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 for example journal articles, books, reports etc.

The department also publishes technical reports which you can read more about under Technical reports.

Under PhD dissertations you will find the department's published PhD dissertations.

Publication list

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Cai, X. & Cheng, H. V. (2024). Array Pattern Synthesis with Discrete Phases for Reconfigurable Intelligent Surfaces. In 2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) (pp. 741 - 745). IEEE. https://doi.org/10.1109/SPAWC60668.2024.10694155

Cai, X. & Cheng, H. V. (2023). Direct Channel Estimation Between MIMO Transmitter and Reconfigurable Intelligent Surface. In IEEE Conference on Global Communications (GLOBECOM) (pp. 4217-4222). IEEE. https://doi.org/10.1109/GLOBECOM54140.2023.10437250

Çabuk, U. C., Tosun, M., Jacobsen, R. H. & Dagdeviren, O. (2020). Path Loss Estimation of Air-to-Air Channels for FANETs over Rugged Terrains. In 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings Article 9302160 IEEE. https://doi.org/10.1109/SIU49456.2020.9302160

Çabuk, U. C., Tosun, M., Jacobsen, R. H. & Dagdeviren, O. (2020). A Holistic Energy Model for Drones. In 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings Article 9302218 IEEE. https://doi.org/10.1109/SIU49456.2020.9302218

Brusatori, M. F. & Volet, N. (2021). Revised theory for the linewidth of diode lasers under external optical feedback. In V. S. Ilchenko, A. M. Armani, J. V. Sheldakova, A. V. Kudryashov & A. H. Paxton (Eds.), Laser Resonators, Microresonators, and Beam Control XXIII Article 1167211 SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2583210

Brusatori, M. F. & Volet, N. (2022). Dynamics of Semiconductor Lasers under External Optical Feedback from Both Sides of the Laser Cavity. Photonics, 9(1), Article 43. https://doi.org/10.3390/photonics9010043

Brusatori, M. F., Duplat, D. N., Degli-Eredi, I., Nielsen, L., Tønning, P. L., Castera, P., Volet, N. & Heck, M. J. R. (2022). Ultralow-linewidth ring laser using hybrid integration and generic foundry platforms. Optics Letters, 47(11), 2686-2689. https://doi.org/10.1364/OL.457367

Bro Damsgaard, S., Hernandez Marcano, N. J., Nørremark, M., Jacobsen, R. H., Rodríguez, I. & Mogensen, P. (2022). Wireless Communications for Internet of Farming: An Early 5G Measurement Study. IEEE Access, 10, 105263-105277. https://doi.org/10.1109/ACCESS.2022.3211096

Brask, M. J., Kai, P. & Nørremark, M., (2025). Supplerende spørgsmål til rapport om Miljø- og Klimateknologi 2025, No. 2025-0822982, 14 p., Apr 11, 2025. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Brandt, P., Grønvig, M., Rong, L., Zhang, G., Gautam, K. R., Kristensen, J. K. & Bjerg, B. (2022). The effect of floor cooling on respiration rate and distribution of pigs in the pen. Livestock Science, 257, Article 104832. https://doi.org/10.1016/j.livsci.2022.104832

Bozorgasli, Z., Foroozan, H., Gheisarnejad Chirani, M. & Khooban, M. H. (2021). New Trends on Digital Twin-Based Blockchain Technology in Zero-Emission Ship Applications. Naval Engineers Journal, 133(3), 115-135. http://bt.e-ditionsbyfry.com/publication/?m=63540&i=721756&view=articleBrowser&article_id=4109541&ver=html5

Bozcan, I. & Kayacan, E. (2020). UAV-AdNet: Unsupervised Anomaly Detection using Deep Neural Networks for Aerial Surveillance. In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 1158-1164). Article 9341790 IEEE. https://doi.org/10.1109/IROS45743.2020.9341790

Bozcan, I., Sejersen, J. L. F., Pham, X. H. & Kayacan, E. (2021). GridNet: Image-Agnostic Conditional Anomaly Detection for Indoor Surveillance. IEEE Robotics and Automation Letters, 6(2), 1638 - 1645. Article 9345954. https://doi.org/10.1109/LRA.2021.3057003

Bozcan, I. & Kayacan, E. (2020). Contextual Anomaly Detection for Low Altitude Aerial Surveillance.

Bozcan, I. (2021). Learning-based Anomaly Detection for Aerial Surveillance. Århus Universitet.

Boudjadar, J. (2020). A Study of the Trade-off Energy Consumption-Performance-Schedulability for DVFS Multicore Systems. International Journal of Computer and Information Engineering, 14(11), 380-391.

