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Department of Electrical and Computer Engineering

Publications at Department of Electrical and Computer Engineering

Under publication list you can find a complete list of the publications that are written by employees at the Publications at Department of Electrical and Computer Engineering.

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Khatiboun, D. F. (2026). Neuromorphic Computing on the Edge On the Design of Energy-efficient and Adaptive Spiking Neural Network Architectures for Real-time Devices. [PhD dissertation, Aarhus University].

Borges, H. B. (2025). Neural Correlates of Speech Intelligibility. [PhD dissertation, Aarhus University].

Bliddal, H., Christensen, C. B., Møller, C., Vuust, P. & Kidmose, P. (2021). Neural correlates of beat perception measured using ear-EEG: Bringing EEG music studies into the concert hall . Poster session presented at Rhythm Production and Perception Workshop 2021, Oslo, Norway.

Bliddal, H., Christensen, C. B., Møller, C., Vuust, P. & Kidmose, P. (2021). Neural correlates of beat perception measured using ear-EEG. Poster session presented at Advances and Perspectives in Auditory Neuroscience, United States.

Zhao, X. (2020). Network Coding for Distributed Storage of IoT. [PhD dissertation, Aarhus University].

Marandi, S. A., Sehat, H., Lucani Rötter, D. E., Mousavifar, S. & Jacobsen, R. H. (2021). Network Coding-based Data Storage and Retrieval for Kademlia. In 2021 IEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Proceedings Article 9448845 IEEE. https://doi.org/10.1109/VTC2021-Spring51267.2021.9448845

Ronchini, M., Rezaeiyan, Y., Zamani, M., Panuccio, G. & Moradi, F. (2022). NET-TEN: a silicon neuromorphic network for low-latency detection of seizures in local field potentials. ArXiv. https://doi.org/10.48550/arXiv.2210.10565

Ronchini, M., Rezaeiyan, Y., Zamani, M., Panuccio, G. & Moradi, F. (2023). NET-TEN: a silicon neuromorphic network for low-latency detection of seizures in local field potentials. Journal of Neural Engineering, 20(3), Article 036002. https://doi.org/10.1088/1741-2552/acd029

Böttner, C., Jakobsen, F. W., Nielsen, T., Winsborrow, M., Polteau, S., Mazzini, A., Planke, S., Andresen, K. J., Millinge, O. J. S., Asif, M. R., Laberg, J. S., Hopper, J., Myklebust, R. & Seidenkrantz, M. S. (2025). Natural hydrocarbon seepage at the Northeast Greenland continental shelf. Communications Earth and Environment, 6(1), Article 879. https://doi.org/10.1038/s43247-025-02932-8

Naveed, K., Mukhtar, S. & Ur Rehman, N. (2021). Multivariate Signal Denoising Based on Generic Multivariate Detrended Fluctuation Analysis. In 2021 IEEE Statistical Signal Processing Workshop, SSP 2021 (pp. 441-445). IEEE. https://doi.org/10.1109/SSP49050.2021.9513823

Ahmed, M. U., Rehman, N., Looney, D., Rutkowski, T. M., Kidmose, P. & Mandic, D. P. (2012). Multivariate entropy analysis with data-driven scales. In 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 3901-3904). IEEE. https://doi.org/10.1109/icassp.2012.6288770, https://doi.org/10.1109/ICASSP.2012.6288770

Wang, X., Berardinelli, G., Cheng, H. V., Popovski, P. & Adeogun, R. (2025). Multi-User Beamforming with Deep Reinforcement Learning in Sensing-Aided Communication. 61-66. https://doi.org/10.1109/EuCNC/6GSummit63408.2025.11036884

Shi, L., Hernandez Marcano, N. J. & Jacobsen, R. H. (2022). Multi-UAV Path Coordination through Generalized Potential Games. In 2022 8th International Conference on Automation, Robotics and Applications, ICARA 2022 (pp. 125-129). IEEE. https://doi.org/10.1109/ICARA55094.2022.9738578

Morante Moreno, M., Frølich, K., Shahzaib, M., shakil, S. & Rehman, N. U. (2024). Multiscale Functional Connectivity analysis of episodic memory reconstruction. Frontiers in Cognition, 3, Article 1433234. https://doi.org/10.3389/fcogn.2024.1433234

Nazari, M., Korshoej, A. R. & Rehman, N. U. (2024). Multiscale Dynamic Graph Signal Analysis. Social Science Research Network (SSRN). https://doi.org/10.2139/ssrn.4713829

Nazari, M., Korshøj, A. R. & ur Rehman, N. (2024). Multiscale dynamic graph signal analysis. Signal Processing, 222, Article 109519. https://doi.org/10.1016/j.sigpro.2024.109519

Dahl, M. K., Hassan Hire, J., Zamani, M. & Moradi, F. (2024). Multimodal Temperature Sensing Using Electromechanical Impedance (EMI) for Structural Health Monitoring. IEEE Sensors Journal, 24(3), 3457-3464. https://doi.org/10.1109/JSEN.2023.3343779

