Dr Essa Anas
Essa teaches various subjects in the UG and PG Mechatronics and Intelligent Machines courses. With particular expertise in artificial intelligence and deep learning, Essa's industrial experience in I4.0 allowed us to provide a very successful module in the PG. Essa also supervises postgraduate projects on the UG and PG MIM. He is also a Nvidia Deep Learning Institute Certified Instructor and Nvidia Jetson AI Ambassador, and he has run many industrial AI and Machine Learning workshops.
Essa has published his work mainly in Machine Learning and Deep Learning in different fields. For instance, he published his work in medical applications using Deep Learning. Also, in-depth estimation for autonomous navigation. Essa also published work in Eyes-Computer interaction, among many other publications.
Mr. Anas has been the course leader for Mechatronics and Intelligent Machines since 2019. He is responsible for student application approvals for full-time, part-time, and top-up applications. He is also the course leader of the EEE in SEGi (Malaysia) and is responsible for course-related activities within these courses.
Essa has organised several significant academic and industrial events over the years, including workshops, clubs, and other events for PG and UG students. For instance, he is organising industrial trips to different industrial partners. Also, he organises workshops in deep learning and Natural Language Processing with the collaboration of Nvidia. He is also organising clubs for robotics arms, autonomous navigations, and robotics simulations.
- Ph.D. Computer Vision and Deep Learning
- M.Sc. in Digital Signal and Image Processing
- M.SC. in Electronics Engineering
- B.Sc. in Electrical Engineering
- Machine Learning
- Deep Learning
- Reinforcement Learning
- Industry 4.0
- Associate Fellow of the Higher Education Academy
Publications
- “CT scan Registration with 3D Dense Motion Field Estimation Using LSGAN”, In MIUA 2020, the University of Oxford, 15th-17th July 2020.
- “Scene disparity estimation with convolutional neural networks,” In SPIE Optical Metrology, 25-27 June 2019, Munich, Germany.
- “Dynamic State Recognition Using CNN-RNN Processing Pipeline,” International Journal of COMADEM, 21(3), 2018.
- “Online Eye Status Detection in the Wild with Convolutional Neural Networks,” 12th International Conference on Computer Vision Theory and Applications, VISAPP’17, 2017.
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