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.

Publication list

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Deutch, F., Weiss, M. G., Wagner, S. R., Hansen, L. S., Larsen, F., Figueiredo, C., Moers, C. & Keller, A. K. (2025). Machine-Learning-Based Activity Tracking for Individual Pig Monitoring in Experimental Facilities for Improved Animal Welfare in Research. Sensors, 25(3), Article 785. https://doi.org/10.3390/s25030785

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. Article 9285309. https://doi.org/10.1109/JSEN.2020.3042937

Fathollahi, A. (2025). Machine Learning and Artificial Intelligence Techniques in Smart Grids Stability Analysis: A Review. Energies, 18(13), Article 3431. https://doi.org/10.3390/en18133431

Wu, Q. F., Jochum, M., Avery, J. E., Vettoretti, G. & Nuterman, R. (2025). Machine Guided Derivation of the Atlantic Meridional Overturning Circulation (AMOC) Strength. Geophysical Research Letters, 52(3), Article e2024GL113454. https://doi.org/10.1029/2024GL113454

Ugurlu, H. I., Redder, A. & Kayacan, E. (2025). Lyapunov-Inspired Deep Reinforcement Learning for Robot Navigation in Obstacle Environments. In 2025 IEEE Symposium on Computational Intelligence on Engineering/Cyber Physical Systems, CIES 2025 IEEE. https://doi.org/10.1109/CIES64955.2025.11007627

Islam, M. T., Khan, H. A., Naveed, K., Nauman, A., Gulfam, S. M. & Kim, S. W. (2023). LUVS-Net: A Lightweight U-Net Vessel Segmentor for Retinal Vasculature Detection in Fundus Images. Electronics, 12(8), Article 1786. https://doi.org/10.3390/electronics12081786

Phan, H., Lorenzen, K. P., Heremans, E., Chen, O. Y., Tran, M. C., Koch, P., Mertins, A., Baumert, M., Mikkelsen, K. B. & De Vos, M. (2023). L-SeqSleepNet: Whole-cycle Long Sequence Modeling for Automatic Sleep Staging. IEEE Journal of Biomedical and Health Informatics, 27(10), 4748-4757. https://doi.org/10.1109/JBHI.2023.3303197

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). Article 9308440 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308440

Spasaro, M. (2021). Low-Power Radio-Frequency Low Noise Amplifiers for Future Wireless Transceivers. [PhD thesis, Aarhus University]. Aarhus Universitet.

Shreya, S., Rezaeiyan, Y., Sadeghi, M., Kaushik, B. K. & Moradi, F. (2023). Low-Power Pattern Recognition System Using Spintronics Compute-in-memory Architecture. In 2023 IEEE Nanotechnology Materials and Devices Conference (NMDC) (pp. 730-734). IEEE. https://doi.org/10.1109/NMDC57951.2023.10344005

Ronchini, M. (2023). Low Power IC Implementation of Spiking Neural Networks for Implantable Neuromorphic Chips. [PhD thesis, Aarhus University]. Aarhus Universitet.

Sadeghi, M. (2025). Low-Power ASIC Design of a Programmable Spiking Neural Network Platform. [PhD thesis, Aarhus University].

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 Article 1214806 SPIE - International Society for Optical Engineering. 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.

Kumar, R. R., Hänsel, A., Castera, P., Volet, N. & Heck, M. J. R. (2024). Low-kappa DBR grating filters on an InP generic photonic integration foundry platform. Journal of the Optical Society of America B: Optical Physics, 41(4), 1054-1059. https://doi.org/10.1364/JOSAB.518800

Tashakor, N., Arabsalmanabadi, B., Naseri, F. & Goetz, S. (2022). Low-Cost Parameter Estimation Approach for Modular Converters and Reconfigurable Battery Systems Using Dual Kalman Filter. IEEE Transactions on Power Electronics, 37(6), 6323-6334. https://doi.org/10.1109/TPEL.2021.3137879

Jakobsen, M. O. (2024). Low cost MEMS accelerometer and microphone based condition monitoring sensor, with LoRa and Bluetooth Low Energy radio. HardwareX, 18, Article e00525. https://doi.org/10.1016/j.ohx.2024.e00525

Taurone, F., Lucani Rötter, D. E., Fehér, M. & Zhang, Q. (2023). Lossless preprocessing of floating point data to enhance compression. In R. Mehmood, V. Alves, I. Praça, J. Wikarek, J. Parra-Domínguez, R. Loukanova, I. de Miguel, T. Pinto, R. Nunes & M. Ricca (Eds.), Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference. DCAI 2023 (pp. 457–466). Springer. https://doi.org/10.1007/978-3-031-38318-2_45

