Huadong Mo

Dr Huadong Mo is an Associate Professor at the School of Systems and Computing, University of New South Wales, Australia. He is also the Inaugural Director of Resilient Intelligent Systems for Clean Energy Research (RISER) Hub. 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 from 2019 to 2021, and then a Senior Lecturer at the School of Systems and Computing from 2021 to 2025 at the University of New South Wales. His research aims to enhance the resilience, performance, and security of complex systems using learning-based algorithms, primarily in the emerging fields of renewable energy, cyber-physical, and manufacturing systems, leveraging data sensing and analysis to reveal patterns of system evolution under uncertainty. He has established a distinctive research program that bridges fundamental AI research with large-scale translation in battery and clean-energy systems, attracting substantial industry and government co-investment and delivering technologies from methodological innovation through to real-world demonstration. ***Scholarships of $39,206 (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 and Electronics, or Computer Science are highly preferred, but students in other subjects with similar competence are also welcome. 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 learn more about my research, please visit my Google Scholar and ResearchGate profiles. Research Topics: 1. Advanced sensing and data analysis for energy system prognostics and health management 2. Sustainable transportation and energy systems 3. Robust operation of power and energy systems under extreme events 4. (Quantum-inspired) Reinforcement learning-based lifelong asset management Others: 1. IEEE Senior Member 2. Postgraduate Course Coordinator of Systems Engineering, School of Systems and Computing, UNSW Canberra 3. Chair of IEEE SMC ACT Chapter 4. Associate Editor or Committee Member for Over 10 SCI Journals and International Conferences, including International Journal of Machine Learning and Cybernetics, Scientific Reports, Quality and Reliability Engineering International etc 5. Certificate of FULT Program 2019 6. ‘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) 7. Wolfgang Kroger, Huadong Mo. Handing complex critical infrastructure towards increased resilience. The 11th International Conference on Reliability, Maintainability and Safety, 2016, Hangzhou, China. (keynote) 8. Reviewer for over 30 international journals urban resilience, smart grids, artificial intelligence, battery energy storage system; Fields of Research: Industrial Engineering, Renewable Power and Energy Systems Engineering (excl. Solar Cells), Control Engineering, Optimisation