Rate My Professor Zeyad Khalifa

Zeyad Khalifa serves as Associate Lecturer in the School of Information Technology at Murdoch University, which falls under the College of Science, Technology, Engineering and Mathematics. He is an academic and researcher specializing in computer vision, machine learning, and robotics, with a focus on visual affordance understanding using RGB-D data. Additionally, he is associated with University Preparation Pathways. Holding a Bachelor of Science, Khalifa contributes to the institution's research and educational missions through his expertise in these areas.

In research, Khalifa has produced key conference papers in prominent international forums. He co-authored 'A Large Scale Multi-View RGBD Visual Affordance Learning Dataset' with Syed Afaq Ali Shah, published in the proceedings of the 2023 IEEE International Conference on Image Processing (ICIP) in Kuala Lumpur, Malaysia. The same collaborators produced 'Hierarchical Transformer for Visual Affordance Understanding using a Large-scale Dataset' for the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). He also contributed to 'Towards Visual Affordance Learning: A Benchmark for Affordance Segmentation and Recognition' in 2022. These works advance understanding in visual affordance for robotics and AI applications. In his teaching role, Khalifa oversees the certification component of the ICT298 – IT Certification Pathways unit in the School of IT and University Preparation Pathways. Offered across two semesters with capped enrolments, the unit integrates industry-recognized certification pathways via a partnership with Prodigy Learning, addressing rising demand for practical credentials while upholding high standards and broadening student access.