Dr Sina Abdipoor

Dr Sina Abdipoor

  • Lecturer
  • School of Computing and Artificial Intelligence
Faculty of Engineering and Technology
SDGs Focus

Biography

Mr Sina Abdipoor is a lecturer affiliated with the Department of Data Science and Artificial Intelligence at ºìÐÓÊÓƵ University. His primary research interest lies in Operations Research (OR), where he specialises in utilising metaheuristics to address various optimisation problems. Currently, his research efforts are concentrated on the application of hybrid approaches for tackling real-world scheduling problems. 

In addition to his active role, he serves as a reviewer for Elsevier's Journal of Expert Systems with Applications and Intelligent Systems with Applications, as well as IEEE Access. Since 2016, he has pursued his passion for teaching, sharing his knowledge in various Computer Science subjects as well as General English and Academic English Writing. 

Beyond academia, he has extensive experience working as an AI Engineer and consultant in various domains. He frequently discusses the applications of OR theory in real-world problems to save time and improve efficiency. He is an active member of the Canadian Operational Research Society and is passionate about advancing AI and its practical applications.

Academic & Professional Qualifications

  • Ph.D. Artificial Intelligence, Universiti Putra Malaysia (2026)
  • MSc. Artificial Intelligence, K. N. Toosi University of Technology (2019)
  • BSc. Software Engineering, Imam Khomeini International University (2016)

Research Interests

  • Artificial Intelligence
  • Operations research
  • Optimization
  • Evolutionary Computing
  • Machine Learning

Teaching Areas

  • Artificial Intelligence/Data Science
  • Optimization/Search Algorithms
  • Evolutionary Computing/Metaheuristics
  • Computer Science/Programming
  • Machine Learning/Reinforcement Learning

Notable Publications

  1. Abdipoor, S., Yaakob, R., Goh, S. L., & Abdullah, S. (2023). Meta-heuristic approaches for the university course timetabling problem. Intelligent Systems with Applications, 19, 200253.
  2. Abdipoor, S., Yaakob, R., Goh, S. L., Abdullah, S., Hamdan, H., & Kasmiran, K. A. (2025). Optimality vs. Generality: Performance Assessment of Meta-heuristics in Educational Timetabling. IEEE Access.
  3. Ghafouri, S., Abdipoor, S., & Doyle, J. (2023, September). Smart-Kube: energy-aware and fair kubernetes job scheduler using deep reinforcement learning. In 2023 IEEE 8th International Conference on Smart Cloud (SmartCloud) (pp. 154-163). IEEE.
  4. Wang, H., Cai, Y., Yue, F., Luo, H., Abdipoor, S., & Goh, S. L. (2024, October). Digital Twin System for Smart Campuses. In 2024 IEEE International Conference on Control Science and Systems Engineering (ICCSSE) (pp. 75-80). IEEE.
  5. Abdipoor, S., Yaakob, R., Goh, S. L., Abdullah, S., Kasmiran, K. A., & Hamdan, H. (2023, June). International timetabling competition 2019: A systematic literature review. In 2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) (pp. 22-27). IEEE.
  6. Hao, L., Abdipoor, S., Qing, L., & Litao, X. (2024, March). Hybrid graph neural networks with LSTM attention mechanism for recommendation systems in MOOCs. In 2024 20th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) (pp. 63-68). IEEE.
     

Achievements & Accolades

2024

  1. Representing Universiti Putra Malaysia (UPM) at the National Level of the Three Minute Thesis (3MT) Competition (Universiti Kebangsaan Malaysia)
  2. Winners of the 3MT Competition (UPM)
  3. Best Paper Award (CSPA2024)

2023

  1. Special Jury Award at the Postgraduate (Ph.D.) Colloquium (UPM)

Professional Associations

  1. Active Member of the Canadian Operational Research Society