Dr Faris Syahmi Samidi

Dr Faris Syahmi Samidi

  • Lecturer
Department of Data Science and Artificial Intelligence
SDGs Focus

Biography

Dr Faris Syahmi Samidi holds a PhD from Universiti Tenaga Nasional in Engineering. His expertise lies in 5G networks, reinforcement learning, and spectrum optimization. He has been actively involved in research and industry projects, particularly in AI-driven network optimization and data analytics for utilities. Previously, he was an adjunct lecturer at MJIIT, Universiti Teknologi Malaysia, teaching Mobile and Internet Programming. His research interests extend to smart grids, big data applications, and emerging technologies in wireless communications. He welcomes collaboration opportunities to drive impactful research and innovation.

Academic & Professional Qualifications

  • PhD in Engineering, Universiti Tenaga Nasional (2025)
  • BEEE, Universiti Tenaga Nasional (2019)

Research Interests

  • Machine Learning; Reinforcement Learning
  • 5G Wireless; Optical Communication
  • Smart Grid; Distribution Network Communication
  • Artificial Intelligent and Big Data Analytics

Teaching Areas

  • Network and Communication
  • Database
  • Mobile and Web Development
  • Software Development

Courses Taught

  • Mobile Application Development
  • Internet Programming

Notable Publications

2024 -

F. S. Samidi, N. A. M. Radzi and N. M. Aripin, "Reinforcement Learning Model Selection for Resource Allocation and Subcarrier Spacing Optimization in 5G Sliced Spectrum Networks," 2024 IEEE International Conference on Applied Electronics and Engineering (ICAEE), Shah Alam, Malaysia, 2024, pp. 1-6. 

2023 -

I. T. Zulkifli, N. A. M. Radzi, N. M. Aripin, K. H. M. Azmi, F. S. Samidi and N. A. Azhar, "Classification of Hospital of the Future Applications using Machine Learning," 2023 IEEE 13th Symposium on Computer Applications & Industrial Electronics (ISCAIE), Penang, Malaysia, 2023, pp. 13-17. 

2023 -

N. A. Azhar et al., "Selecting Communication Technologies for an Electrical Substation Based on the AHP," in IEEE Access, vol. 11, pp. 110724-110735, 2023. 

2022 -

Samidi, F.S.; Mohamed Radzi, N.A.; Mohd Azmi, K.H.; Mohd Aripin, N.; Azhar, N.A. 5G Technology: ML Hyperparameter Tuning Analysis for Subcarrier Spacing Prediction Model. Appl. Sci. 2022, 12, 8271. 

2022 -

K. H. Mohd Azmi, N. A. Mohamed Radzi, N. A.  Azhar, F. S. Samidi, I. Thaqifah Zulkifli and A. M. Zainal, "Active Electric Distribution Network: Applications, Challenges, and Opportunities," in IEEE Access, vol. 10, pp. 134655-134689, 2022. 

2021 -

F. S. Samidi, N. A. M. Radzi, W. S. H. M. W. Ahmad, F. Abdullah, M. Z. Jamaludin and A. Ismail, "5G New Radio: Dynamic Time Division Duplex Radio Resource Management Approaches," in IEEE Access, vol. 9, pp. 113850-113865, 2021. 

Achievements & Accolades

  1. Development of Resource Allocation and Subcarrier Spacing Optimization in 5G Sliced Spectrum Networks Using Reinforcement Learning with DTDD INI Model and Machine Learning.  (Copyright Reference: DV2023W06382)
  2. User Interface for Communication Technology Selection in Distribution Substation.  (Copyright Reference: LY2022W02791)
  3. Hybrid Multi-criteria Decision-Making algorithm for Communication System Selection for 11kV substation.  (Copyright Reference: LY2021W00705)
  4. 5G Adaptive Learning for Dynamic Time Division Duplex Method.  (Copyright Reference: LY2021W01898)