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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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Tola, D., Böttjer, T., Larsen, P. G. & Esterle, L. (2022). Towards Modular Digital Twins of Robot Systems. In Proceedings - 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2022 (pp. 95-100). IEEE. https://doi.org/10.1109/ACSOSC56246.2022.00040
Tola, D. & Corke, P. (2023). Understanding URDF: A Survey Based on User Experience. In Y. Jingang (Ed.), 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE) IEEE. https://doi.org/10.1109/CASE56687.2023.10260660
Tola, D. & Corke, P. (2024). Understanding URDF: A Dataset and Analysis. IEEE Robotics and Automation Letters, 9(5), 4479-4486. Article 10478618. https://doi.org/10.1109/LRA.2024.3381482
Tola, D. (2024). Enabling Digitalization in Modular Robotic Systems Integration. [PhD dissertation, Aarhus University]. Aarhus Universitet.
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.
Todnem Bach Christensen, L., Straadt, D., Vassis, S., Lillelund, C. M., Stoustrup, P. B., Pauwels, R., Pedersen, T. K. & Pedersen, C. F. (2024). An Explainable and Conformal AI Model to Detect Temporomandibular Joint Involvement in Children Suffering from Juvenile Idiopathic Arthritis. In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA (pp. 1-4). IEEE. https://doi.org/10.1109/EMBC53108.2024.10781771
Thule, C., Gomes, C. & Lausdahl, K. G. (2020). Formally Verified FMI Enabled External Data Broker: Rabbitmq FMU. In Proceedings of the 2020 Summer Simulation Conference (Vol. 52, pp. 254-265). Article 12 Association for Computing Machinery. https://doi.org/10.5555/3427510.3427533
Thrysøe, S. A. (2021). Educating biomedical 3D printing engineers. Transactions on Additive Manufacturing Meets Medicine , 3(1), Article 512. https://doi.org/10.18416/AMMM.2021.2109512
Thomsen, A. K., Rasmussen, B. S., Frasheri, M., Gil Arboleda, S. & Larsen, P. G. (2025). Towards Digital Twin Aided Autonomy for a UR3e Robotic Manipulator. In A. Cavalcanti, S. Foster & R. Richardson (Eds.), Towards Autonomous Robotic Systems (pp. 295-309). Springer. https://doi.org/10.1007/978-3-032-01486-3_24
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
Teizer, J., Johansen, K. W. & Schultz, C. P. L. (2022). The Concept of Digital Twin for Construction Safety. In F. Jazizadeh, T. Shealy & M. J. Garvin (Eds.), Construction Research Congress 2022: Computer Applications, Automation, and Data Analytics (pp. 1156-1165). American Society of Civil Engineers. https://doi.org/10.1061/9780784483961.121
Teimouri, A., Fathollahi, A., Raeiszadeh, M., Rezaei, M. & Mosavi, A. (2026). High-Speed Fault Detection and Location Approach for Multilevel Inverters Using Deep Learning and Reliability Evaluation. IEEE Open Journal of the Industrial Electronics Society, 7, 291-312. https://doi.org/10.1109/OJIES.2026.3651309
Tcherniak, D., Talasila, P., Ulriksen, M. D., Abbiati, G., Mahato, S. & Jensen, A. M. D. (2025). Efficient system identification, model updating, and virtual sensing in the Digital-Twin-as-a-Service software platform. In M. Dohler, A. Melot & M. A. Lopez (Eds.), Proceedings of the 11th International Operational Modal Analysis Conference, IOMAC 2025 (pp. 271-279). International Operational Modal Analysis Conference (IOMAC). https://iomac2025.sciencesconf.org/596439/document
Taurone, F., Lucani Rötter, D. E., Fehér, M. & Zhang, Q. (2023). Change a Bit to save Bytes: Compression for Floating Point Time-Series Data. In M. Zorzi, M. Tao & W. Saad (Eds.), ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance (pp. 3756-3761). IEEE. https://doi.org/10.1109/ICC45041.2023.10279204
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
