Rate My Professor Fung Ting

Dr. Ting's academic interests center on deep learning for medical image analysis and bio data analysis, expert systems for computer-aided detection, and biomedical engineering encompassing telehealth and medical imaging. Her key publications include 'Convolutional neural network improvement for breast cancer classification' in Expert Systems with Applications (2019), which addresses automated classification and segmentation of breast cancer lesions; 'Case-control comparison brain lesion segmentation for early infarct detection' in Computerized Medical Imaging and Graphics (2018); 'RCS-YOLO: A fast and high-accuracy object detector for brain tumor detection' (2023); 'Implementing a successful Collaborative Active Learning approach in information technology discipline' (2022); and 'ASF-YOLO: A novel YOLO model with attentional scale sequence fusion for cell nuclei instance segmentation' among others. She has garnered significant recognition, including Champion Awards at the World Summit on the Information Society (WSIS) Prizes in 2020 and 2019 for her research projects, the 2023 FIT Dean's Education Excellence Awards, Highly Commended Award by The IET Innovation Awards 2018, Merit Award at the International APICTA Awards 2017, and the 2017 Best Master Thesis Award. Her career history features roles as Consultant (Software Engineering) at Choy Engineering (Soon Seng) Sdn Bhd (2019-2020), Graduate Research Assistant at Multimedia University (2017-2019), and Research Scholar at Telekom Malaysia Research and Development (2015-2017). Dr. Ting currently serves as Primary Chief Investigator on projects such as RewardQNet for untreated intracranial aneurysm segmentation (2022-2026) and a comprehensive end-to-end intelligent platform for brain tumor diagnosis, treatment, and recurrence monitoring (2025-2027), contributing to advancements in biomedical machine learning.