Dr Huadong Mo

Dr. Huadong Mo is currently a Senior Lecturer at the School of Engineering and Information Technology, University of New South Wales Canberra, Australia. He received a B.E. degree in automation from the University of Science and Technology of China, China, in 2012 and a Ph.D. degree in systems engineering and engineering management from the City University of Hong Kong, Hong Kong, in 2016. He was a research associate at the Reliability and Risk Engineering Lab, Institute of Energy Technology, ETH Zurich, Switzerland, from 2016 to 2019 and a Lecturer at the School of Engineering and Information Technology, University of New South Wales at Canberra, Australia, from 2019 to 2021. His research aims to enhance the resilience, performance, and security of complex systems with learning-based algorithms, which primarily lay in the emerging field of power and energy systems, cyber-physical systems, and manufacturing systems, leveraging the capacity to collect and analyze data to reveal patterns of system evolution against disturbance.

***Scholarships of $35,000 (AUD) are available for Ph.D. students who achieved High Distinction (H1) in their undergraduate program and/or have completed a Master’s degree by Research.***

***A new research proposal is needed based on our further discussions***

Several types of scholarships are available (International Postgraduate Research Scholarships & China Scholarship Council (CSC) Sponsored Studies); however, admission and scholarship applications are highly competitive. Undergraduate Students (Top 15%) or Master Students  (Top 20%) in Automation, Statistics, Mathematics, Electrical Electronics , or Computer Science are highly preferred, but students in other subjects with similar competence are also welcome. A self-assessment tool is available to get a general feel for your competitiveness. You need to meet the English language requirements (refer to UNSW Canberra: TOEFL (IBT) 90 overall (min. 23 in writing, 22 in reading, listening, and speaking) and IELTS (Academic) 6.5 overall (min. 6.0 in each subset)). In addition, during your Ph.D. study, possible Ph.D. exchange with other top universities is encouraged, e.g. ETH Zurich, Cambridge, UCB, MIT, Université Paris Saclay, CityU of HK, NTNU, Tsinghua University, and NUS, and attending international conferences is also sponsored.

If you are eligible and interested in working with me on the following (or closely related) topics or keywords, please send me your CV, academic transcripts, the result of the self-assessment, and a research proposal consisting of Research Motivation, Research Problems, Research Objectives, a Brief Review of the most relevant Literature, Proposed Methodology (discussing your proposed approach to answer the RP&ROs including the type of data you need and how you will get them, techniques, etc.) and Expected Outcome (including a timetable over 3.5 years).

For more information, please refer to the following links on how and when to apply for a research degree. If you want to know more about my research, please refer to my Google Scholar and ResearchGate.

Research Topics:

• Advanced sensing and data analysis for prognostics and health management
• Sustainable transportation and energy systems
• Robust operation of power and energy systems under extreme events
• (Quantum-inspired) Reinforcement learning-based lifelong asset management

Others:

• IEEE Senior Member
• Postgraduate Course Coordinator of Systems Engineering, School of Systems and Computing, UNSW Canberra
• Chair of IEEE SMC ACT Chapter
• Best Presentation Award, 2022 IEEE 5th Student Conference on Electrical Machines and Systems, Korea
• Best Paper Award, 2021 Internation Conference on Electrical Machines and Systems, Korea
• Associte Editor or Committe Member for Over 10 SCI Journals and International Conferences

• Arc PGC Supervisor Award, 2021

• IEEE SMC Outstanding Chapter Award, 2021 (Chair: Fangbao Tian, co-Chair: Huadong Mo and Daoyi Dong)
• Alumni Achievement 2019, City University of Hong Kong
• Certificate of FULT Program 2019
• ‘Online health monitoring of battery via trustworthy artificial intelligence’ at the International Workshop on Big Data and AI-Driven Fault Diagnosis for Industrial Applications, Xi’an, China. (keynote)
• Wolfgang Kroger, Huadong Mo. Handing complex critical infrastructure towards increased resilience. The 11th International Conference on Reliability, Maintainability and Safety, 2016, Hangzhou, China. (keynote)
• Reviewer for over 30 international journals
• Outstanding Paper Award, 2017 IEEE International Conference on Industrial Engineering and Engineering Management, Singapore
• Outstanding Reviewer of 2 SCI Q1 Journals 
• Outstanding Academic Performance Award for Research Degree Students 2013-15 at City University of Hong Kong, Hong Kong (107,240 HKD)
• Outstanding Graduates of the University of Science and Technology of China, 2012