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 for example journal articles, books, reports etc.

The department also publishes technical reports which you can read more about under Technical reports.

Under PhD dissertations you will find the department's published PhD dissertations.

Publication list

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Razmi, P., Fathollahidehkordi, A., Gheisarnejad Chirani, M. & Khooban, M. H. (2023). Neuromorphic deep learning frequency regulation in stand-alone microgrids. Applied Soft Computing. https://www.sciencedirect.com/science/article/pii/S1568494623004362

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.

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 (VTC2021-Spring) IEEE. I E E E V T S Vehicular Technology Conference. Proceedings 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), [036002]. https://doi.org/10.1088/1741-2552/acd029

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

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. IEEE Workshop on Statistical Signal Processing Proceedings Vol. 2021-July https://doi.org/10.1109/SSP49050.2021.9513823

Naveed, K., Shaukat, B., Ehsan, S., Mcdonald-Maier, K. D., Rehman, N. U. & Baghaie, A. (Ed.) (2019). Multiscale image denoising using goodness-of-fit test based on EDF statistics. PLOS ONE, 14(5), e0216197. https://doi.org/10.1371/journal.pone.0216197

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. [9070152]. https://doi.org/10.1109/TNNLS.2020.2984831

Rehman, N. U., Naveed, K., Ehsan, S. & McDonald-Maier, K. (2016). Multi-scale image denoising based on goodness of fit (GOF) tests. In 2016 24th European Signal Processing Conference (EUSIPCO) IEEE. https://doi.org/10.1109/eusipco.2016.7760508

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. Power Systems https://doi.org/10.1007/978-3-030-64631-8_1

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

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

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

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

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. Lecture Notes in Networks and Systems Vol. 182 https://doi.org/10.1007/978-3-030-65796-3_3

Shi, L. (2022). Motion Planning for Autonomous Aerial Robots. Aarhus Universitet.

Bjerge, K., Frigaard, C. E. & Karstoft, H. (2022). Motion Informed Object Detection of Small Insects in Time-lapse Camera Recordings. arXiv.org.

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, [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

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

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

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. Lecture Notes in Computer Science Vol. 13252 https://doi.org/10.1007/978-3-031-12441-9_7

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). Simulation Series Vol. 53 No. 2

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

Rezaeiyan, Y., Zamani, M., Shoaei, O. & Serdijn, W. A. (2018). Mixed-Signal IC With Pulse Width Modulation Wireless Telemetry for Implantable Cardiac Pacemakers in 0.18-μm CMOS. IEEE Transactions on Biomedical Circuits and Systems, 12(3), 589 - 600. https://doi.org/10.1109/TBCAS.2018.2819021

Banaei, M., Oloomi‐buygi, M., Raouf‐Sheybani, H. & Khooban, M. H. (2021). Mixed supply function‐Cournot equilibrium model of futures and day‐ahead electricity markets. IET Generation, Transmission & Distribution, 15(10), 1640-1654. https://doi.org/10.1049/gtd2.12123

Hageman, K., Feal, A., Gamba, J., Girish, A., Bleier, J., Lindorfer, M., Tapiador, J. & Vallina-Rodriguez, N. (2023). Mixed Signals: Analyzing Software Attribution Challenges in the Android Ecosystem. IEEE Transactions on Software Engineering, 49(4), 2964-2979. https://doi.org/10.1109/TSE.2023.3236582

Salehi, Z., Karimaghaee, P. & Khooban, M. H. (2021). Mixed Positive-Bounded Balanced Truncation. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(7), 2488-2492. https://doi.org/10.1109/TCSII.2021.3053160

Nielsen, L., Burihabwa, D., Schiavoni, V., Felber, P. & Lucani Rötter, D. E. (2021). MinervaFS: A User-Space File System for Generalised Deduplication. In International Symposium on Reliable Distributed Systems (SRDS) IEEE. https://doi.org/10.1109/SRDS53918.2021.00033

Konnerup, D., Nørremark, M. & Jensen, M. (2022). Miljøpositivliste for producentorganisationers driftsfonde til støtteberettigede teknologier til frugt- og grøntsagssektoren 2022. Aarhus Universitet - DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug

Hansen, M. J., Kai, P., Nørremark, M., Børsting, C. F., Ottosen, C-O. & Konnerup, D. (2022). Miljø- og Klimateknologi 2022. Aarhus Universitet - DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug

Khezri, R., Mahmoudi, A. & Khooban, M. H. (2021). Microgrids planning for residential electrification in rural areas. In S. Padmanaban, P. Sivaraman, C. Sharmeela & J. B. Holm-Nielsen (Eds.), Residential Microgrids and Rural Electrifications (pp. 1-25). Academic Press. https://doi.org/10.1016/B978-0-323-90177-2.00014-1

Oshnoei, S., Fathollahidehkordi, A., Oshnoei, A. & Khooban, M. H. (2023). Microgrid Frequency Regulation Based on a Fractional Order Cascade Controller. Fractal Fractional. https://www.mdpi.com/2504-3110/7/4/343