Alvarez Tunon, O., Brodskiy, Y. & Kayacan, E. (2023). Loss it right: Euclidean and riemannian metrics in learning-based visual odometry. In ISR Europe 2023: 56th International Symposium on Robotics, in cooperation with Fraunhofer IPA September 26 – 27, 2023 in Stuttgart (pp. 107-111). VDE Verlag GmbH. https://ieeexplore.ieee.org/abstract/document/10363060

Esterle, L. & King, D. W. (2021). Loosening Control—A Hybrid Approach to Controlling Heterogeneous Swarms. ACM Transactions on Autonomous and Adaptive Systems, 16(2), Article 5. https://doi.org/10.1145/3502725

Musaeus, C. S., Waldemar, G., Andersen, B. B., Høgh, P., Kidmose, P., Hemmsen, M. C., Rank, M. L., Kjær, T. W. & Frederiksen, K. S. (2022). Long-Term EEG Monitoring in Patients with Alzheimer's Disease Using Ear-EEG: A Feasibility Study. Journal of Alzheimer's Disease, 90(4), 1713-1723. https://doi.org/10.3233/JAD-220491

Jørgensen, S. D., Kidmose, P., Mikkelsen, K., Blech, M., Hemmsen, M. C., Rank, M. L. & Kjaer, T. W. (2023). Long-term ear-EEG monitoring of sleep – A case study during shift work. Journal of Sleep Research, 32(5), Article e13853. https://doi.org/10.1111/jsr.13853

Nørremark, M. & Grøn Sørensen, C. (2022). Logistic chain redesign in crop harvest processes. Poster session presented at Fremtidens Dage, Herning, Denmark.

de la Cour, J. D., Johnsen, C.-J. & Avery, J. E. (2024). Lockstep-Parallel Dualization of Surface Triangulations. In PASC '24: Proceedings of the Platform for Advanced Scientific Computing Conference Article 9 Association for Computing Machinery. https://doi.org/10.1145/3659914.3659923

Polinski, A., Mazur-Milecka, M., Kowalczyk, N., Jaguszewska, K. & Wagner, S. R. (2025). Local Pulse Transit Time Analysis. In Proceeding - 17th International Conference on Human System Interaction, HSI 2025 IEEE Computer Society. https://doi.org/10.1109/HSI66212.2025.11142434

Kuldeep, G. (2022). Lightweight Time-Series Signal Compression Period Extraction and Multiresolution using Difference Sequences. IEEE Internet of Things Journal, 9(9), 7043-7050. https://doi.org/10.1109/JIOT.2021.3113951

Kuldeep, G. & Zhang, Q. (2023). Lightweight electrocardiogram signal compression. Biomedical Signal Processing and Control, 85, Article 105012. https://doi.org/10.1016/j.bspc.2023.105012

Vestergaard, R., Techel, J., Zhang, Q. & Lucani Rötter, D. E. (2022). Lightweight Compression for Severely Constrained IoT Devices. In European Wireless 2022; 27th European Wireless Conference (pp. 1-6). IEEE.

Zayed, Y. N. H., Kristoffersen, A. E., Kamari, A. & Schultz, C. P. L. (2025). Leveraging Large Language Models in Capturing Architects Social Design Intentions in Buildings A Case Study. In Proceedings of SBE2025 Zurich: Sustainable Built Environment Conference (SBE25) https://doi.org/10.3929/ethz-c-000785697

Laakom, F., Chumachenko, K., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). Learning to ignore: rethinking attention in CNNs. In 32rd British Machine Vision Conference https://arxiv.org/pdf/2111.05684.pdf

Heidari, N. & Iosifidis, A. (2023). Learning Diversified Feature Representations for Facial Expression Recognition in the Wild. ArXiv. https://doi.org/10.48550/arXiv.2210.09381

Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2023). Learning Distinct Features Helps, Provably. In D. Koutra, C. Plant, M. Gomez Rodriguez, E. Baralis & F. Bonchi (Eds.), Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part II (pp. 206-222). Springer. https://doi.org/10.1007/978-3-031-43415-0_13

Bozcan, I. (2021). Learning-based Anomaly Detection for Aerial Surveillance. [PhD thesis, Aarhus University]. Aarhus Universitet.

