Members
Head of the Research Group
Hamed Badihi
- Assistant Professor
- Automation Technology and Dependable Systems
- Faculty of Engineering and Natural Sciences
- Tampere University
- +358505695950
- hamed.badihi@tuni.fi
About me
I am an Assistant Professor in Automation Technology and Dependable Systems. I also lead the Dependability and Automation Research in Cyber-Physical Systems (DARES) Group, which is part of the Dependable Systems Cyber Laboratories. My research focuses on critical aspects of condition monitoring, fault-tolerant control, and attack-resilient control, aimed at developing a sustainable and dependable cyber-physical world.
Field of expertise
- Condition monitoring, diagnostics, and prognostics
- Fault-tolerant and attack-resilient control
- Safety and security of industrial control systems
- Cyber-physical-social systems
- Senior Member of Institute of Electrical and Electronics Engineers (SM.IEEE)
- Editor of International Transactions on Electrical Energy Systems, Wiley
- Editor of Advances in Fuzzy Systems, Wiley
- Editor of Processes, MDPI
A Normal Behavior Model Based on Machine Learning for Wind Turbine Cyber-Attack Detection
Wu, H., Badihi, H., Xue, Y. & Vilkko, M., 2024, 2024 International Workshop on Artificial Intelligence and Machine Learning for Energy Transformation, AIE 2024. IEEE, (2024 International Workshop on Artificial Intelligence and Machine Learning for Energy Transformation, AIE 2024).Tutkimustuotos: Konferenssiartikkeli › Tieteellinen › vertaisarvioitu
Hybrid Fault-Tolerant and Attack-Resilient Cooperative Control in an Offshore Wind Farm
Jadidi, S., Badihi, H. & Zhang, Y., huhtik. 2024, julkaisussa: IEEE Transactions on Sustainable Energy. 15, 2, s. 1365-1379 15 SivumääräTutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Intelligent Fault-Tolerant Active Power Control Using Reinforcement Learning for Offshore Wind Farms
Zhang, X., Badihi, H., Jadidi, S., Yu, Z. & Zhang, Y., 2024, julkaisussa: IEEE Access. 12, s. 83782-83795Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Active Fault-Tolerant and Attack-Resilient Control for a Renewable Microgrid Against Power-Loss Faults and Data Integrity Attacks
Jadidi, S., Badihi, H. & Zhang, Y., 3 lokak. 2023, julkaisussa: IEEE Transactions on Cybernetics.Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Design of an intelligent hybrid diagnosis scheme for cyber-physical PV systems at the microgrid level
Jadidi, S., Badihi, H. & Zhang, Y., elok. 2023, julkaisussa: International Journal of Electrical Power and Energy Systems. 150Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Enhancing Hierarchical Fault-Tolerant Cooperative Control in Wind Farms: The Application of Model Predictive Control and Control Reallocation
Jadidi, S., Badihi, H. & Zhang, Y., 2023, 12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023. IEEE, s. 429-434 6 Sivumäärä (IEEE International Conference on Renewable Energy Research and Applications).Tutkimustuotos: Konferenssiartikkeli › Tieteellinen › vertaisarvioitu
Multitarget Normal Behavior Model Based on Heterogeneous Stacked Regressions and Change-Point Detection for Wind Turbine Condition Monitoring
Bilendo, F., Lu, N., Badihi, H., Meyer, A., Cali, Ü. & Cambron, P., 22 marrask. 2023, julkaisussa: IEEE Transactions on Industrial Informatics.Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Smart Cyber-Attack Diagnosis and Mitigation in a Wind Farm Network Operator
Badihi, H., Jadidi, S., Yu, Z., Zhang, Y. & Lu, N., syysk. 2023, julkaisussa: IEEE Transactions on Industrial Informatics. 19, 9Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
A Comprehensive Review on Signal-Based and Model-Based Condition Monitoring of Wind Turbines: Fault Diagnosis and Lifetime Prognosis
Badihi, H., Zhang, Y., Jiang, B., Pillay, P. & Rakheja, S., kesäk. 2022, julkaisussa: Proceedings of the IEEE.Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
A Normal Behavior Model Based on Power Curve and Stacked Regressions for Condition Monitoring of Wind Turbines
Bilendo, F., Badihi, H., Lu, N., Cambron, P. & Jiang, B., 2022, julkaisussa: IEEE Transactions on Instrumentation and Measurement.Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Postdoctoral Researchers
Subhajit Chatterjee
- Postdoctoral Research Fellow
- Faculty of Engineering and Natural Sciences
- Tampere University
- +358504668830
- subhajit.chatterjee@tuni.fi
About me
I am a Postdoctoral Research Fellow in Machine Learning and Renewable Energy Systems. I am also a member of the Dependability and Automation Research in Cyber-Physical Systems (DARES) Group, which is part of the Dependable Systems Cyber Laboratories. My research disciplines on Artificial Intelligence on critical aspects of federated learning, condition monitoring.