Yuksel, O., Sandberg, M., Hattel, J. H., Akkerman, R. & Baran, I. (2021). Mesoscale Process Modeling of a Thick Pultruded Composite with Variability in Fiber Volume Fraction. Materials, 14(13), [3763]. https://doi.org/10.3390/ma14133763

Shreya, S., Zamani, M., Rezaeiyan, Y., Ghanatian Najafabadi, H., Böhnert, T., Jenkins, A., Ferreira, R., Farkhani, H. & Moradi, F. (2022). Memory and Communication-in-Logic Using Vortex and Precessional Oscillations in a Magnetic Tunnel Junction. IEEE Magnetics Letters, [4505605]. https://doi.org/10.1109/LMAG.2022.3224676

Yazdani, N. (2021). Massive-Scale IoT Dynamic Data Updating and Compression for a Scalable IoT Infrastructure. Aarhus Universitet.

Weiß., G., Pietraroia., D., Sassanelli., C. & Macedo., H. (2021). Manufacturing Process Simulation in a Hybrid Cloud Setup. In Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics (pp. 49-58). SCITEPRESS Digital Library. https://doi.org/10.5220/0010641700003062

Boettjer, T., Krogshave, J. T. & Ramanujan, D. (2021). Machine-specific estimation of milling energy consumption in detailed design. Journal of Manufacturing Science and Engineering, Transactions of the ASME, 143(8), [081010]. https://doi.org/10.1115/1.4050179

Thoft Krogshave, J., Böttjer, T. & Ramanujan, D. (2020). Machine-Specific Energy Estimation Using the Unit Process Life Cycle Inventory (UPLCI) Model. In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference: Volume 6: 25th Design for Manufacturing and the Life Cycle Conference (DFMLC) [V006T06A031] American Society of Mechanical Engineers. https://doi.org/10.1115/DETC2020-22483

Bording, T. S., Asif, M. R., Barfod, A. S., Larsen, J. J., Zhang, B., Grombacher, D. J., Christiansen, A. V., Engebretsen, K. W., Pedersen, J. B., Maurya, P. K. & Auken, E. (2021). Machine learning based fast forward modelling of ground-based time-domain electromagnetic data. Journal of Applied Geophysics, 187, [104290]. https://doi.org/10.1016/j.jappgeo.2021.104290

Khezri, R., Razmi, P., Mahmoudi, A., Bidram, A. & Khooban, M. H. (2023). Machine Learning-based Sizing of a Renewable-Battery System for Grid-Connected Homes with Fast-Charging Electric Vehicle. IEEE Transactions on Sustainable Energy, 14(2), 837-848. https://doi.org/10.1109/TSTE.2022.3227003

Faraji, B., Gheisarnejad, M., Rouhollahi, K., Esfahani, Z. & Khooban, M. H. (2021). Machine Learning Approach based on Ultra-Local Model Control for Treating Cancer Pain. I E E E Sensors Journal, 21(6), 8245-8252. [9285309]. https://doi.org/10.1109/JSEN.2020.3042937

Bajovic, D., Bakhtiarnia, A., Bravos, G., Brutti, A., Burkhardt, F., Cauchi, D., Chazapis, A., Cianco, C., Dall'Asen, N., Delic, V., Dimou, C., Djokic, D., Escobar-Molero, A., Esterle, L., Eyben, F., Farella, E., Festi, T., Geromitsos, A., Giakoumakis, G. ... Zammit, J. (2021). MARVEL: Multimodal Extreme Scale Data Analytics for Smart Cities Environments. In 2021 International Balkan Conference on Communications and Networking, BalkanCom 2021 (pp. 143-147). IEEE. https://doi.org/10.1109/BalkanCom53780.2021.9593258

Ruf, F., Nielsen, L., Balauroiu, M., Volet, N. & Heck, M. (2022). Low-loss all-optical ns-switching for single-photon routing in scalable integrated quantum photonics. In R. G. Baets, P. O'Brien & L. Vivien (Eds.), Integrated Photonics Platforms II [12148-6] SPIE - International Society for Optical Engineering. Proceedings of SPIE, the International Society for Optical Engineering Vol. 12148 https://doi.org/10.1117/12.2621540

Balauroiu, M., Ruf, F., Volet, N. & Heck, M. (2021). Low-loss all-optical ns-switching for scalable quantum photonic links. Poster session presented at Photonic Links for Quantum Technology Platforms.

Shabani, M. & Iosifidis, A. (2020). Low-Rank Temporal Attention-Augmented Bilinear Network for financial time-series forecasting. In 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (pp. 2156-2161). [9308440] IEEE. 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 https://doi.org/10.1109/SSCI47803.2020.9308440

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Technical reports

Department of Electrical and Computer Engineering publishes technical reports covering our research areas.

With the reports, we wish to communicate the newest knowledge and research to society ahead of and during the publication process which can take up to a year.

Read the technical reports by following the link below:

Technical Report Department of Electrical and Computer Engineering

PhD dissertations

At the Department of Electrical and Computer Engineering, PhD dissertations are published via Aarhus University Library's/State and University Library's online E-books platform that is open access. You can find the published dissertations by following the link below.

PhD dissertations at Department of Electrical and Computer Engineering

AU Engineering Profile

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