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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Tran, D. T., Gabbouj, M. & Iosifidis, A. (2022). Progressive and compressive learning. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 187-220). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00014-2

Lillelund, C. M., Harbo, M. & Pedersen, C. F. (2026). Prognosis of fall risk in home care clients: A noninvasive approach using survival analysis. Journal of Public Health. From Theory to Practice, 34(4), 905-917. https://doi.org/10.1007/s10389-024-02317-9

Domini, D., Ingemann, C. O., Aguzzi, G., Esterle, L. & Viroli, M. (2026). ProFed: A Benchmark for Proximity-Based Non-IID Federated Learning. Journal of Open Research Software, 14(1), Artikel 13. https://doi.org/10.5334/jors.624

Kakavandi, F., de Reus, R., Gomes, C., Heidari, N., Iosifidis, A. & Larsen, P. G. (2022). Product Quality Control in Assembly Machine under Data Restricted Settings. I 2022 IEEE 20th International Conference on Industrial Informatics, INDIN 2022 (s. 735-741). IEEE. https://doi.org/10.1109/INDIN51773.2022.9976173

Naveed, K., Madsen, L. M., Grombacher, D. & Larsen, J. J. (2024). Processing Time-domain Induced Polarization Data Using Variational Mode Decomposition. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-13. Artikel 5905713. https://doi.org/10.1109/TGRS.2024.3362290

Hallerstede, S. & Kamburjan, E. (red.) (2023). Proceedings of the Workshop on Applications of Formal Methods and Digital Twins co-located with 25th International Symposium on Formal Methods (FM 2023). CEUR-WS.org. CEUR Workshop Proceedings Bind 3507 https://ceur-ws.org/Vol-3507/

Macedo, H. D. & Pierce, K. (2023). Proceedings of the 21st International Overture Workshop. http://arxiv.org/pdf/2311.07120v2

Macedo, H. D. & Pierce, K. (red.) (2022). Proceedings of the 20th International Overture Workshop. https://doi.org/10.48550/arXiv.2208.10233

Macedo, H. D., Thule, C. & Pierce, K. (2021). Proceedings of the 19th International Overture Workshop. https://arxiv.org/abs/2110.09371

Asplund, F., Macedo, H. D. & Sassanelli, C. (2021). Problematizing the Service Portfolio of Digital Innovation Hubs. I L. M. Camarinha-Matos, X. Boucher & H. Afsarmanesh (red.), Smart and Sustainable Collaborative Networks 4.0 - 22nd IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2021, Proceedings: 22nd IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2021, Saint-Étienne, France, November 22–24, 2021, Proceedings (s. 433-440). Springer. https://doi.org/10.1007/978-3-030-85969-5_40

Sergeeva, A. & Kidmose, P. (2026). Probing Spectral Masking With Auditory Steady-State Responses. Ear and Hearing, 47(5), 1246-1256. Artikel 10.1097/AUD.0000000000001815. Advance online publication. https://doi.org/10.1097/AUD.0000000000001815

Andersen, M. S., Gomes, C., Thompson, S. & Larsen, P. G. (2025). Probabilistic Update Scheduling for Digital Twins: A Semi-Markov Approach. I Proceedings - 2025 ACM/IEEE 28th International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2025 (s. 250-256). IEEE. https://doi.org/10.1109/MODELS-C68889.2025.00043

Katikaridis, D., Benos, L., Kateris, D., Papageorgiou, E., Karras, G., Menexes, I., Berruto, R., Sørensen, C. G. & Bochtis, D. (2026). Proactive Path Planning Using Centralized UAV-UGV Coordination in Semi-Structured Agricultural Environments. Applied Sciences (Switzerland), 16(2), Artikel 1143. https://doi.org/10.3390/app16021143

Zhang, S., Ding, Y., Tang, W., Sun, W., Liao, Y. & Zhou, P. Y. (2025). Privacy-Preserving Orthogonal Aggregation for Guaranteeing Gender Fairness in Federated Recommendation. I WSDM 2025 - Proceedings of the 18th ACM International Conference on Web Search and Data Mining (s. 327-335). Association for Computing Machinery. https://doi.org/10.1145/3701551.3703513

Larsen, E. L., Espelund, U., Lauritsen, S. M., Thiesson, B., Lange, J., Friis Kjeldsen, G. & Jørgensen, M. J. (2022). +Priokritisk. Early identification of clinical detorioriation among hospitalized patients by explainable AI. Poster-session præsenteret på Symposium on Artificial Intelligence for Learning Health Systems.

