Md Rakibul Ahasan
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Md Rakibul Ahasan

Md Rakibul Ahasan received his B.S. degree in Electronics and Telecommunication Engineering from the Rajshahi University of Engineering and Technology, Bangladesh in 2011, M.S. degree in Computer Science and Engineering from the BRAC University, Bangladesh in 2022, and a second M.S. degree in Electrical and Computer Engineering from Miami University, Oxford, Ohio in 2024.


From 2012 to 2022, he worked as a Machine Learning Engineer with extensive experience in telecommunications and network operations at Robi Axiata Ltd. Bangladesh. He developed a machine learning-based anomaly detector for telecom network performance data. He played a pivotal role in transforming legacy systems into advanced frameworks and developing automated network inventory discovery solutions.


His research interests include data driven cyber-attack detection in cyber physical system (electric vehicle and water distribution system ), optimization, anomaly detection, and machine learning. He is a currently pursuing PhD in electrical engineering under Dr. Abdulrahman Takiddin at Florida State University.


Contact Information:

Publications

  1. M.R. Ahasan, SR Fahim, Rachad Atat, Abdulrahman Takiddin “A Graph-Based Optimization Approach for Resilient EV Rerouting in Disrupted Charging Networks,” in Proc. 2026 IEEE 23rd Consumer Communications & Networking Conf. (CCNC), Las Vegas, Nevada, USA, 2026.
  2. M.R. Ahasan, F Joad, R Atat, C Thompson, E Serpedin, A Takiddin, “Graph Transfer Learning-Based Attack Detection in Cyber-Physical Water Distribution Systems,” in Proc. 2025 European Signal Processing Conf. (EUSIPCO), Palermo, Italy, 2025.
  3. M.R. Ahasan, SR Fahim, A Takiddin, “Securing EVCS Infrastructure Against Cyberattacks with a Deep Learning-Based Detection Model,” in Proc. 2025 10th Int. Conf. on Fog and Mobile Edge Computing (FMEC), 2025.
  4. M.R. Ahasan, “A Multi-Objective Public Bus Smart Window Management System (SWMS) Considering Energy Efficiency and Passenger Comfort,” Miami University, 2023.
  5. M.R. Ahasan, MF Momen, MS Haque, MR Akram, GR Alam, MZ Uddin, “Benchmarking Unsupervised Machine Learning for Mobile Network Anomaly Detection,” in Proc. 2022 Int. Conf. on Innovations in Science, Engineering and Technology, 2022.
  6. M.R. Ahasan, MS Haque, MR Akram, MF Momen, MGR Alam, “Deep Learning Autoencoder Based Anomaly Detection Model on 4G Network Performance Data,” in Proc. 2022 IEEE World AI IoT Congress (AIIoT), 2022, pp. 232–237.
  7. M.R. Ahasan, MS Haque, MGR Alam, “Supervised Learning Based Mobile Network Anomaly Detection from Key Performance Indicator (KPI) Data,” in Proc. 2022 IEEE Region 10 Symposium (TENSYMP), 2022, pp. 1–6.
  8. M.R. Ahasan, “3G and 4G Paging Success Rate Based Mobile Network Anomaly Detection Using Supervised and Unsupervised Learning,” Brac University, 2022.