Shimaa Bergies 助理教授

Shimaa Bergies	最高學歷	Ph.D. in Electrical Engineering and Computer Science, National Taiwan University of Science and Technology
	TEL	(07) 601-1000 Ext: 研究室：
	E-mail	shbergies@nkust.edu.tw
	專長	Cybersecurity, 4G/5G/6G Networks, Internet of Things (IoT), Data Analysis, and Image Processing
	解惑時間	Thursday 13:30–15:30
	實驗室網頁	建置中
	個人網頁	Google Scholar LinkedIn

學歷：

Ph.D. in Electrical Engineering and Computer Science, National Taiwan University of Science and Technology
M.Sc. in Electrical Engineering and Computer Science, National Taiwan University of Science and Technology
B.Sc. in Electrical Engineering, Electronics and Communication, Faculty of Engineering at Shoubra, Benha University

經歷：

Postdoctoral Fellow, Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology

研究計畫：

My research is driven by a commitment to solving real-world problems through the application of cutting-edge technologies in AI, IoT, and cybersecurity. I believe that my work has the potential to make a meaningful impact on the future of autonomous systems, smart environments, and cybersecurity. I am excited about the opportunity to contribute to the academic and industrial advancements in these fields and to work with students, researchers, and industry professionals to further drive innovation and create solutions that have far-reaching societal benefits.

Research Projects：

Autonomous Cleaning Machine: Converted a manual cleaning machine into an autonomous one; Vision System for Autonomous Robots: Developed a system for object detection and tracking.
Robot Arm Control Based on EMG Data: Implemented control based on Electro-Myography data.
IoT 5G Temperature and Humidity Tracking: Monitored indoor climate conditions.
Remote Robot Control via IoT 5G: Enabled remote control of multiple robots.
Gender Classification and Emotion Prediction: Designed a system for gender classification and emotion prediction.
Gesture Recognition for Robot Control: Developed a control system based on human gesture recognition.
Indoor Auto Guided Vehicle Positioning: Implemented a positioning system for AGVs.
Secure Automated Electric Vehicles: Developed solutions to secure electric vehicles against cyberattacks and data loss.
NSTC Outdoor Auto Guided Vehicle Positioning: Implemented a positioning system for AGVs.
GNSS-DDM Satellite Data Analysis: Analyzed satellite data for wind speed and direction detection and prediction.
Taiwan Aerospace Agency (TASA) Data Analysis: Analyzed CubeSat datasets for detecting and predicting satellite motion anomalies.

Journal Papers：

M. Elsisi and S. Bergies, “A Robust IoT Architecture for Smart Inverters in Microgrids Using Hybrid Deep Learning and Signal Processing against Adversarial Attacks,” Internet of Things, 2025. (SCI, Impact Factor = 6, Q1)
https://doi.org/10.1016/j.iot.2025.101576
S. Bergies, T. M. Aljohani, S.-F. Su, and M. Elsisi, “An IoT-Based Deep-Learning Architecture to Secure Automated Electric Vehicles Against Cyberattacks and Data Loss,” IEEE Transactions on Systems, Man, and Cybernetics, 2024. (SCI, Impact Factor = 8.6, Q1)
https://doi.org/10.1109/TSMC.2024.3409314
S. Bergies, M. Elsisi, and Chun-Lien Su, “New Design of Robust Model Predictive Control Using Frequency Domain Bands and Dandelion-Optimizer,” IEEE Transactions on Reliability, 2024. (SCI, Impact Factor = 5, Q1)
https://doi.org/10.1109/TR.2024.3488122
S. Bergies, S.-F. Su, and M. Elsisi, “Model Predictive Paradigm with Low Computational Burden Based on Dandelion Optimizer for Autonomous Vehicle Considering Vision System Uncertainty,” Mathematics, Vol. 10, 2022. (SCI, Impact Factor = 2.3, Q1)
https://doi.org/10.3390/math10234539
M. Elsisi, H. G. Zaini, K. Mahmoud, S. Bergies, and S. S. M. Ghoneim, “Improvement of Trajectory Tracking by Robot Manipulator Based on a New Co-operative Optimization Algorithm,” Mathematics, Vol. 9, 2021. (SCI, Impact Factor = 2.3, Q1)
https://doi.org/10.3390/math9243231
Chieh Tsai, Pei-Jun Lee, S. Bergies, John Liobe, and Vaidotas Barzde, “Enhancing Satellite Image Quality with the Edge-Based Wavelet Transformer for Super-Resolution,” Elsevier, Vol. 28, 2025. (SCI, Impact Factor = 3.2, Q2)
https://doi.org/10.1016/j.acags.2025.100302
Wei-Chen Hsu, Pei-Jun Lee, S. Bergies, and Chun-Fu Chen, “Cloud Segmentation Accelerator Design for Low Data Transmission Rate on Satellite Payload,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 18, 2025. (SCI, Impact Factor = 5.3, Q1)
https://doi.org/10.1109/JSTARS.2025.3629088
S. Bergies, P. T. T. Nguyen, and C. H. Kuo, “Cleaning Robot Vision System Based on RGBD Camera and Deep Learning YOLO-Based Object Detection Algorithm,” International Journal of iRobotics, Vol. 4, pp. 23–29.
Chun-Fu Chen, Pei-Jun Lee, and Shimaa Bergies, “Efficient Cloud Removal for Remote Sensing Data Transmission via Model Compression and Sparse Accelerator Design,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. (SCI, Impact Factor = 5.3, Q1)
https://doi.org/10.1109/JSTARS.2026.3661035
M. Elsisi and S. Bergies, “A Cyber-Resilient IoT Framework for Smart Inverters in Microgrids Using Hybrid Deep Learning and Signal Processing against Cyberattacks,” Submitted to Internet of Things, 2025.

Conference Papers：

S. Bergies and M. Elsisi, “Reliable IoT Paradigm Towards Renewable Energy Penetration and Enhancing Resilience Operation in Smart Grids,” 6th International Black Sea Modern Scientific Research Congress Conference, 2024.
S. Bergies and M. Elsisi, “Reliable IoT Paradigm Towards Renewable Energy Penetration and Enhancing Resilience Operation in Smart Grids,” 6th International Black Sea Modern Scientific Research Congress, August 23–25, 2024, Trabzon, Turkiye.
M. Elsisi and S. Bergies, “Cyber-Resilient State of Charge Monitoring in Electric Vehicles via Robust Kalman Filter,” 14th International Mardin Artuklu Scientific Research Conference, June 1–3, 2025, Mardin, Turkiye.
M. Elsisi, S. Bergies, and C.-L. Su, “Reliable IoT Architecture with Deep Gated Recurrent Units for Enhanced Resilience and Renewable Energy Integration in Smart Grids,” IEEE International Conference on Energy Technologies for Future Grids (ETFG 2025), Wollongong, Australia, 2025.