Dr. Yuqian Lu earned his PhD in Mechatronics Engineering from The University of Auckland in 2017. He joined the university as a Lecturer in 2019 and was promoted to Senior Lecturer in 2022, and Senior Lecturer (over the Bar) in 2024.

His research focuses on developing intelligent system technologies that transform workplaces into more efficient, enjoyable, and sustainable environments. Specifically, he specializes in cognitive sensing, reasoning, control, and human interaction technologies, with applications in manufacturing and construction.

As Principal Investigator, Dr. Lu has secured over NZ$3.5M in competitive research funding, including grants from the MBIE Endeavour Fund (2024, Smart Ideas), MBIE Endeavour Fund (2026, Research Programme), National Science Challenge (2022, Seed), and Callaghan Innovation (2021-2023). He has also contributed as a co-Principal Investigator to research projects totaling more than NZ$20M. In recognition of his research contributions and real-world impact, he was awarded the University of Auckland Early Career Research Excellence Award in 2023.

Dr. Lu has published extensively, with over 120 papers appearing in leading journals and conferences in his field. He serves as an associate editor and editorial board member for several prestigious academic journals and conferences.

2023 UoA Research Excellence Award Ceremony Interview: https://www.youtube.com/watch?v=rDinvHYYLCk

TVNZ OneNews Interview on AI, Robotics, 5G: https://youtu.be/GgVvbyDCkY0?si=T321cuiospXKSbUG

Vision Explained on Next-Gen Intelligent Robot: https://youtu.be/MTKrBF3L0i8?si=p4S1PD3wf29JIBmo

Research team website (http://iai.auckland.ac.nz)

Distinctions/Honours:
- Journal of Manufacturing Systems, Best Paper Award, 2024

- 51^st International Conference on Computers and Industrial Engineering, Best Paper Award, 2024 

- KiwiNet Emerging Innovator, 2023
- University of Auckland Early Career Research Excellence Award, 2023
- 2021-2024 World's Top 2% Scientists, according to Stanford University
- Robotics and Computer-Integrated Manufacturing, Best Paper Award, 2021

Supervision Achievements:

• Saahil Chand, Dean's List and Nomination for Vice-Chancellor's Prize for Best Doctoral Thesis
• Ilango Kandasamy, Master of Engineering Studies Student, Best Paper Award, 51^st International Conference on Computers and Industrial Engineering, 2024

Initiatives

- IEEE RAS Automation Research Spotlights (https://www.automationspotlights.org/)

Responsibilities:
- Manufacturing System Teaching Group Coordinator
- Department Teaching Resource Coordinator

Committee/Professional groups/Services

- Associate Editor, IEEE Transactions on Systems, Man and Cybernetics: Systems

- Associate Editor, IEEE Transactions on Automation Science and Engineering
- Associate Editor, IET Collaborative Intelligent Manufacturing
- Associate Editor, IET Cyber-Systems and Robotics
- Associate Editor, IEEE CASE Conference Editorial Board

- Co-Chair, IEEE RAS Technical Committee on Digital Manufacturing and Human-Centred Automation
- Editorial Board, Journal of Manufacturing Systems
- Editorial Board, Journal of Engineering Design
- Editorial Board, Scientific Reports, Nature
- Managing Guest Editor, Robotics and Computer-Integrated Manufacturing
- Managing Guest Editor, International Journal of Computer-Integrated Manufacturing
- Guest Editor, Neural Computing and Applications
- Committee Member, NAMRI/SME (The North American Manufacturing Research Institution of SME) Scientific Committee

- Publication Chair, 2026 IEEE 19th International Conference on Automation Science and Engineering

- Publication Chair, 2025 IEEE 19th International Conference on Automation Science and Engineering
- Organisition Chair, 2023 IEEE 19th International Conference on Automation Science and Engineering
- Special Session Chair, 2022 IEEE 18th International Conference on Automation Science and Engineering
- Session Chair, 2021 IEEE 17th International Conference on Automation Science and Engineering
- IEEE, ASME and SME member

Areas of Expertise:
Intelligent robots, Automation, Machine learning, Smart manufacturing, Human-machine Interaction, Construction automation