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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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.

Ring, L., Zamm, A., Mathys, C. & Kappel, S. L. (2026). Liblsl.dart: A Dart native API for Lab Streaming Layer (LSL). The Journal of Open Source Software, Article 10.21105/joss.10425. https://doi.org/10.21105/joss.10425

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 dissertation, Aarhus University]. Aarhus Universitet.

Esfahani, Z., Derakhshan, A. & Ramprasad, S. (2025). Lcoe Reduction in African Off-Grid Rural Microgrids: a Systematic Approach Using Dsm and Innovative Bchp Integration. In 2025 IEEE PES Conference on Innovative Smart Grid Technologies - Middle East (ISGT Middle East) IEEE. https://doi.org/10.1109/ISGTMiddleEast65737.2025.11314274

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

Bozorgtabar, B., Mahapatra, D., Roy , S., Naseer, M., Razzak, I. & Ge, Z. (Accepted/In press). LATA: Laplacian-Assisted Transductive Adaptation for Conformal Uncertainty in Medical VLMs. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition IEEE. https://arxiv.org/pdf/2602.17535

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

Jiang, X., Gao, Y., Xu, H., Zhang, Q., Liao, Y. & Zhou, P. Y. (2025). Knowledge Rumination for Client Utility Evaluation in Heterogeneous Federated Learning. In 2025 IEEE International Conference on Multimedia and Expo: Journey to the Center of Machine Imagination, ICME 2025 - Conference Proceedings IEEE Computer Society Press. https://doi.org/10.1109/ICME59968.2025.11210094

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/

Rafiei Foroushani, M. & Nørremark, M. (2025). Investigation of available ground-truth data in Denmark that can be used for remote identification and localization of populations of selected plant species. DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug

Gentili, M., Tanaka, T., Nichols, V. A., Jørgensen, R. N., Jørgensen, J. R. & Gislum, R. (2025). Investigating weed and companion plant ecosystem services and disservices distribution maps using machine learning: Joint approaches for sustainable weed management. In 20TH EUROPEAN WEED RESEARCH SOCIETY SYMPOSIUM: Joint Approaches for Sustainable Weed Management (pp. 340-340). European Weed Research Society. https://doi.org/10.21001/20.weed.research.society.symposium.2025

Asif, M. R., Maurya, P. K., Larsen, J. J. & Christiansen, A. V. (2022). Investigating the Integration of Neural Networks in Least-Squares Method for Airborne Electromagnetic Data Inversion. 1-5. Paper presented at NSG2022 3rd Conference on Airborne, Drone and Robotic Geophysics, Beograd, Serbia. https://doi.org/10.3997/2214-4609.202220034

Meskin, M., Starkey, P. A., Kaspersen, A. E., Ringgaard, S., Sand, S. G., Nygaard, J. V., Jensen, J. A., Traberg, M. S. & Johansen, P. (2024). Investigating the importance of left atrial compliance on fluid dynamics in a novel mock circulatory loop. Scientific Reports, 14(1), 1864. Article 1864. https://doi.org/10.1038/s41598-024-52327-6

Khare, S. K., Khan, A. M., Bajaj, V. & Sinha, G. R. (2023). Introduction to smart healthcare and the role of cognitive sensors. In G. R. Sinha & V. Bajaj (Eds.), Cognitive Sensors: Applications in smart healthcare (Vol. 2, pp. 1-21). IOP Publishing. https://doi.org/10.1088/978-0-7503-5346-5ch1

Feng, H., Gomes, C., Thule, C., Lausdahl, K., Iosifidis, A. & Larsen, P. G. (2021). Introduction to Digital Twin Engineering. In C. R. Martin, M. J. Blas & A. I. Psijas (Eds.), 2021 Annual Modeling and Simulation Conference (ANNSIM) (pp. 1-12). IEEE. https://doi.org/10.23919/ANNSIM52504.2021.9552135

Iosifidis, A. & Tefas, A. (2022). Introduction. In A. Iosifidis & A. Tefas (Eds.), Deep Learning for Robot Perception and Cognition Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00006-3

Kavanagh, S. R., Nielsen, R. S., Hansen, J. L., Davidsen, R. S., Hansen, O., Samli, A. E., Vesborg, P. C. K., Scanlon, D. O. & Walsh, A. (2025). Intrinsic point defect tolerance in selenium for indoor and tandem photovoltaics. Energy and Environmental Science, 18(9), 4431-4446. https://doi.org/10.1039/d4ee04647a

