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Research Opportunities ...
Opportunity for MS/PhD study with a full scholarship is available at the Department of Electrical and Computer Engineering, College of Science and Engineering, Idaho State University, Idaho Falls, ID, USA. Research directions include (but not limited to): IoT Security and Privacy; Privacy-Preserving Machine Learning; Smart Health Care Security and Privacy; and 6G Communications. Requirements include: (1) Master's degree in Computer Science, Computer Engineering, Applied Math or a related discipline; (2) High GPA; (3) Good programming and mathematical analysis/optimization skills; and (4) Good TOEFL/IELTS and GRE scores (given the candidate has already taken the tests).
Interested students, please send your CV, transcript(s), and your English proficiency scores to: email@example.com
Potential candidate(s) will be contacted for an interview over Zoom, particularly for verifying domain knowledge in the undergraduate project and/or Masters thesis, and programming skills.
Note: Applicants not fulfilling the aforementioned requirements will be deemed not serious, and will not be responded to.
Paper accepted: IEEE Access [Q1, IF: 3.745], “New Color Image Zero-Watermarking Using Orthogonal Multi-Channel Fractional-Order Legendre-Fourier Moments”.
Paper accepted: IEEE Internet of Things Journal [Q1, IF: 9.936], “Privacy-Preserving and Efficient Data Collection Scheme for AMI Networks Using Deep Learning”.
Paper accepted: IEEE Internet of Things Journal [Q1, IF: 9.936], “Detection of False-Reading Attacks in Smart Grid Net-Metering System”.
Paper accepted: IEEE Transactions on Green Communications and Networking, “UV-CDS: On-Premises Energy-Efficient Scheduling of Ultraviolet-C Drone-based Sterilization to Combat COVID-19”.
Editor: IEEE Transactions on Vehicular Technology (Impact Factor: 5.379).
Paper accepted: IEEE Access [Q1, IF: 3.745], “Robust Color Images Watermarking Using New Fractional-Order Exponent Moments”.
Paper accepted: ISNCC 2021, “Countering Presence Privacy Attack in Efficient AMI Networks Using Interactive Deep-Learning”.
Award: 2021 CAES Summer Visiting Faculty Program (CSVFP). Hosted by Center for Advanced Energy Studies (CAES), Idaho Falls, ID, USA. In collaboration with Idaho National Laboratory, Idaho Falls, ID, USA.
Paper accepted: IEEE Access [Q1, IF: 3.745], “A New Image Encryption Algorithm for Grey and Color Medical Images”.
Guest Editor: IEEE Wireless Communications special issue on “Smart, Optimal, and Explainable Orchestration of Network Slices in 5G and Beyond Networks”.
Paper accepted: IEEE Access [Q1, IF: 3.745], “A Proof-of-Concept of Ultra-Edge Smart IoT Sensor: A Continuous and Lightweight Arrhythmia Monitoring Approach”.
Paper accepted: IEEE ICC 2021, “On COVID-19 Prediction Using Asynchronous Federated Learning-Based Agile Radiograph Screening Booths”.
Paper accepted: IEEE ICC 2021, “Noise-Removal from Spectrally-Similar Signals Using Reservoir Computing for MCG Monitoring”.
Paper accepted: IEEE ICC 2021, “Wi-Fi Assisted Two-Hop Relay Probing in WiGig Device to Device Networks”.
Award - Funded project: ($5K for one-year), supported by Idaho State University, Internal Small Grant Program (ISGP).
Paper accepted: IEEE Access [Q1, IF: 3.745], “Resources Allocation in Underlay Device-to-Device Communications Networks: A Reduced-Constraints Approach”.
Paper accepted: IoTaIS 2020, “A Rigorous Analysis of Biomedical Edge Computing: An Arrhythmia Classification Use-Case Leveraging Deep Learning”.
Four book chapters accepted: in “Secure Edge Computing: Applications, Techniques and Challenges”, to be Published by CRC Press, 2021.
Paper accepted: IEEE Access [Q1, IF: 3.745], “MARLA-SG: Multi-Agent Reinforcement Learning Algorithm for Efficient Demand Response in Smart Grid”.
Guest Editorial published: IEEE Internet of Things Magazine (IEEE IoTM), “Smart IoT Solutions for Combating the COVID-19 Pandemic”.
Paper accepted: IEEE Internet of Things Journal [Q1, IF: 9.936], “An Efficient and Light-weight Predictive Channel Assignment Scheme for Multi-Band B5G Enabled Massive IoT: A Deep Learning Approach”.
Finalist: CAES Annual Pitch Event (CAPE): Baby Shark Tank virtual pitch competition hosted by Center for Advanced Energy Studies (CAES), Idaho Falls, ID, USA .
Paper accepted: IEEE Internet of Things Journal [Q1, IF: 9.936], “Efficient Privacy-Preserving Electricity Theft Detection with Dynamic Billing and Load Monitoring for AMI Networks”.
Paper accepted: IEEE Access [Q1, IF: 3.745], “Detection of Lying Electrical Vehicles in Charging Coordination Using Deep Learning”.
Paper accepted: IEEE Network [Q1, IF: 8.808], “A Deep Learning Method for Predictive Channel Assignment in Beyond 5G Networks”.
Paper accepted: IEEE Access [Q1, IF: 3.745], “Smart Parking System With Privacy Preservation and Reputation Management Using Blockchain”.
Paper accepted: IEEE Access [Q1, IF: 3.745], “DL-CRC: Deep Learning-based Chest Radiograph Classification for COVID-19 Detection: A Novel Approach”.
Guest Editor: IEEE Internet of Things Magazine (IEEE IoTM) special issue on “Smart IoT Solutions for Combating COVID-19 Pandemic”.
Three book chapters published: in “Combating Security Challenges in the Age of Big Data: Powered By State of the Art AI Techniques”, ISBN: 978-3030356415, CRC Press, USA , 2020.
Paper accepted: AISI 2020, “Performance Analysis of Spectrum Sensing Thresholding Methods for Cognitive Radio Networks”.
Best poster (CIHR category) awarded: Sadman Sakib (with Dr. Fouda as co-supervisor) received the award at the research week event at Lakehead University, Canada.
Paper accepted: IWCMC 2020, “Migrating Intelligence From Cloud to Ultra-Edge Smart IoT Sensor Based on Deep Learning: An Arrhythmia Monitoring Use-Case”.
Paper accepted: ISNCC 2020, “PMBFE: Efficient and Privacy-Preserving Monitoring and Billing Using Functional Encryption for AMI Networks”.
Paper accepted: IEEE ICC 2020, “AI Aided Noise Processing of Spintronic Based IoT Sensor for Magnetocardiography Application”.
Paper accepted: IEEE ICIoT 2020, “Blockchain-based Authentication for 5G Networks”.
Paper accepted: JAC-ECC 2020, “Joint Resources Allocation of Device-to-Device Communications Underlaying Cellular Networks”.
Paper accepted: IEEE CCNC 2020, “Mimic Learning to Generate a Shareable Network Intrusion Detection Model”.
Associate Editor: IEEE Access (Impact Factor: 3.745), 3 year-term.