Rate My Professor Suhuai Luo

Associate Professor Suhuai Luo serves as an associate professor in information technology at the University of Newcastle, within the School of Electrical Engineering and Computing in the College of Engineering, Science and Environment. He earned his Bachelor and Master degrees in Electrical Engineering from Nanjing University of Posts and Telecommunications, followed by a PhD in Electrical Engineering from the University of Sydney. His career history includes positions as a senior research scientist at CSIRO in Australia and researcher at the Bioinformatics Institute, A*STAR in Singapore. Luo's research specializations encompass image processing, computer vision, machine learning, cyber security, and media data mining, applied to areas such as medical imaging for computer-aided diagnoses, computer vision for intelligent driving systems, and machine learning for cybersecurity.

He has obtained competitive grants including an ARC Linkage grant, an ARC Discovery grant, and a CSIRO Flagship Project. Luo has authored over 150 journal and conference papers, with key publications such as 'A survey on machine learning techniques for cyber security in the last decade' (2020), 'Deep sequence modelling for Alzheimer's disease detection using MRI' (2021, Ebrahimi A, Luo S, Chiong R), 'Automated detection of pneumoconiosis with multilevel deep features learned from chest X-Ray radiographs' (2021, Devnath L, Luo S, Summons P, Wang D), 'Convolutional neural networks for Alzheimer's disease detection on MRI images' (2021), and 'A Review of Time-Series Anomaly Detection Techniques: A Step to Future Perspectives' (2021, Shaukat K et al.). His work has achieved over 10,967 citations on Google Scholar, with an h-index of 56. He has supervised more than 30 honours and Master's students and 22 PhD students. Luo has acted as Special Issue Editor for Applied Sciences (2021-2022), reviewer for ARC grants (2021), and programme committee member for more than 40 conferences. He delivered keynote speeches including 'Automatic Alzheimer’s Disease Recognition from MRI data Using Deep Learning Method' (2017), 'A novel level set segmentation algorithm for computer-aided hepatic surgical planning' (2016), and 'Automatic Liver Segmentation from CT Images by Combining Statistical Models with Machine Learning' (2014). He is Co-Lead in the Health and society area of the Centre for Applied and Responsible AI.