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Farhad Rahdari (Assistant professor)

صفحه فارسی

Institute of Information Technology and Computer / Department of Computer and Information Technology
  • Email: farhadr [AT] kgut.ac.ir
  • Resume: CV
 

Biography

Farhad Rahdari received his B.Sc. and M.Sc. degrees in computer engineering from the Faculty of Computer Engineering, Iran University of Science & Technology (IUST), Tehran, Iran in 2000 and 2007. He also got his Ph.D. degree in computer engineering from the Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran in 2023.



Research Interests

Resource Management in Cellular Networks, QoE Management, and Intelligent Networks.

Journals

  1. Rahdari, F., & Sheikh-Hosseini, M. (2024). Nonlinear symbolic regression for bit error rate prediction of NOMA systems in 5G cellular communications. Engineering Applications of Artificial Intelligence, 127, 107344. doi: 10.1016/j.engappai.2023.107344

  2. Rahdari, F., Khayyambashi, M. R., & Movahhedinia, N. (2023). QoE-aware NOMA user grouping in 5G mobile communications using a multi-stage interval type-2 fuzzy set model. Ad Hoc Networks, 103227. doi: 10.1016/j.adhoc.2023.103227

  3. Sheikh‐Hosseini, M., Hasheminejad, M., & Rahdari, F. (2023). Linear precoder design for peak‐to‐average power ratio reduction of generalized frequency division multiplexing signal using gradient descent methods. Transactions on Emerging Telecommunications Technologies, 34(2), e4698. doi: 10.1002/ett.4698

  4. Rahdari, F., Khayyambashi, M. R., & Movahhedinia, N. (2022). A QoE-Aware Nonlinear Fuzzy Radio Resource Management Approach for Revenue Enhancement. IEEE Systems Journal. doi: 10.1109/JSYST.2022.3210324

  5. Rahdari, F., Movahhedinia, N., Khayyambashi, M. R., & Valaee, S. (2021). QoE-aware power control and user grouping in Cognitive Radio OFDM–NOMA systems. Computer Networks, 189, 107906. doi: 10.1016/j.comnet.2021.107906

  6. Rahdari, F., Rashedi, E., & Eftekhari, M. (2019). A multimodal emotion recognition system using facial landmark analysis. Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 43, 171-189. doi: 10.1007/s40998-018-0142-9

  7. Mousavi, R., Eftekhari, M., & Rahdari, F. (2018). Omni-Ensemble Learning (OEL): Utilizing Over-Bagging, Static and Dynamic Ensemble Selection Approaches for Software Defect Prediction. International Journal on Artificial Intelligence Tools, 27(06), 1850024. doi: 10.1142/S0218213018500240

  8. Ghaemi, A., Rashedi, E., Pourrahimi, A. M., Kamandar, M., & Rahdari, F. (2017). Automatic channel selection in EEG signals for classification of left or right hand movement in Brain Computer Interfaces using improved binary gravitation search algorithm. Biomedical Signal Processing and Control, 33, 109-118. doi: 10.1016/j.bspc.2016.11.018

  9. Rahdari, F., Eftekhari, M., & Mousavi, R. (2016). A two-level multi-gene genetic programming model for speech quality prediction in Voice over Internet Protocol systems. Computers & Electrical Engineering, 49, 9-24. doi: 10.1016/j.compeleceng.2015.10.008

  10. Rahdari, F., Eftekhari, M., Akbari, A., & Zeinalkhani, M. (2014). Developing Fuzzy Models for Estmating the Quality of VoIP. Iranian Journal of Fuzzy Systems, 11(1). doi: 10.22111/ijfs.2014.1395


Conferences

  1. Rahdari, F., Mousavi, R., & Eftekhari, M. (2014, October). An ensemble learning model for single-ended speech quality assessment using multiple-level signal decomposition method. In 2014 4th International Conference on Computer and Knowledge Engineering (ICCKE) (pp. 189-193). IEEE. doi: 10.1109/ICCKE.2014.6993412

  2. Rahdari, F., & Eftekhari, M. (2012, May). Using Bayesian classifiers for estimating the quality of VoIP. In The 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP 2012) (pp. 348-353). IEEE. doi: 10.1109/AISP.2012.6313771

  3. Rahdari, F., & Eftekhari, M. (2011). Developing Fuzzy Models for estimating quality of VOIP using a hybrid of GA and Neuro-Fuzzy. In Proc. the 2nd Int. Conferences on Contemporary Issues in Computer and Information Sciences (CICIS), Iran. doi:

  4. Rahdari, F., & Eftekhari, M. (2011, October). Modeling the perceived voice quality for VOIP system based on Neuro-fuzzy: A comparative study. In 2011 1st International eConference on Computer and Knowledge Engineering (ICCKE) (pp. 60-65). IEEE. doi: 10.1109/ICCKE.2011.6413325


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