Merhi, Y., Betancur, P. F., Ripolles, T. S., Suetta, C., Brage-Andersen, M. R., Hansen, S. K., Frydenlund, A., Nygaard, J. V., Mikkelsen, P. H., Boix, P. P. & Agarwala, S. (2023). Printed dry electrode for neuromuscular electrical stimulation (NMES) for e-textile. Nanoscale, 15(11), 5337-5344. https://doi.org/10.1039/d2nr06008f

Homayounzadeh, M., Homayounzade, M. & Khooban, M. H. (2024). Prescribed-time resilient current-sensorless DC power converter control. IET Power Electronics, 17(14), 2123-2133. https://doi.org/10.1049/pel2.12776

Bochtis, D. D., Sørensen, C. G., Fountas, S., Moysiadis, V. & Pardalos, P. M. (2022). Preface. Springer Optimization and Its Applications, 184, v-xiii.

Bowen, J. P., Gomes, C. & Liu, Z. (2025). Preface. I J. P. Bowen, C. Gomes & Z. Liu (red.), Engineering Trustworthy Software Systems (s. vii-xiv). Springer.

Riishede, I., Rode, L., Sperling, L., Overgaard, M., Ravn, J. D., Sandager, P., Skov, H., Wagner, S. R., Nørgaard, P., Clausen, T. D., Jensen, C. A. J., Pihl, K., Jørgensen, F. S., Munk, J. K., Zingenberg, H. J., Pedersen, N. G., Andersen, M. R., Wright, A., Wright, D. ... Ekelund, C. K. (2023). Pre-eclampsia Screening in Denmark (PRESIDE): National Validation Study. Obstetrical and Gynecological Survey, 78(12), 715-717. https://doi.org/10.1097/01.ogx.0001004636.48406.54

Riishede, I., Rode, L., Sperling, L., Ravn, J. D., Sandager, P., Skov, H., Wagner, S. R., Nørgaard, P., Clausen, T. D., Jensen, C. A. J., Pihl, K., Jørgensen, F. S., Munk, J. K., Zingenberg, H. J., Pedersen, N. G., Andersen, M. R., Wright, A., Wright, D., Tabor, A. & Ekelund, C. K. (2023). Pre-eclampsia screening in Denmark (PRESIDE): national validation study. Ultrasound in Obstetrics and Gynecology, 61(6), 682-690. https://doi.org/10.1002/uog.26183

Mazur-Milecka, M., Kowalczyk, N., Jaguszewska, K., Zamkowska, D., Wójcik, D., Preis, K., Skov, H., Wagner, S., Sandager, P., Sobotka, M. & Rumiński, J. (2023). Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data. I P. Strumiłło, A. Klepaczko, M. Strzelecki & D. Bociąga (red.), The Latest Developments and Challenges in Biomedical Engineering: Proceedings of the 23rd Polish Conference on Biocybernetics and Biomedical Engineering, Lodz, Poland, September 27–29, 2023 (s. 267-281). Springer. https://doi.org/10.1007/978-3-031-38430-1_21

Yeh, Y., Kokkinis, G., Zhang, Q., Elayoubi, S. E. & Varma, V. S. (2026). Predictive Hybrid Resource Scheduling for Haptic Traffic with Diffusion-Based Offline Reinforcement Learning. I 2026 24th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and WirelessNetworks, WiOpt 2026 IEEE. https://doi.org/10.23919/WiOpt71098.2026.11568169

Nawoya, S., Geissmann, Q., Karstoft, H., Bjerge, K., Akol, R., Katumba, A., Mwikirize, C. & Gebreyesus, G. (2025). Prediction of black soldier fly larval sex and morphological traits using computer vision and deep learning. Smart Agricultural Technology, 11, Artikel 100953. https://doi.org/10.1016/j.atech.2025.100953

