Prof. Steven Weidong Su | Distributed system | Top Researcher Award

Professor, Shandong First Medical University,China📝

Professor Steven Su is a leading researcher and educator in the fields of medical AI, robotics, and systems control. With a Ph.D. from ANU, he has held significant academic and leadership roles at institutions like Shandong First Medical University and UTS. He is recognized for his work on AI Exoskeletons for stroke rehabilitation and the development of novel medical sensors. As a senior member of IEEE and an editor for several prestigious journals, he continues to shape the future of engineering and medical technologies through his teaching, research, and professional contributions.

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Education 🎓

Professor Steven Su holds a Ph.D. in Statistical Optimisation and its Application in Modelling and Control from the prestigious Australian National University (ANU). He completed both his Master of Engineering in Automation Engineering and Bachelor of Engineering in Automation at the Harbin Institute of Technology in China. His advanced education in engineering and optimisation theory has laid the foundation for his distinguished career in research and teaching, where he has made significant contributions to fields such as robotics, medical AI, and systems control.

Professional Experience 💼

Professor Steven Su has over 15 years of experience in academia, with a strong focus on teaching, research, and leadership in the fields of engineering and medical AI. He currently serves as the Associate Dean (Teaching and Education) at the College of Medical Artificial Intelligence and Big Data at Shandong First Medical University, overseeing academic programs and research leadership for 3,000 students and 130 faculty members. Previously, he was a Senior Lecturer and Associate Professor at the University of Technology Sydney (UTS), where he directed postgraduate programs and developed cutting-edge projects, including AI-powered exoskeletons for stroke rehabilitation. His leadership extends to roles such as Chief Technical Officer at Sydney Robotics Academy, guiding robotics competitions and innovation. With a background in process modeling and control, he has held roles at the University of New South Wales and contributed significantly to medical and industrial research projects.

Research Interests 🔬

Professor Steven Su’s research focuses on the integration of advanced engineering principles with medical applications, particularly in wearable and portable monitoring devices, robotic modeling and control, and machine learning. His work explores the potential of smart sensing and the Internet of Things (IoT) to develop innovative solutions for healthcare, including rehabilitation robotics, AI-powered medical devices, and systems for personalized health monitoring. He is particularly interested in the modeling and control of systems used in wearable technologies, with a strong emphasis on medical AI and its application in rehabilitation robotics. Additionally, his research delves into biomedical signal processing and the development of intelligent systems for clinical environments. Professor Su has contributed to the advancement of AI-exoskeletons and other assistive technologies aimed at improving patient care, particularly for stroke survivors. His research bridges the gap between engineering, medical science, and technology, with a focus on improving healthcare outcomes.

Author Metrics 🏆

• Publications: Professor Su has authored numerous papers in journals like Int. J. Circuit Theory & Applications, International Journal of Advanced Robotic Systems, and Applied Soft Computing.
• Citations: His work on robotics, AI, and medical technologies has been cited widely within the research community.
• Editorial Roles: Associate Editor for International Journal of Advanced Robotic Systems (2017-2020), Editorial Member for Applied Soft Computing (2014-2017), and Editor for Int. J. Circuit Theory & Applications (2021-present).

Publications Top Notes 📚

1. Backstepping control of electro-hydraulic system based on extended-state-observer with plant dynamics largely unknown
   • Authors: Q Guo, Y Zhang, BG Celler, SW Su
   • Journal: IEEE Transactions on Industrial Electronics
   • Volume: 63, Issue: 11
   • Pages: 6909-6920
   • Year: 2016
   • Citation Count: 237
2. Investigation of window size in classification of EEG-emotion signal with wavelet entropy and support vector machine
   • Authors: H Candra, M Yuwono, R Chai, A Handojoseno, I Elamvazuthi, HT Nguyen, …
   • Conference: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
   • Year: 2015
   • Citation Count: 179
3. Nonlinear modeling and control of human heart rate response during exercise with various work load intensities
   • Authors: TM Cheng, AV Savkin, BG Celler, SW Su, L Wang
   • Journal: IEEE Transactions on Biomedical Engineering
   • Volume: 55, Issue: 11
   • Pages: 2499-2508
   • Year: 2008
   • Citation Count: 179
4. Identification and control for heart rate regulation during treadmill exercise
   • Authors: SW Su, L Wang, BG Celler, AV Savkin, Y Guo
   • Journal: IEEE Transactions on Biomedical Engineering
   • Volume: 54, Issue: 7
   • Pages: 1238-1246
   • Year: 2007
   • Citation Count: 167
5. Neural adaptive backstepping control of a robotic manipulator with prescribed performance constraint
   • Authors: Q Guo, Y Zhang, BG Celler, SW Su
   • Journal: IEEE Transactions on Neural Networks and Learning Systems
   • Volume: 30, Issue: 12
   • Pages: 3572-3583
   • Year: 2018
   • Citation Count: 152
6. Unsupervised machine-learning method for improving the performance of ambulatory fall-detection systems
   • Authors: M Yuwono, BD Moulton, SW Su, BG Celler, HT Nguyen
   • Journal: Biomedical Engineering Online
   • Volume: 11, Article Number: 1-11
   • Year: 2012 (Note: This seems to be a 2012 publication based on the context of other similar works)
   • Citation Count: 109