Rate My Professor Douglas Chai

Associate Professor Douglas Chai serves as the interim Executive Dean of the School of Engineering at Edith Cowan University, leading a diverse academic and professional team spanning electrical, mechanical, civil, chemical, energy, motorsports, and aviation disciplines. He supports strong performance across teaching, research, and engagement, while remaining actively involved in teaching to maintain close connections to student learning and program quality. Chai holds a PhD from The University of Western Australia (2000) and a BE (Hons) in Electrical and Electronic Engineering. As an active researcher, his work centers on image processing and pattern recognition, computer vision, and visual communications. He has authored over 100 publications, amassed more than 6,000 citations, achieved a Field-Weighted Citation Impact of 2.57, supervised 14 higher degree by research completions, secured two Australian Research Council Discovery Projects, and participated in multiple defence-funded collaborations.

Chai is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and a member of the Australian Institute of Company Directors (AICD). Over 24 years, he has contributed to various IEEE committees, chairing the IEEE Western Australia Section, the IEEE Signal Processing WA Chapter, and the IEEE ComSoc WA Chapter. In 2019, he received the IEEE WA Section Outstanding Volunteer Award. Notable publications include 'Review of deep learning methods in robotic grasp detection' (2018), 'Multimodal fusion for audio-image and video action recognition' (2024), 'Structure-aware image translation-based long future prediction for predictive control of autonomous ground vehicles' (2023), 'A dataset of audio-image representations for multimodal human action recognition' (2024), 'Feature-based panoramic image stitching' (2017), and 'Barcodes for Mobile Devices' (2010). His research influences advancements in robotics, autonomous navigation, and multimodal recognition, underscored by substantial citation metrics and funded projects.