Baltakys, K., Baltakienė, M., Heidari, N., Iosifidis, A. & Kanniainen, J. (2023). Predicting the trading behavior of socially connected investors: Graph neural network approach with implications to market surveillance. Expert Systems with Applications, 228, Artikel 120285. https://doi.org/10.1016/j.eswa.2023.120285

Shabani, M., Magris, M., Tzagkarakis, G., Kanniainen, J. & Iosifidis, A. (2023). Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots. Neural Computing and Applications, 35(25), 18519–18531. https://doi.org/10.1007/s00521-023-08674-y

Lillelund, C. M., Pannullo, F., Jakobsen, M. O. & Pedersen, C. F. (2023). Predicting Survival Time of Ball Bearings in the Presence of Censoring. I AAAI Symposium on Survival Prediction: Algorithms, Challenges, and Applications (SPACA) AAAI Press.

Bagheri Tookanlou, P., Pourmoayed, R., Grøn Sørensen, C. & Nørremark, M. (2025). Predicting readiness of arable land and scheduling of tillage operations using finite-horizon Markov decision process and Gaussian state space models. The Open Operational Research Journal, 25(4), Artikel 92. https://doi.org/10.1007/s12351-025-00964-8

Khawaja, W., Jacobsen, R. H., Hussain, S. & Guvenc, I. (2025). Predicting Lifespan of Ground-to-Air Multipath Components in mmWave UAV Channels. I 2025 IEEE Wireless Communications and Networking Conference, WCNC 2025 IEEE. https://doi.org/10.1109/WCNC61545.2025.10978787

Kragh, M. F., Rimestad, J., Lassen, J. T., Berntsen, J. & Karstoft, H. (2022). Predicting embryo viability based on self-supervised alignment of time-lapse videos. IEEE Transactions on Medical Imaging, 41(2), 465-475. https://doi.org/10.1109/TMI.2021.3116986

Evans, V. T., Gomes, C. & Lucani Rötter, D. E. (2025). Precision on Demand: Propositional Logic for Event-Trigger Threshold Regulation. IEEE Internet of Things Journal, 12(3), 2674-2689. https://doi.org/10.1109/JIOT.2024.3476922

D’Ambrosio, F., Harbo, M., Contiero, D., Bonfigli, A. R., Cicconi, D., Heuer, N., Roos, A., Pedersen, C. F., Fabbietti, P. & Gagliardi, C. (2024). Preact to lower the risk of falling by customized rehabilitation across Europe: the feasibility study protocol of the PRECISE project in Italy. Frontiers in Public Health, 12, Artikel 1293621. https://doi.org/10.3389/fpubh.2024.1293621

Fathollahi, A. & Andresen, B. (2025). Power Quality Analysis and Improvement of Power-to-X Plants Using Digital Twins: A Practical Application in Denmark. IEEE Transactions on Energy Conversion, 40(3), 1909-1921. https://doi.org/10.1109/TEC.2025.3531113

Hatamzadeh, E. (2026). Power Management IC Design for IoT Applications. [Ph.d.-afhandling, Aarhus Universitet].

Jeppesen, J. H., Nørremark, M. & Jacobsen, R. H. (2022). Potato Cyst Nematode Detection based on Open Satellite Data. DCA - Nationalt Center for Fødevarer og Jordbrug. Advisory report from DCA – National Center for Food and Agriculture

Schranz, T., Legaard, C. M., Tola, D. & Schweiger, G. (2021). Portable runtime environments for Python-based FMUs: Adding Docker support to UniFMU. I Proceedings of 14th Modelica Conference 2021 (s. 419-424) https://doi.org/10.3384/ecp21181419

Kamari, A., Petersen, J. H. & Schultz, C. P. L. (2021). Popularizing DGNB in the Danish construction industry: A field study of the industry via a qualitative comparative analysis. I Proceedings of the 38th International Conference of CIB W78, Luxembourg, 13-15 October: Joint Conference CIB W78 - LDAC 2021 (s. 638-649). Artikel 64. http://itc.scix.net/paper/w78-2021-paper-064

