العربية
Dr Sanad Al Maskari
Biography
Dr Sanad is an Assistant Professor at the Faculty of Computing and Information Technology at Sohar University. He has more than a decade experience in the academic field. Prior to academia he worked as a software developer and research assistance in the University of Queensland. His experience in teaching, research and industry equip him with essential skills to advance science and technology. He holds a Ph.D. in machine learning and data mining from the University of Queensland Australia. He holds a B.Sc. and M.Sc. from Queensland University of Technology, Australia. He acquired his Postgraduate Certificate in Teaching in Higher Education (PGCTHE) from Edge Hill University, UK.
With more than 10 years of experience in teaching, research and supervising undergraduate and postgraduate students, his major research interests focus in the fields of Artificial Intelligence (AI), Machine Learning, and Data Mining – specifically in Machine Vision, Machine Olfaction, Smart Sensing, and Deep Learning. His other research areas of interest include Education, Social Computing, and the Fourth Industrial Revolution. He has made various contributions in the field of machine learning including AI based drift compensation methods for e-nose sensors, sentiment analysis and image recognition.
Dr Sanad has published in many research papers in various reputable conferences including Knowledge Discovery and Data Mining (PAKDD), Australasian Database Conference (ADC) and various reputable journals. He has authored various book chapters in the field of machine learning and smart sensing published by Taylor & Francis and IGI Global. Part of his commitment to research Dr Sand is has served as a peer reviewer in various reputable journals and research funding bodies. In addition he has been contributing in the organization of various conferences including Sohar University Teaching and Learning Conference.
Dr Sanad is committed in improving the teaching and learning experience for the students. He has more than a decade experience in program development, curriculum design, and education quality management. He server as a member in the university teaching and learning committee, quality committee and an active member in the Center of Education Development (CED). He is involved in program development and enhancement process at the university. During his career he designed and developed various courses including pattern recognition, data mining, ERP, cloud computing, mobile application, and others.
As a recognition for his commitment and passion to teaching, Dr Sanad was awarded the Vice Chancellors Outstanding Teaching Award for the academic year 2019-2020. His dedication to the continuous improvement of teaching and learning is unwavering.
Beside his teaching and research Dr Sanad is a program coordinator for the Business Information Technology program at the faculty of computing and Information Technology. He is the chairman for the university Information Service Committee and acting member in university teaching and learning committee, Centre for Educational Development, and an active member in the university ethics committee.
Dr Sanad is committed to fostering academic growth and research development. He has supervised Ph.D., Master’s and undergraduate students and guided them through their research journey. He has been awarded various research grants and currently involved in a number of external research projects. His experience in the computer science field especially machine learning, AI, pattern recognition, data mining, data analytics and IoT is essential for the execution and delivery of these projects.
In short, Dr Sanad has almost a decade of experience in teaching, research, project management, strategy planning, leadership, research collaboration, research funding, and project implementation. He has gained a wide range of important skills in these areas. He uses his skills to advance scientific understanding, encourage innovation, and help students do well in school.
Qualification
- Ph.D. in Computer Science, University of Queensland, Australia, 2018.
- Masters in Information Technology, Queensland University of Technology, Australia, 2007.
- Bachelors in Information Technology (Software & Data communication), Queensland University of Technology, Australia, 2006.
Teaching Interest
- Data mining
- Pattern Recognition
- AI, Robotics
- Software Development
- Mobile Applications
Research Interest
- Big Data
- Data mining
- Robotics
- Machine Learning
- Artificial intelligence specifically in machine olfaction, sensor data and environment monitoring
- Information Security
- Virtual Reality
- Social Computing
Publications
- Al-Maskari, S., Ibrahim, I. A., Li, X., Abusham, E., & Almars, A. (2018, May). Feature extraction for smart sensing using multi-perspectives transformation. In Australasian Database Conference (pp. 236-248). Springer, Cham.
- Al Maskari, S., & Li, X. (2018). E-nose pattern recognition and drift compensation methods. In Electronic Nose Technologies and Advances in Machine Olfaction (pp. 38-57). IGI Global.
- Al-Maskari, S., Zia, K., Muhammad, A., & Saini, D. K. (2018, August). Impact of Mobility Mode on Innovation Dissemination: An Agent-Based Simulation Modeling. In International Conference on Simulation of Adaptive Behavior (pp. 3-14). Springer, Cham.
- Albarrak, A., Al-Maskari, S., Ibrahim, I. A., & Almars, A. M. (2018, November). Efficiently Mining Constrained Subsequence Patterns. In International Conference on Advanced Data Mining and Applications (pp. 3-16). Springer, Cham.
- Al-Maskari, S., Bélisle, E., Li, X., Le Digabel, S., Nawahda, A., & Zhong, J. (2016, April). Classification with quantification for air quality monitoring. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 578-590). Springer, Cham.