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. & Khooban, M. H. (2021). A Safety-Driven Cost Optimization for the Real-Time Operation of a Hybrid Energy System. In H. Selvaraj, G. Chmaj & D. Zydek (Eds.), Proceedings of the 27th International Conference on Systems Engineering, ICSEng 2020 (pp. 390-400). Springer. https://doi.org/10.1007/978-3-030-65796-3_38

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 and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-82196-8_45

Boudjadar, J. (2022). A Digital Twin Setup for Safety-aware Optimization of a Cyber-Physical System. Paper presented at International Conference on Informatics in Control, Automation and Robotics, Lisbon, Portugal.

Boudjadar, J. (2022). A Flexible Implementation Model for Neural Networks on FPGAs. Paper presented at International Conference on Intelligent Systems Design and Applications.

Boudjadar, J. & Schultz, C. P. L. (2023). A Knowledge-Based Proactive Intelligent System for Buildings Occupancy Monitoring. 680-687. Paper presented at 19th International Conference on Software Technologies, Rome, Italy.

Boudjadar, J. & Islam, S. U. (2024). AgriScanNet-18: A Robust Multilayer CNN for Identification of Potato Plant Diseases. 291-308. Paper presented at Intelligent Systems Conference, Amsterdam, Netherlands. https://doi.org/10.1007/978-3-031-47724-9_20

Boudjadar, J., Islam, S. U. & Buyya, R. (2025). Dynamic FPGA reconfiguration for scalable embedded artificial intelligence (AI): A co-design methodology for convolutional neural networks (CNN) acceleration. Future Generation Computer Systems, 169, Article 107777. https://doi.org/10.1016/j.future.2025.107777

Böttjer, T., Sandberg, M., Larsen, P. G. & Macedo, H. D. (2021). Modelling an Injection Moulding Machine using the Vienna Development Method. In H. D. Macedo, C. Thule & K. Pierce (Eds.), Proceedings of the 19th International Overture Workshop (pp. 51-65) https://arxiv.org/abs/2110.09371

Böttjer, T., Ørnskov Rønsch, G., Gonçalves Gomes, C. Â., Ramanujan, D., Iosifidis, A. & Larsen, P. G. (2021). Data-Driven Identification of Remaining Useful Life for Plastic Injection Moulds. In A.-L. Andersen, R. Andersen, D. Brunoe, M. Stoettrup Schioenning Larsen, K. Nielsen, A. Napoleone & S. Kjeldgaard (Eds.), Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems: Proceedings of the Changeable, Agile, Reconﬁgurable and Virtual Production Conference and the World Mass Customization & Personalization Conference (pp. 431-439). Springer. https://www.springerprofessional.de/en/data-driven-identification-of-remaining-useful-life-for-plastic-/19816878

Böttjer, T., Ørnskov Rønsch, G., Gomes, C., Ramanujan, D., Iosifidis, A. & Larsen, P. G. (2022). Data-Driven Identification of Remaining Useful Life for Plastic Injection Moulds. In A.-L. Andersen, R. Andersen, T. D. Brunoe, M. Stoettrup Schioenning Larsen, K. Nielsen, A. Napoleone & S. Kjeldgaard (Eds.), Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems - Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference CARV 2021 and 10th World Mass Customization and Personalization Conference MCPC 2021 (pp. 431-439). Springer. https://doi.org/10.1007/978-3-030-90700-6_49

Böttjer, T., Tola, D., Kakavandi, F., Wewer, C. R., Ramanujan, D., Gomes, C., Larsen, P. G. & Iosifidis, A. (2023). A review of unit level digital twin applications in the manufacturing industry. CIRP Journal of Manufacturing Science and Technology, 45, 162-189. https://doi.org/10.1016/j.cirpj.2023.06.011

Böttjer, T. (2024). Towards Manufacturing Digital Twins: A Case Study in the Injection Moulding Industry. Section of Electrical and Computer Engineering, Department of Engineering, Aarhus University, DK.

Borup, K., Kidmose, P., Phan, H. & Mikkelsen, K. (2023). Automatic sleep scoring using patient-specific ensemble models and knowledge distillation for ear-EEG data. Biomedical Signal Processing and Control, 81, Article 104496. https://doi.org/10.1016/j.bspc.2022.104496

Borges, H. B. (2025). Neural Correlates of Speech Intelligibility.

Borges, H. B., Kidmose, P., Christensen, C. B., Alickovic, E. & Zaar, J. (2024). Speech Reception Threshold Estimation via EEG-Based Continuous Speech Envelope Reconstruction.

Borges, H. B. (2024). The Speech Reception Threshold Can be Estimated Using EEG Electrodes In and Around the Ear.