Taurone, F., Dorsch, J., Lucani Rötter, D. E. & Zhang, Q. (2024). triaGeD: using compression for anomaly detection. In A. Bilgin, J. E. Fowler, J. Serra-Sagrista, Y. Ye & J. A. Storer (Eds.), Proceedings - DCC 2024: 2024 Data Compression Conference (pp. 588-588). IEEE. https://doi.org/10.1109/DCC58796.2024.00105
Taurone, F., Fehér, M., Sipos, M. & Lucani Rötter, D. E. (2024). TREAT - Two wRongs makE A righT: Efficient distributed storage and queries of IoT datasets with erasure coding and compression. In DEBS 2024: Proceedings of the 18th ACM International Conference on Distributed and Event-Based Systems (pp. 147-158). Association for Computing Machinery. https://doi.org/10.1145/3629104.3666039
Tashakor, N., Naseri, F., Fang, J., Schotten, H. & Goetz, S. (2022). Voltage and Resistance Estimation of Battery-Integrated Cascaded Converters. In IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society IEEE. https://doi.org/10.1109/IECON49645.2022.9968369
Tang, W., Cao, Y., Ying, J., Wang, B., Zhao, Y., Liao, Y. & Zhou, P. (2024). A + B: A General Generator-Reader Framework for Optimizing LLMs to Unleash Synergy Potential. In L.-W. Ku, A. Martins & V. Srikumar (Eds.), The 62nd Annual Meeting of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics, ACL 2024 (pp. 3670-3685). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.findings-acl.219
Tang, P., Luo, X. & Woodcock, J. (2025). Auto-Encoding Neural Tucker Factorization. IEEE Transactions on Knowledge and Data Engineering, 37(10), 5795-5807. https://doi.org/10.1109/TKDE.2025.3590198
Tamirat, T. W., Pedersen, S. M., Farquharson, R. J., de Bruin, S., Forristal, P. D., Sørensen, C. G., Nuyttens, D., Pedersen, H. H. & Thomsen, M. N. (2022). Controlled traffic farming and field traffic management: Perceptions of farmers groups from Northern and Western European countries. Soil and Tillage Research, 217, Article 105288. https://doi.org/10.1016/j.still.2021.105288
Talasila, P., Mikkelsen, P. H., Gil Arboleda, S. & Larsen, P. G. (2024). Realising Digital Twins. In J. Fitzgerald, C. Gomes & P. G. Larsen (Eds.), The Engineering of Digital Twins (pp. 225-256). Springer. https://doi.org/10.1007/978-3-031-66719-0_11
Talasila, P., Tcherniak, D., Jensen, A. M. D., Mahato, S., Schörghofer-Queiroz, A., Ulriksen, M. D., Abbiati, G., Larsen, P. G. & Damkilde, L. (2025). Structural Health Monitoring of Engineering Structures Using Digital Twins: A Digital Twin Platform Approach. In Á. Cunha & E. Caetano (Eds.), Experimental Vibration Analysis for Civil Engineering Structures, EVACES 2025 - Volume 1 (pp. 986-996). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-96110-6_98
Tagarakis, A. C., Benos, L., Kyriakarakos, G., Pearson, S., Sørensen, C. G. & Bochtis, D. (2024). Digital Twins in Agriculture and Forestry: A Review. Sensors, 24(10), Article 3117. https://doi.org/10.3390/s24103117
Tabar, Y. R., Mikkelsen, K. B., Shenton, N., Kappel, S. L., Nikbakht, R., Toft, H. O., Henriksen, C. H., Hemmsen, M. C., Rank, M. L., Otto, M. & Kidmose, P. (2023). At-home sleep monitoring using generic ear-EEG. Frontiers in Neuroscience, 17, Article 987578. https://doi.org/10.3389/fnins.2023.987578
Swain, K. C., Zaman, Q. U., Schumann, A. W., Percival, D. C. & Bochtis, D. (2010). Computer vision system for wild blueberry fruit yield mapping. Biosystems Engineering, 106(4), 389-394. https://doi.org/10.1016/j.biosystemseng.2010.05.001
Surrow, J. H., Thomsen, S. T., Kumar, R. R., Far Brusatori, M., Montes, M. P., Hoede, C., Klein, H. N. & Volet, N. (2025). Widely tunable SG-DBR laser with ultra-narrow linewidth achieved via polarization-controlled feedback. In P. Cheben, J. Ctyroky & I. Molina-Fernandez (Eds.), Integrated Optics: Design, Devices, Systems, and Applications VIII Article 135300E SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.3055201