Rate My Professor Stephen So

Stephen So is a Senior Lecturer in Electrical and Electronic Engineering within the School of Engineering and Built Environment at Griffith University's Gold Coast campus. He earned his BEng degree with First Class Honours in Microelectronic Engineering from Griffith University in 1999 and his PhD in image processing from the School of Microelectronic Engineering at the same institution in 2005. Born in Hong Kong in 1977, Dr. So's academic career has been centered at Griffith University, where he began as a PhD candidate in the Signal Processing Lab from 2000 to 2005. His research specializations include digital signal processing, image and speech coding, speech signal enhancement and noise reduction, distributed speech recognition, ECG signal processing, machine learning, and deep neural networks. He is actively involved in applying signal processing and deep learning techniques to swallow sounds in children for detecting aspiration and dysphagia. Dr. So teaches courses focused on signal processing, programming, high performance computing, and numerical methods, convening several of these programs. He supervises research students and has contributed to funded projects, including one valued at $18,780 from the School of Engineering and Built Environment.

Dr. So's scholarly impact is evidenced by over 912 citations on Google Scholar, with an emphasis on practical applications of advanced signal processing techniques. Key publications include 'A Comprehensive Review of Deep Learning-Based Crack Detection: Approaches, Implementation Strategies, Datasets and Benchmarks' (Applied Sciences, 2022, cited over 200 times), 'Deep Learning for Real-time ECG R-peak Prediction' (2020), 'Kalman Filter with Sensitivity Tuning for Improved Noise Reduction' (Circuits, Systems, and Signal Processing, 2017, cited 27 times), 'Using an Automated Speech Recognition Approach to Differentiate Between Normal and Aspirating Swallowing Sounds Recorded from Digital Cervical Auscultation in Children' (Dysphagia, 2022), and 'Efficient Product Code Vector Quantisation Using the Structured Residual Vector Quantiser' (Signal Processing, 2005). He maintains an ORCID identifier 0000-0003-1004-3285 and engages in professional activities such as IEEE involvement. His work advances engineering solutions in biomedical signal analysis and structural health monitoring.