Dr. Maath Alani is a Research Fellow at the Australian Institute for Bioengineering and Nanotechnology (AIBN) at the University of Queensland. His focus is centered in the field of image processing, artificial intelligence, and visualization, and he is currently developing a pipeline to analyze cellular phenotypes in 3D tissues as well as implementing machine learning techniques in organoid biology, which have the potential to foster drug screening in preclinical settings.

Dr. Maath Alani first obtained his  master's degree in the field of image processing from the Faculty of Computer Science and Information Technology, University of Malaya. He developed a new approach for detecting man-made objects based on a hybrid technique having a combination of two features, which were texture-based and shape-based techniques. The hybrid technique has shown that it can detect the desired objects more accurately and efficiently. The generated algorithm of his research could be applied in many fields, such as robotics, automatic navigation, virtual reality, image indexing, bioinformatics, and others.

Then, Dr. Maath Alani carried out his PhD at the Institute of Visual Informatics at the National University of Malaysia to develop an artificial intelligence-based learning application tool named Gesture Recognition Application for the Deaf and Hard of Hearing (GRA-DHH) using machine learning and Natural User Interface (NUI). The study included analyzing recorded data of groups of students using machine learning techniques to observe and facilitate the learning of children with learning disabilities caused by a disease named dyslexia and dysgraphia. This promoted the development and implementation of intelligent interactive learning applications using 3D interactive devices such as the Kinect camera.

Key Publications

  1. Maath Alani, Hasan Kahtan, Wan Nor Ashikin Wan Ahmad Fatthi (2021). Effective use of NUI/UX Design in Gesture Recognition Learning Application for Deaf and Hard of Hearing (D/HH). INTERNATIONAL EXHIBITION & SYMPOSIUM ON PRODUCTIVITY, INNOVATION, KNOWLEDGE & EDUCATION.
  2. Kahtan, H., Awang, S. B., Kadir, T. A. B. A., Abdulghafoor, M. S., & Shamsuri, T. S. S. B. T. (2018). Motion Analysis-Based Application for Enhancing Physical Education. Advanced Science Letters, 24(10), 7668-7674.
  3. Abdulghafoor, M., Ahmad, A., & Huang, J.-Y. (2015). Survey on the Use of Applications for Deaf and Hard Hearing Literacy. Paper presented at the International Conference on Computer, Communication, and Control Technology, 2015 Kuching, Sarawak. IEEE
  4. Abdulghafoor, M., Ahmad, A., & Huang, J.-Y. (2015). Literacy Sign Language Application Using Visual Phonics: A Theoretical Framework. International Journal of Web-Based Learning and Teaching Technologies.
  5. Abdulghafoor, M., Ahmad, A., & Huang, J.-Y. (2015). Assistive Malaysian Sign Language Application for D/HH learning using Visual Phonics. 4th International Visual Informatics Conference 2015 (IVIC'15). Springer International Publishing Switzerland