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

Sort by: Date | Author | Title

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 and Fractional, 7(4), Article 343. https://doi.org/10.3390/fractalfract7040343

Kashem, A., Anzer, A., Jagirdar, R., Sojib, M. S., Farooq, F. & Das, P. (2025). Metaheuristic-based machine learning approaches of compressive strength forecasting of steel fiber reinforced concrete with SHapley Additive exPlanations. Multiscale and Multidisciplinary Modeling, Experiments and Design, 8(1), Article 61. https://doi.org/10.1007/s41939-024-00656-4

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), Article 3763. https://doi.org/10.3390/ma14133763

D'Inverno, G. A., Moradizadeh, S., Salavatidezfouli, S., Africa, P. C. & Rozza, G. (2025). Mesh-informed Reduced Order Models for aneurysm rupture risk prediction. Journal of Computational and Applied Mathematics, 470, Article 116727. https://doi.org/10.1016/j.cam.2025.116727

Tofte, A., Shreya, S., Ghanatian Najafabadi, H., Böhnert, T., Ferreira, R., Farkhani, H. & Moradi, F. (2022). Memory and Communication Logic (MCL) in Magnetic Tunnel Junctions. Poster session presented at Trends in MAGnetism-PetaSpin Conference, Italy.

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, 13, Article 4505605. https://doi.org/10.1109/LMAG.2022.3224676

Kilic, K., Vægter, H. B., Bruun, K. D., Vach, W., Hartvigsen, J., Koes, B. W., Kidmose, P., Søndergaard, J. & Thorlund, J. B. (2025). Melatonin for chronic back pain (the MOCHA trial): study protocol for a randomized, double-blind, placebo-controlled trial. Current Controlled Trials in Cardiovascular Medicine, 26(1), Article 513. https://doi.org/10.1186/s13063-025-09206-w

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

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

Dobbs, A. M., Goldsmith, A. S., Ginn, D., Skovsen, S. K., Bagavathiannan, M. V., Mirsky, S. B., Reberg-Horton, C. S. & Leon, R. G. (2024). Mapping predicted biomass in cereal rye using 3D imaging and geostatistics. Weed Science, 72(5), 553-561. https://doi.org/10.1017/wsc.2024.62

Cai, X., Pan, G., Chen, H., Wymeersch, H. & Cheng, H. V. (2026). Map-aided ISAC Beam Design via Active Sensing. IEEE Wireless Communications Letters, 15, 3064-3068. https://doi.org/10.1109/LWC.2026.3682799

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, IN4PL 2021 (pp. 49-58). SCITEPRESS Digital Library. https://doi.org/10.5220/0010641700003062

Magris, M., Shabani, M. & Iosifidis, A. (2024). Manifold Gaussian Variational Bayes on the Precision Matrix. Neural Computation, 36(9), 1744-1798. https://doi.org/10.1162/neco_a_01686

Oberbauer, F., Winkel, T. J., Böhnert, T., Wanjura, C. C., Claro, M. S., Benetti, L., Çaha, I., Deepak, F. L., Moradi, F., Ferreira, R., Münzenberg, M. & Parvini, T. S. (2025). Magnetic tunnel junctions driven by hybrid optical-electrical signals as a flexible neuromorphic computing platform. Communications Physics, 8(1), Article 329. https://doi.org/10.1038/s42005-025-02257-0

Esterle, L., Montagna, S., Pianini, D., Aguzzi, G., Bellman, K. L., Ciatto, G., Contoli, C., Donati, M., Mariani, S., Rahmani, A., Savaglio, C., Storti, E., TaheriNejad, N., van der Sluis, O. & Wang, Z. (2024). MADTECC 2024: 1st Workshop on Medical Applications with Digital Twins and Edge-cloud Continuum - Welcome and Committees. In 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (pp. 30-31). IEEE. https://doi.org/10.1109/PerComWorkshops59983.2024.10502899

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), Article 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) Article V006T06A031 American Society of Mechanical Engineers. https://doi.org/10.1115/DETC2020-22483

Jensen, R. I. T. (2024). Machine Learning for Anti-money Laundering. [PhD dissertation, Aarhus University]. Aarhus Universitet.

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

Lauritsen, S. M. (2022). MACHINE LEARNING BASED PREDICTION OF CLINICAL DETERIORATION IN GENERAL WARDS. [PhD dissertation, Aarhus University].

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, Article 104290. https://doi.org/10.1016/j.jappgeo.2021.104290

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 dissertation, 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 dissertation, Aarhus University]. Aarhus Universitet.

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

Gardner, A. B., Siddharth, A., Reichler, M., Hulyal, S. U., Attanasio, A., Ji, X., Bhave, S., Volet, N., Blanconi, S. & Kippenberg, T. J. (2025). Low-Noise, Frequency-Agile Photonic Integrated Blue Laser for LiDAR and Underwater Communication. In 2025 European Conference on Optical Communications, ECOC 2025 IEEE. https://doi.org/10.1109/ECOC66593.2025.11262955

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 Press. https://doi.org/10.1109/HSI66212.2025.11142434

Sah, D., Parfeniukas, K., Boccardi, R., Bandaru, N., Lachowicz, A., Salomon, B. P., Borie, B., Baraket, M., Plakhotnyuk, M., Dos Reis Benatto, G. A., Thorsteinsson, S., Poulsen, P. B. & Davidsen, R. S. (2026). Local edge passivation of laser-scribed cells for compensating cut losses. Solar Energy Materials and Solar Cells, 299, Article 114178. https://doi.org/10.1016/j.solmat.2026.114178

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

Displaying results 601 to 650 out of 1477

Revised 30.12.2025

AU Engineering