Møller, C., Celma-Miralles, A., Borges, H. B., Stupacher, J., Christensen, C. B., Vuust, P. & Kidmose, P. (2026). Polyrhythms in the Brain: Metrical Priming, Acoustic Balance, and Perceptual Biases. Annals of the New York Academy of Sciences, 1559(1), Artikel e70290. https://doi.org/10.1111/nyas.70290

Godoy, P. H., Ahler, L. C., Thomsen, S. T., Ulsig, E. Z. & Volet, N. (2025). Platform-Dependent Feasibility of All-Optical Switching in Photonic Integrated Circuits. I Advanced Photonics Congress (IPR, Networks, NOMA, SOLITH, SPPCom) https://doi.org/10.1364/IPRSN.2025.IW2A.5

Henriksen, M. L., Karlsen, C. B., Klarskov, P. & Hinge, M. (2022). Plastic classification via in-line hyperspectral camera analysis and unsupervised machine learning. Vibrational Spectroscopy, 118, Artikel 103329. https://doi.org/10.1016/j.vibspec.2021.103329

Garval, M., Pedersen, L., Pedersen, L. M., Nielsen, A. K. W. D. J., Christiansen, D. H., Lange, J. & Wagner, S. (2026). Placement-Dependent Accuracy of a Smartphone-Based Sensor Application Compared to an Accelerometer-Based System for Measuring Physical Activity in Healthy Adults: A Validation Study. Sensors, 26(7), Artikel 2033. https://doi.org/10.3390/s26072033

Nørremark, M. (2022). Pilot project on precision farming. 4. Abstract fra Advances and Innovations in Agricultural Engineering., Herning, Danmark.

Merhi, Y. (2025). Piezoelectric and Crystallinity Enhancements in Poly-L-Lactide Acid (PLLA) for Bioresorbable Biomedical Sensor. [Ph.d.-afhandling, Aarhus Universitet].

Raj, R. K., Verma, R. S., Jony, S. H., Saini, S. & Shreya, S. (2026). Physics-informed analytical modeling of dzyaloshinskii-moriya interaction gradient-driven magnetic skyrmion. Journal of Magnetism and Magnetic Materials, 648, Artikel 174022. https://doi.org/10.1016/j.jmmm.2026.174022

Zehtabiyan-Rezaie, N., Iosifidis, A. & Abkar, M. (2023). Physics-Guided Machine Learning for Wind-Farm Power Prediction: Toward Interpretability and Generalizability. PRX Energy, 2(1), Artikel 013009. https://doi.org/10.1103/PRXEnergy.2.013009

Rasmussen, S. M., Nielsen, T., Hody, S., Hager, H. & Schousboe, L. P. (2021). Photoplethysmography for demarcation of cutaneous squamous cell carcinoma. Scientific Reports, 11, Artikel 21467. https://doi.org/10.1038/s41598-021-00645-4

Rasool, S. & Jacobsen, R. H. (2025). Perspective Chapter: Leveraging Self-Sovereign Identity to Introduce ReCert: A Foundational Framework for Decentralized BCTE Solutions. I Blockchain - Pioneering the Web3 Infrastructure for an Intelligent Future InTechOpen. https://doi.org/10.5772/intechopen.1007156

Jeppesen, J., Christensen, J., Johansen, P. & Beniczky, S. (2023). Personalized seizure detection using logistic regression machine learning based on wearable ECG-monitoring device. Seizure, 107, 155-161. https://doi.org/10.1016/j.seizure.2023.04.012

Lorenzen, K. P., Heremans, E. R. M., Vos, M. D. & Mikkelsen, K. B. (2024). Personalization of Automatic Sleep Scoring: How Best to Adapt Models to Personal Domains in Wearable EEG. IEEE Journal of Biomedical and Health Informatics, 28(10), 5804-5815. https://doi.org/10.1109/JBHI.2024.3409165

Mohammadi, S., Pahlevani, P. & Lucani, D. E. (2021). Perpetual Network Coding for Delay Sensitive Applications. Wireless Personal Communications, 120(2), 923-947. https://doi.org/10.1007/s11277-021-08497-x

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