Liu, Q., Zheng, Y., Wu, H., Michalek, L., Ronchini, M., Mow, R. K., Wang, W., Park, H., Ji, X., Yu, Z., Yao, Z. F., Nishio, Y., Zhao, C., Pei, J. & Bao, Z. (2026). Intrinsically stretchable complementary circuits based on direct photo-patternable polymer semiconductors. Nature Electronics, 9(5), 507-518. https://doi.org/10.1038/s41928-026-01599-z

Haldrup, M., Rasmussen, M., Mohamad, N., Dyrskog, S., Thorup, L., Mikic, N., Wismann, J., Grønhøj, M., Poulsen, F. R., Nazari, M., Rehman, N. U., Simonsen, C. Z. & Korshøj, A. R. (2023). Intraventricular Lavage vs External Ventricular Drainage for Intraventricular Hemorrhage: A Randomized Clinical Trial. JAMA Network Open, 6(10), e2335247. Article e2335247. https://doi.org/10.1001/jamanetworkopen.2023.35247

Kumar, R. R., Nielsen, L., Volet, N. & Heck, M. (2023). Intra-cavity coherent combining of DBR lasers on an InP generic foundry platform. Optics Letters, 48(7), 1614-1617. https://doi.org/10.1364/OL.483889

Fares, H., Ronchini, M., Zamani, M., Farkhani, H. & Moradi, F. (2022). In the realm of hybrid Brain: Human Brain and AI. ArXiv. https://doi.org/10.48550/arXiv.2210.01461

Kakavandi, F., Han, P., de Reus, R., Larsen, P. G. & Zhang, H. (2023). Interpretable Fault Detection Approach With Deep Neural Networks to Industrial Applications. In 2023 International Conference on Control, Automation and Diagnosis (ICCAD 2023) IEEE. https://doi.org/10.1109/ICCAD57653.2023.10152435

Taurone, F. (2025). Interplays between Compression, Privacy and Analytics for the Internet of Things. [PhD dissertation, Aarhus University].

David, I., Shao, G., Gomes, C., Tilbury, D. & Zarkout, B. (2025). Interoperability of Digital Twins: Challenges, Success Factors, and Future Research Directions. In T. Margaria & B. Steffen (Eds.), Leveraging Applications of Formal Methods, Verification and Validation. Specification and Verification - 12th International Symposium, ISoLA 2024, Proceedings (pp. 27-46). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-75390-9_3

Abdolmaleki, H., Astri Bjørnetun Haugen, A., Buhl, K. B., Daasbjerg, K. & Agarwala, S. (2023). Interfacial Engineering of PVDF‐TrFE toward Higher Piezoelectric, Ferroelectric, and Dielectric Performance for Sensing and Energy Harvesting Applications. Advanced Science, 10(6), Article 2205942. https://doi.org/10.1002/advs.202205942

Skov, H., Riishede Christiansen, I. L., Rode, L., Pihl, K., Jørgensen, F. S., Zingenberg, H., Nørgaard, P., Gros Pedersen, N. M., Gjerris, A. C. R., Wagner, S. R., Tabor, A., Ekelund, C. K. & Sandager, P. (2022). Inter-arm blood pressure difference in early pregnancy and risk of preeclampsia. Abstract from FMF 19th World Congress 2022, Kreta, Greece. https://fetalmedicine.org/abstracts/2022/var/pdf/abstracts/2022/04236.pdf

Laakom, F., Raitoharju, J., Nikkanen, J., Iosifidis, A. & Gabbouj, M. (2021). INTEL-TAU: A Color Constancy Dataset. IEEE Access, 9, 39560-39567. Article 9371681. https://doi.org/10.1109/ACCESS.2021.3064382

Boudjadar, J. & Beck, M. M. (2021). Intelligent Time Synchronization Protocol for Energy Efficient Sensor Systems. Paper presented at Intelligent Systems Conference , Amsterdam, Netherlands.

Boudjadar, J. & Beck, M. M. (2022). Intelligent Time Synchronization Protocol for Energy Efficient Sensor Systems. In K. Arai (Ed.), Intelligent Systems and Applications - Proceedings of the 2021 Intelligent Systems Conference IntelliSys (pp. 609-623). Springer Science+Business Media. https://doi.org/10.1007/978-3-030-82196-8_45

Yildirim, B., Gheisarnejad Chirani, M., Mohammadzadeh, A. & Khooban, M. H. (2023). Intelligent frequency stabilization of low-inertia islanded power grids-based redox battery. Journal of Energy Storage, 71, Article 108190. https://doi.org/10.1016/j.est.2023.108190

Fathollahi, A. (2024). Intelligent Control Framework for Improving Energy System Stability Through Deep Learning-Based Modal Optimization Scheme. Sustainability (Switzerland), 16(21), Article 9392. https://doi.org/10.3390/su16219392

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AU Engineering