decision will be made while a serial of rules is triggered. In this research, an under-development computational architecture is used to process with only necessary environmental information and triggers a chain of knowledge-based rules to make a decision. The research contributes to demonstrating a new approach to build smarter machines in general, over “narrowed” AI functions.

Date Project Title Investigators Funding Body Amount
2021 Remote Operations - Shadow Robots - Stage 1 Shi P, Yuan X Australian Meat Processor Corporation AUD 165,000
2021 Collaborative Robots Evaluation and Deployment Strategy Development – Stage 2 Shi P, Yuan X Australian Meat Processor Corporation AUD 34,000
2021 AGVs (with optional integrated collaborative robots) - Stage 2 Shi P, Yuan X Australian Meat Processor Corporation AUD 34,000
2021 A systematic solution for Innovation Challenges of Australian Meat Processor Corporation Shi P, Yuan X Australian Meat Processor Corporation AUD 9,857.10
2021 Bone Belt Monitoring - Stage 2 Shi P, Wu Q, Yuan X Australian Meat Processor Corporation AUD 55,000
2021 Beef Butt (HQ) Deboning Automation – Stage 2 Shi P, Wu Q, Yuan X Australian Meat Processor Corporation AUD 235,000
Date Taught Developed Coordinated Course Title Institution Course Level/ Code
2017 x     Analog Electronics The University of Adelaide ELEC ENG 1100
2017 x     Electronic Systems The University of Adelaide ELEC ENG 1101
2017 x     Digital Electronics The University of Adelaide ELEC ENG 1102
2018 x     Analog Electronics The University of Adelaide ELEC ENG 1100
2018 x     Electronic Systems The University of Adelaide ELEC ENG 1101
2018 x     Digital Systems The University of Adelaide ELEC ENG 2100
2018 x     Digital Electronics The University of Adelaide ELEC ENG 1102
2018 x x x Autonomous Systems The University of Adelaide ELEC ENG 4107
2019 x     Analog Electronics The University of Adelaide ELEC ENG 1100
2019 x x   Electronic Systems The University of Adelaide ELEC ENG 1101
2019 x     Digital Systems The University of Adelaide ELEC ENG 2100
2019 x x   Digital Electronics The University of Adelaide ELEC ENG 1102
2019 x x x Autonomous Systems The University of Adelaide ELEC ENG 4107
2020 x     Analog Electronics The University of Adelaide ELEC ENG 1100
2020 x     Electronic Systems The University of Adelaide ELEC ENG 1101
2020 x     Digital Systems The University of Adelaide ELEC ENG 2100
2020 x x   Digital Electronics The University of Adelaide ELEC ENG 1102
2021 x x   Analog Electronics The University of Adelaide ELEC ENG 1100
2021 x x   Electronic Systems The University of Adelaide ELEC ENG 1101
2021 x     Digital Systems The University of Adelaide ELEC ENG 2100
2021 x     Digital Electronics The University of Adelaide ELEC ENG 1102
2021 x     Research Methods and Project Management The University of Adelaide ENG 3005
  • Position: ARC Senior Research Fellow
  • Phone: 83133159
  • Email: xin.yuan@adelaide.edu.au
  • Campus: North Terrace
  • Building: Ingkarni Wardli, floor 3
  • Org Unit: School of Electrical and Electronic Engineering
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