Oleksiienko, I. & Iosifidis, A. (2023). Layer Ensembles. In D. Comminiello & M. Scarpiniti (Eds.), 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP) IEEE. https://doi.org/10.1109/MLSP55844.2023.10286005

Marandi, A., Alves, P. G. M. R., Aranha, D. F. & Jacobsen, R. H. (2024). Lattice-based Homomorphic Encryption for Privacy-Preserving Smart Meter Data Analytics. The Computer Journal, 67(5), 1687-1698. https://doi.org/10.1093/comjnl/bxad093

Munshi, M. T. & Klarskov, P. (2021). Laser Terahertz Emission Microscopy of Gold Nanorods forming a Coffee-stain Ring on a Semiconductor Surface. In 2021 46th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2021 IEEE. https://doi.org/10.1109/IRMMW-THz50926.2021.9566850

Marinoudi, V., Benos, L., Villa, C. C., Kateris, D., Berruto, R., Pearson, S., Sørensen, C. G. & Bochtis, D. (2024). Large language models impact on agricultural workforce dynamics: Opportunity or risk? Smart Agricultural Technology, 9, Article 100677. https://doi.org/10.1016/j.atech.2024.100677

Nørremark, M., Hansen, M. J., Børsting, C. F., Ottosen, C.-O. & Jensen, P. K., (2023). Landbrugsteknisk hjælp til besvarelse af høringssvar til Miljø- og klimateknologi 2023, No. 2023-0543309, 41 p., Sept 19, 2023. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Kai, P. & Nørremark, M., (2025). Kortlægning af tekniske elementer af betydning for omlægning fra burægsproduktion til produktion af skrabe-, frilands- og økologiske æg, No. 2025-0796920, 21 p., Mar 26, 2025. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Yalsavar, M., Karimaghaee, P., Sheikh-Akbari, A., Khooban, M. H., Dehmeshki, J. & Al-Majeed, S. (2022). Kernel Parameter Optimization for Support Vector Machine Based on Sliding Mode Control. IEEE Access, 10, 17003-17017. https://doi.org/10.1109/ACCESS.2022.3150001

Mortensen, A. K., Hansen, A. L. & Gislum, R. (2023). Kamera og kunstig intelligens til vurdering af sygdomstryk i sukkerroer. In Faglig beretning 2022: Verksamhetsberättelse (pp. 53-56). NBR Nordic Beet Research Foundation. https://www.nordicbeet.nu/wp-content/uploads/2023/02/nbr_aarsberetning_2022.pdf

Hallerstede, S. (2006). Justifications for the event-b modelling notation. In J. Julliand & O. Kouchnarenko (Eds.), B 2007: Formal Specification and Development in B - 7th International Conference of B Users, Proceedings (pp. 49-63). Springer Verlag. https://doi.org/10.1007/11955757_7

Nazari, M., Korshøj, A. R. & Rehman, N. U. (2024). Jump Plus AM-FM Mode Decomposition. Cornell University. https://doi.org/10.48550/arXiv.2407.07800

Nazari, M., Korshj, A. R. & Rehman, N. U. (2025). Jump Plus AM-FM Mode Decomposition. IEEE Transactions on Signal Processing, 73, 1081-1093. https://doi.org/10.1109/TSP.2025.3535822

Hosseinzadeh, M., Hudson, N., Zhao, X., Khamfroush, H. & Lucani Rötter, D. E. (2021). Joint Compression and Offloading Decisions for Deep Learning Services in 3-Tier Edge Systems. In 2021 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2021 (pp. 254-261). IEEE. https://doi.org/10.1109/DySPAN53946.2021.9677398

Nielsen, A. H., Iosifidis, A. & Karstoft, H. (2021). IrradianceNet: Spatiotemporal Deep Learning Model for Satellite-Derived Solar Irradiance Nowcasting. Solar Energy, 228, 659-669. https://doi.org/10.1016/j.solener.2021.09.073

Amiri, M., Dehghani, M., Khayatian, A., Mohammadi, M., Vafamand, N. & Boudjadar, J. (2021). Investigation of Wind Energy Impact on Power Systems Stability Using Lyapunov Exponents. In H. Selvaraj, G. Chmaj & D. Zydek (Eds.), Proceedings of the 27th International Conference on Systems Engineering, ICSEng 2020 (pp. 12-22). Springer. https://doi.org/10.1007/978-3-030-65796-3_2

Sergeeva, A., Christensen, C. B. & Kidmose, P. (2022). Investigation of the Effect of Spatial Filtering for Detecting Auditory Steady-State Responses Recorded from Ear-EEG. In 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022 (pp. 56-59). IEEE. https://doi.org/10.1109/EMBC48229.2022.9871170

Tabar, Y. R., Mikkelsen, K. B., Rank, M. L., Hemmsen, M. C. & Kidmose, P. (2021). Investigation of low dimensional feature spaces for automatic sleep staging. Computer Methods and Programs in Biomedicine, 205, Article 106091. https://doi.org/10.1016/j.cmpb.2021.106091

Amarloo, A., Cinnella, P., Iosifidis, A., Forooghi, P. & Abkar, M. (2023). Investigation of Data-driven algebraic Reynolds stress models for turbulent secondary flows. In The 14th International ERCOFTAC Symposium on Engineering Turbulence Modelling and Measurements Proceedings https://www.ercoftac.org/etmm/program/conference-program/

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