Gheisarnejad Chirani, M. & Khooban, M. H. (2021). Multi-microgrids with a Frequency Regulation-Based V2G Technology: Systems Analysis, Modeling, and Control. In Design, Control, and Operation of Microgrids in Smart Grids: Power Systems (pp. 1-26). Springer. https://doi.org/10.1007/978-3-030-64631-8_1

Fathollahidehkordi, A. & Andresen, B. (2023). Multi-Machine Power System Transient Stability Enhancement Utilizing a Fractional Order-Based Nonlinear Stabilizer. Fractal and Fractional, 7(11), 808. Article 808. https://doi.org/10.3390/fractalfract7110808

Tran, D. T., Yamac, M., Degerli, A., Gabbouj, M. & Iosifidis, A. (2021). Multilinear compressive learning. IEEE Transactions on Neural Networks and Learning Systems, 32(4), 1512-1524. Article 9070152. https://doi.org/10.1109/TNNLS.2020.2984831

Shabani, M., Tran, D. T., Magris, M., Kanniainen, J. & Iosifidis, A. (2022). Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction. In 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings (pp. 1487-1491). IEEE. https://doi.org/10.23919/EUSIPCO55093.2022.9909957

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2021). Multi-Exit Vision Transformer for Dynamic Inference. In The 32nd British Machine Vision Conference https://www.semanticscholar.org/paper/Multi-Exit-Vision-Transformer-for-Dynamic-Inference-Bakhtiarnia-Zhang/26f61039857423c0aad2c44f0e7769cbb61246c9

Fathollahidehkordi, A., Gheisarnejad Chirani, M., Boudjadar, J., Derakhshandeh, S. Y. & Khooban, M. H. (2023). Multi-Criteria Design of Electric Transit Bus Based on Wireless Charging Infrastructure: A Case Study of Real Road Map in Wakefield. Automation , 4(3), 291-308. https://doi.org/10.3390/automation4030017

Lechuga, M. M. L., Nørremark, M., Jorguseski, L., D'Acunto, L., Politis, C. & Palattella, M. R. (2023). Multi-Connectivity for Livestock Transport in Rural Areas. Paper presented at 2023 Joint EuCNC & 6G Summit, Gothenburg, Sweden.

Kuldeep, G. & Zhang, Q. (2022). Multi-class privacy-preserving cloud computing based on compressive sensing for IoT. Journal of Information Security and Applications, 66, Article 103139. https://doi.org/10.1016/j.jisa.2022.103139

Sejersen, J. L. F., Sarabakha, A., Plagborg Bak Sørensen, K. & Høigaard Jensen, J. (2025). Multi-Agent Path Planning in Complex Environments using Gaussian Belief Propagation with Global Path Finding. 4359-4365. Paper presented at 2025 IEEE International Conference on Robotics and Automation (ICRA) , Atlanta, Georgia, United States. https://doi.org/10.1109/ICRA55743.2025.11128006

Yildirim, B., Gheisarnejad Chirani, M., Temel Özdemir, M. T. Ö. & Khooban, M. H. (2024). Multi-agent fuzzy Q-learning-based PEM fuel cell air-feed system control. International Journal of Hydrogen Energy, 75, 354-362. https://doi.org/10.1016/j.ijhydene.2024.02.129

Nørremark, M., (2024). Muligheder for miljøeffektberegning af teknologier for pesticidreduktion i relation til økologisk jordbrug, No. 2024-0751020, 4 p., Nov 29, 2024. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Nørremark, M. (2024). Muligheder for mere sikker håndtering af kvæg ved teknologisk innovation. DCA - Nationalt Center for Fødevarer og Jordbrug.

Kazemi, Z., Rask, J. K., Gomes, C., Yildiz, E. & Larsen, P. G. (2023). Movable factory—A systematic literature review of concepts, requirements, applications, and gaps. Journal of Manufacturing Systems, 69, 189-207. https://doi.org/10.1016/j.jmsy.2023.06.008

Sadiq, M. T., Yu, X., Yuan, Z., Aziz, M. Z., Rehman, N. U., Ding, W. & Xiao, G. (2022). Motor Imagery BCI Classification Based on Multivariate Variational Mode Decomposition. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(5), 1177-1189. https://doi.org/10.1109/tetci.2022.3147030

Iraji, M., Dehghani, M., Mohammadi, M., Vafamand, N. & Boudjadar, J. (2021). Motor Current Signature Analysis Using Shapelet. In H. Selvaraj, G. Chmaj & D. Zydek (Eds.), Proceedings of the 27th International Conference on Systems Engineering, ICSEng 2020 (pp. 23-33). Springer. https://doi.org/10.1007/978-3-030-65796-3_3

Shi, L. (2022). Motion Planning for Autonomous Aerial Robots. [PhD dissertation, Aarhus University]. Aarhus Universitet.