Responsibilities
My research focuses on applying Artificial Intelligence to critical areas, including federated learning and condition monitoring, to develop robust and intelligent systems that ensure operational safety and reliability. I specialize in creating scalable and advanced machine learning techniques for distributed energy systems, with a focus on advanced fault detection and resilience against potential downtime. Additionally, I have worked with GAN-based synthetic data generation techniques to address data scarcity and imbalance problems, enabling more effective and accurate AI models. By integrating cutting-edge AI methodologies, my work aims to optimize the performance and reliability of renewable energy systems, contributing to sustainable advancements in critical areas.
Field of expertise
- Machine learning
- Generative AI
- Condition monitoring
- Anomaly detection
- Federated learning
Research topics
- Machine Learning
- Generative AI
- Condition Monitoring
- Data Resampling
- Anomaly Detection
- Predictive Modeling
GAN-based synthetic time-series data generation for improving prediction of demand for electric vehicles
Chatterjee, S., Hazra, D. & Byun, Y.-C., 2024, (E-pub ahead of print) julkaisussa: Expert Systems with Applications. 264, 125838.Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Recent advances and applications of machine learning in the variable renewable energy sector
Chatterjee, S., Khan, P. W. & Byun, Y.-C., 2024, julkaisussa: Energy Reports. 12, s. 5044-5065Tutkimustuotos: Katsausartikkeli › vertaisarvioitu
RoadSitu: Leveraging road video frame extraction and three-stage transformers for situation recognition
Chatterjee, S., Shin, H., Gil, J.-M. & Byun, Y.-C., 2024, julkaisussa: Results in Engineering. 24, 103197.Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
A Synthetic Data Generation Technique for Enhancement of Prediction Accuracy of Electric Vehicles Demand
Chatterjee, S. & Byun, Y.-C., 4 tammik. 2023, julkaisussa: Sensors. 23, 2, 532.Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Generating Time-Series Data Using Generative Adversarial Networks for Mobility Demand Prediction
Chatterjee, S. & Byun, Y.-C., 2023, julkaisussa: CMC: COMPUTERS MATERIALS AND CONTINUA. 74, 3, s. 5507-5525Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Highly imbalanced fault classification of wind turbines using data resampling and hybrid ensemble method approach
Chatterjee, S. & Byun, Y.-C., 2023, julkaisussa: Engineering Applications of Artificial Intelligence. 126, 107104.Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
EEG-based emotion classification using stacking ensemble approach
Chatterjee, S. & Byun, Y.-C., 2022, julkaisussa: Sensors. 22, 21Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Enhancement of image classification using transfer learning and GAN-based synthetic data augmentation
Chatterjee, S., Hazra, D., Kim, Y.-W. & Byun, Y.-C., 2022, julkaisussa: Mathematics. 10, 9Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
IncepX-Ensemble: Performance Enhancement Based on Data Augmentation and Hybrid Learning for Recycling Transparent PET Bottles
Chatterjee, S., Hazra, D. & Byun, Y.-C., 2022, julkaisussa: IEEE Access. 10, s. 52280-52293Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Voting ensemble approach for enhancing alzheimer’s disease classification
Chatterjee, S. & Byun, Y.-C., 2022, julkaisussa: Sensors. 22, 19Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu
Doctoral Researchers
Hatef Azami
- Doctoral Researcher