Supervisor: Prof. Mohammad-R. Akbarzadeh-T
Education: PhD in  Electrical Engineering
Contact: Faculty of Engineering, Ferdowsi University of Mashhad, Iran
Email: akbarzadeh {AT} ieee.org
akbazar {AT} ferdowsi.um.ac.ir
Phone: +98 (51) 3880-5010
Personal Website

Research Interest:Bio-inspired computing/optimization/control, soft computing, multi-agent systems and distributed AI, uncertain and complex systems, robotics, cognitive sciences, medical informatics, and biomedical engineering systems.

Selected Research Papers:  Expert Knowledge and Uncertain Knowledge bases in Data Mining, Cognitive Decision Making and Rule Discovery

Selected Journals Papers:
1- Nasibeh Rady Raz, Mohammad-R. Akbarzadeh-T., Alireza Akbarzadeh,, "Experiment-based affect heuristic using fuzzy rules and Taguchi statistical method for tuning complex systems," Expert Systems with Applications,Vol. 172, 2021.

2- Samane Sharif &Mohammad-R. Akbarzadeh-T, "Distributed Probabilistic Fuzzy Rule Mining for Clinical Decision Making,"Fuzzy Information and Engineering , Vol. 13, Num. 4, pp. 436-459, 2021.
3- Mahnaz Kadkhoda, Mohammad-R. Akbarzadeh-T, "Associative Classifier using Extended Fuzzy System,"Tabriz Journal of Electrical Engineering, 2021.

4- E. Adel-Rastkhiz and M. -R. Akbarzadeh-T, "A Specificity-Based Approach to Semantic Interpretation and Hierarchical Complexity Reduction in Fuzzy Models," in IEEE Transactions on Fuzzy Systems, vol. 29, no. 9, pp. 2661-2674, Sept. 2021.

5- M. Kadkhoda, M. -R. Akbarzadeh-T. and F. Sabahi, "FLeAC: A Human-Centered Associative Classifier Using the Validity Concept," in IEEE Transactions on Cybernetics, vol. 52, no. 6, pp. 4234-4245, June 2022.

6- Alireza Bemani-N., M.-R. Akbarzadeh-T., "A hybrid adaptive granular approach to Takagi–Sugeno–Kang fuzzy rule discovery," Applied Soft Computing, Vol. 81, 2019.
7- Mahnaz Kadkhoda, Mohammad-R. Akbarzadeh-T, S. Mahmoud Taheri, "Mining Fuzzy Temporal Itemsets Within Various Time Intervals In Quantitative Datasets," Iranian Journal of Fuzzy Systems, Vol. 13, No.7, pp. 67-89, 2016.
8-Azadeh Soltani, and M. -. Akbarzadeh-T, "A new tree-based approach for evaluating rule antecedent constraint in confabulation based association rule mining," International Journal of Knowledge-Based and Intelligent Engineering Systems, Vol. 19, No. 1, pp. 1-14, 2016.

9-Azadeh Soltani, and M. -. Akbarzadeh-T., "Confabulation-Inspired Association Rule Mining for Rare and Frequent Itemsets," in IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 11, pp. 2053-2064, Nov. 2014.