Bjerge, K., Frigaard, C. E. & Karstoft, H. (2022). Motion Informed Object Detection of Small Insects in Time-lapse Camera Recordings. arxiv.org. https://arxiv.org/abs/2212.00423

Wang, Z., Chen, L., Chen, H. & Rehman, N. U. (2023). Monthly ship price forecasting based on multivariate variational mode decomposition. Engineering Applications of Artificial Intelligence, 125, Article 106698. https://doi.org/10.1016/j.engappai.2023.106698

Alvarez Tunon, O., Brodskiy, Y. & Kayacan, E. (2024). Monocular visual simultaneous localization and mapping:(r) evolution from geometry to deep learning-based pipelines. IEEE Transactions on Artificial Intelligence, 5(5), 1990-2010. Article 3321032. https://doi.org/10.1109/TAI.2023.3321032

Hansen, S. T., Kamburjan, E. & Kazemi, Z. (2025). Monitoring Reconfigurable Simulation Scenarios in Co-simulated Digital Twins. In T. Margaria & B. Steffen (Eds.), Leveraging Applications of Formal Methods, Verification and Validation. Specification and Verification - 12th International Symposium, ISoLA 2024, Proceedings (pp. 47-61). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-75390-9_4

Gheisarnejad Chirani, M., Mohammadzadeh, A. & Khooban, M. H. (2022). Model Predictive Control-Based Type-3 Fuzzy Estimator for Voltage Stabilization of DC Power Converters. IEEE Transactions on Industrial Electronics, 69(12), 13849-13858. https://doi.org/10.1109/TIE.2021.3134052

Salehi, Z., Karimaghaee, P. & Khooban, M. H. (2021). Model Order Reduction of Positive Real Systems Based on Mixed Gramian Balanced Truncation with Error Bounds. Circuits, Systems and Signal Processing, 40(11), 5309-5327. https://doi.org/10.1007/s00034-021-01734-5

Antonsen, M. M. (2025). Model-Mediated Teleoperation for Tactile Internet. [PhD dissertation, Aarhus University].

Li, B., Fitzgerald, J. & Schultz, C. (2022). Modelling the impacts of crowds on occupants in the built environment—A static, rule-based approach to human perception and movement. Advanced Engineering Informatics, 51, Article 101452. https://doi.org/10.1016/j.aei.2021.101452

Kulik, T., Macedo, H. D., Talasila, P. & Larsen, P. G. (2021). Modelling the HUBCAP Sandbox Architecture In VDM: A Study In Security. In J. Fitzgerald, T. Oda & H. D. Macedo (Eds.), Proceedings of the 18th International Overture Workshop (pp. 20-35) https://arxiv.org/pdf/2101.07261.pdf

Amer, A., Felsager, D., Brodskiy, Y. & Sarabakha, A. (2025). Modelling of Underwater Vehicles using Physics-Informed Neural Networks with Control. In International Joint Conference on Neural Networks, IJCNN 2025 - Proceedings IEEE. https://doi.org/10.1109/IJCNN64981.2025.11228873

Bochtis, D., Sørensen, C. A. G., Jørgensen, R. N. & Green, O. (2009). Modelling of material handling operations using controlled traffic. Biosystems Engineering, 103(4), 397-408. https://doi.org/10.1016/j.biosystemseng.2009.02.006

Abbiati, G., Gomes, C., Sandberg, M., Kazemi, Z., Hansen, S. T. & Larsen, P. G. (2024). Modelling for Digital Twins. In J. Fitzgerald, C. Gomes & P. G. Larsen (Eds.), The Engineering of Digital Twins (pp. 89-127). Springer. https://doi.org/10.1007/978-3-031-66719-0_5

Böttjer, T., Sandberg, M., Larsen, P. G. & Macedo, H. D. (2021). Modelling an Injection Moulding Machine using the Vienna Development Method. In H. D. Macedo, C. Thule & K. Pierce (Eds.), Proceedings of the 19th International Overture Workshop (pp. 51-65) https://arxiv.org/abs/2110.09371

Samboju, S. K., Tanjavooru, V. T., Zinsmeister, D. & Peric, V. S. (2021). Modeling of combined heat and power generation unit for dynamic analysis of integrated thermal-electric grids∗. In Proceedings of the 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems Article 11 Association for Computing Machinery. https://doi.org/10.1145/3470481.3472711

Hansen, S. T. & Ölveczky, P. C. (2022). Modeling, Algorithm Synthesis, and Instrumentation for Co-simulation in Maude. In K. Bae (Ed.), Rewriting Logic and Its Applications. WRLA 2022 (pp. 130-150). Springer. https://doi.org/10.1007/978-3-031-12441-9_7

Oshnoei, S., Aghamohammadi, M. R. & Khooban, M. H. (2024). Model-Free Predictive Frequency Control Under Sensor and Actuator FDI Attacks. IEEE Transactions on Circuits and Systems II: Express Briefs, 71(4), 2434-2438. https://doi.org/10.1109/TCSII.2023.3339545

Feng, H., Gomes, C., Iosifidis, A. & Larsen, P. G. (2021). Model-based monitoring and state estimation for digital twins: The Kalman filter. In C. R. Martin, M. J. Blas & A. I. Psijas (Eds.), Annual Modeling and Simulation Conference (ANNSIM 2021) (pp. 1-2)

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