Borges, H. B., Christensen, C. B., Kidmose, P., Alickovic, E. & Zaar, J. (2025). Speech Reception Threshold Estimation via EEG-Based Continuous Speech Envelope Reconstruction. European Journal of Neuroscience, 61(6). https://doi.org/10.1111/ejn.70083

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

Böhnert, T., Rezaeiyan, Y., Claro, M. S., Benetti, L., Jenkins, A. S., Farkhani, H., Moradi, F. & Ferreira, R. (2023). Weighted spin torque nano-oscillator system for neuromorphic computing. Nature Communication Engineering, 2, Article 65. https://doi.org/10.1038/s44172-023-00117-9

Bogomolov, S., Fitzgerald, J., Foldager, F. F., Gamble, C., Larsen, P. G., Pierce, K., Stankaitis, P. & Wooding, B. (2021). Tuning Robotti: the Machine-assisted Exploration of Parameter Spaces in Multi-Models of a Cyber-Physical System. In J. Fitzgerald, T. Oda & H. D. Macedo (Eds.), Proceedings of the 18th International Overture Workshop (pp. 50-65) https://arxiv.org/pdf/2101.07261.pdf

Bogomolov, S., Gomes, C., Isasa, C., Soudjani, S., Stankaitis, P. & Wright, T. (2025). Reachability analysis of FMI models using data-driven dynamic sensitivity. Simulation, 101(5), 575-596. https://doi.org/10.1177/00375497241261409

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

Bochtis, D., Sørensen, C. A. G., Jørgensen, R. N. & Green, O. (2009). Modelling of material handling operations using controlled traffic. Biosystems Engineering, 103(4), 397-408. https://doi.org/10.1016/j.biosystemseng.2009.02.006

Bochtis, D. & Grøn Sørensen, C. (2010). Agricultural fleet management: an operational research approach. Paper presented at World Congress of the International Commission of Agricultural and Biosystems Engineering (CIGR), Quebec, Canada. http://bioeng.ca/publications/meetings-papers?sobi2Task=sobi2Details&sobi2Id=383

Bochtis, D. & Grøn Sørensen, C. (2010). Agricultural fleet management: An operational research approach. In P. Savoie, J. Villeneuve & R. Morisette (Eds.), XVIIth World Congress of the International Commission of Agricultural and Biosystems Engineering, Book of Abstracts (pp. 212) https://www.researchgate.net/publication/267331059_AGRICULTURAL_FLEET_MANAGEMENT_AN_OPERATIONAL_RESEARCH_APPROACH

Bochtis, D., Sørensen, C. A. G., Jørgensen, R. N., Nørremark, M., Hameed, I. A. & Swain, K. C. (2011). Robotic weed monitoring. Acta Agriculturae Scandinavica, Section B - Soil & Plant Science, 61(3), 202-208. https://doi.org/10.1080/09064711003796428

Bochtis, D. D., Grøn Sørensen, C., Busato, P. & Berruto, R. (2013). Benefits from optimal route planning based on B-patterns. Biosystems Engineering, 115(4), 389-395. https://doi.org/10.1016/j.biosystemseng.2013.04.006

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

Bliddal, H., Christensen, C. B., Møller, C., Vuust, P. & Kidmose, P. (2021). Neural correlates of beat perception measured using ear-EEG: Bringing EEG music studies into the concert hall . Poster session presented at Rhythm Production and Perception Workshop 2021, Oslo, Norway.

Bliddal, H., Christensen, C. B., Møller, C., Vuust, P. & Kidmose, P. (2021). Neural correlates of beat perception measured using ear-EEG. Poster session presented at Advances and Perspectives in Auditory Neuroscience, United States.

Bjerge, K., Schougaard, J. H. & Larsen, D. E. (2021). A scalable and efficient convolutional neural network accelerator using HLS for a system-on-chip design. Microprocessors and Microsystems, 87, Article 104363. https://doi.org/10.1016/j.micpro.2021.104363

Bjerge, K., Mann, H. M. R. & Høye, T. T. (2022). Real-time insect tracking and monitoring with computer vision and deep learning. Remote Sensing in Ecology and Conservation, 8(3), 315-327. https://doi.org/10.1002/rse2.245

Bjerge, K., Alison, J., Dyrmann, M., Frigaard, C. E., Mann, H. M. R. & Høye, T. T. (2022). Accurate detection and identification of insects from camera trap images with deep learning. bioRxiv. https://doi.org/10.1101/2022.10.25.513484

Displaying results 951 to 1000 out of 1143

Technical reports

Department of Electrical and Computer Engineering publishes technical reports covering our research areas.

With the reports, we wish to communicate the newest knowledge and research to society ahead of and during the publication process which can take up to a year.

Read the technical reports by following the link below:

Technical Report Department of Electrical and Computer Engineering

PhD dissertations

At the Department of Electrical and Computer Engineering, PhD dissertations are published via Aarhus University Library's/State and University Library's online E-books platform that is open access. You can find the published dissertations by following the link below.

PhD dissertations at Department of Electrical and Computer Engineering

AU Engineering Profile

Download AU Engineering Profile 2013-2022:

Revised 22.02.2024

AU Engineering