Publikationer fra instituttet

Under publikationsliste finder du en samlet liste over de publikationer, som er lavet af medarbejdere ved Institut for Elektro- og Computerteknologi.

Publikationsliste

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Liu, J. (2020). Mobile Edge Computing in 5G. [Ph.d.-afhandling, Aarhus Universitet].

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

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

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. Artikel 9328872. https://doi.org/10.1109/TCSII.2021.3053160

Aubard, M., Quijano, S., Alvarez Tunon, O., Antal, L. & Brodskiy, Y. (2024). Mission Planning and Safety Assessment for Pipeline Inspection Using Autonomous Underwater Vehicles: A Framework based on Behavior Trees. I OCEANS 2024 - Singapore IEEE. https://doi.org/10.1109/OCEANS51537.2024.10682385

Macedo, H. D. & Touili, T. (2013). Mining Malware Specifications through Static Reachability Analysis.

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

Alvarez Tunon, O., Kanner, H., Ribeiro Marnet, L., Pham, X. H., Sejersen, J. L. F., Brodskiy, Y. & Kayacan, E. (2023). MIMIR-UW: A Multipurpose Synthetic Dataset for Underwater Navigation and Inspection. I 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (s. 6141-6148). IEEE. https://doi.org/10.1109/IROS55552.2023.10341436

Nørremark, M., Kristensen, E. F., Jensen, M., Ottosen, C.-O., Petridis, A., Mendanha dos Santos, T., Melander, B. & Jensen, P. K. (2024). Miljøpositivliste for producentorganisationers driftsfonde til støtteberettigede teknologier til frugt- og grøntsagssektoren 2024. DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug

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

Nørremark, M., Adamsen, A. P. S., Brask, M. J., Børsting, C. F., Hansen, M. J., Kai, P. & Ottosen, C.-O. (2025). Miljø- og Klimateknologi 2025. DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug

Nørremark, M., Hansen, M. J., Kai, P., Børsting, C. F., Ottosen, C.-O., Konnerup, D., Jensen, P. K. & Melander, B. (2023). Miljø- og Klimateknologi 2023. DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug DCA rapport Nr. 221 https://dcapub.au.dk/djfpublikation/djfpdf/DCArapport221.pdf

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

Madsen, M. L., Ulsig, E. Z., Folsach, S., Godoy, P. H., Stanton, E. J. & Volet, N. (2023). Mid-infrared difference-frequency generation in AlGaAs-on-insulator waveguides. Journal of the Optical Society of America B: Optical Physics, 40(7), 1742-1748. https://doi.org/10.1364/JOSAB.488065

Khezri, R., Mahmoudi, A. & Khooban, M. H. (2021). Microgrids planning for residential electrification in rural areas. I S. Padmanaban, P. Sivaraman, C. Sharmeela & J. B. Holm-Nielsen (red.), Residential Microgrids and Rural Electrifications (s. 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), Artikel 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), Artikel 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), Artikel 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, Artikel 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 præsenteret på Trends in MAGnetism-PetaSpin Conference, Italien.

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, Artikel 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. Trials, 26(1), Artikel 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. [Ph.d.-afhandling, Aarhus Universitet]. 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. I 2021 International Balkan Conference on Communications and Networking, BalkanCom 2021 (s. 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

Weiß., G., Pietraroia., D., Sassanelli., C. & Macedo., H. (2021). Manufacturing Process Simulation in a Hybrid Cloud Setup. I Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2021 (s. 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), Artikel 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. I 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (s. 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), Artikel 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. I 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) Artikel V006T06A031 American Society of Mechanical Engineers. https://doi.org/10.1115/DETC2020-22483

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

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. [Ph.d.-afhandling, Aarhus Universitet].

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, Artikel 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), Artikel 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. Artikel 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), Artikel 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), Artikel 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. I 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), Artikel 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. I 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (s. 2156-2161). Artikel 9308440 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308440

Spasaro, M. (2021). Low-Power Radio-Frequency Low Noise Amplifiers for Future Wireless Transceivers. [Ph.d.-afhandling, Aarhus Universitet]. 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. I 2023 IEEE Nanotechnology Materials and Devices Conference (NMDC) (s. 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. [Ph.d.-afhandling, Aarhus Universitet]. Aarhus Universitet.

Sadeghi, M. (2025). Low-Power ASIC Design of a Programmable Spiking Neural Network Platform. [Ph.d.-afhandling, Aarhus Universitet].

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. I 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. I R. G. Baets, P. O'Brien & L. Vivien (red.), Integrated Photonics Platforms II Artikel 1214806 SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2621540

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