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.

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Ulsig, E. Z. & Tønning, P. (2022, Mar 16). Forskere: En sikker type UV-lys er et nyt våben mod corona og fremtidige epidemier. https://videnskab.dk/forskerzonen/teknologi-innovation/en-sikker-type-uv-lys-er-det-nye-vaaben-mod-corona-og-fremtidige-epidemier

Ulsig, E. Z., Stanton, E. J., Reddy, D. V., Shalm, K., Volet, N. & Mirin, R. (2023). Correlated Photon Pairs Obtained by SPDC in AlGaAs-OI Waveguides. In Quantum 2.0: Proceedings Optica Quantum 2.0 Conference and Exhibition (pp. QTh4C-2) https://doi.org/10.1364/QUANTUM.2023.QTh4C.2

Ulsig, E. Z., Degli-Eredi, I., Stanton, E. J. & Volet, N. (2022). Efficient Low Threshold Frequency Conversion in AlGaAs-On-Insulator Waveguides. Frontiers in Photonics, 3, Article 904651. https://doi.org/10.3389/fphot.2022.904651

Ulsig, E. Z. & Tønning, P. (2022). Forskere: En sikker type uv-lys er det nye våben mod corona og fremtidige epidemier. Videnskab.dk [online]. https://videnskab.dk/forskerzonen/teknologi-innovation/en-sikker-type-uv-lys-er-det-nye-vaaben-mod-corona-og-fremtidige-epidemier

Ulsig, E., Madsen, M., J. Stanton, E., Reddy, D., Leger, A., Sørensen, S., Degli-Eredi, I., Stevens, M., Hamel, D., Shalm, L., Mirin, R. & Volet, N. (2024). Widely tunable integrated GaAs and AlGaAs platforms for efficient second-order frequency conversion. https://doi.org/10.1364/opticaopen.25540030.v1

Ulsig, E. Z., Madsen, M. L., Stanton, E. J., Reddy, D. V., Leger, A. Z., Sørensen, S. R., Godoy, P. H., Degli-Eredi, I., Stevens, M. J., Hamel, D. R., Shalm, L. K., Mirin, R. P. & Volet, N. (2024). Efficient and widely tunable mid-infrared sources using GaAs and AlGaAs integrated platforms for second-order frequency conversion. Optics Express, 32(21), 36986-37000. https://doi.org/10.1364/OE.523615

Ulsig, E. Z., Linnet Madsen, M., Stanton, E. J., Venkatarama Reddy, D., Degli-Eredi, I., Mirin, R. & Volet, N. (2023). Single-photon downconversion in GaAs, AlGaAs and InGaP-on-insulator. In 2023 IEEE Photonics Conference (IPC) https://doi.org/10.1109/IPC57732.2023.10360732

Ulsig, E. Z. (2024). Second-order frequency conversion in III-V waveguides integrated on silicon. [PhD thesis, Aarhus University].

Ugurlu, H. I., Pham, X. H. & Kayacan, E. (2022). Sim-to-Real Deep Reinforcement Learning for Safe End-to-End Planning of Aerial Robots. Robotics, 11(5), Article 109. https://doi.org/10.3390/robotics11050109

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

Tunon, O. A. (2024). Vision-based navigation for underwater safety-critical applications. [PhD thesis, Aarhus University].

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2020). Performance Indicator in Multilinear Compressive Learning. In 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (pp. 1822-1828). Article 9308418 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308418

Tran, D. T., Yamac, M., Degerli, A., Gabbouj, M. & Iosifidis, A. (2021). Multilinear compressive learning. IEEE Transactions on Neural Networks and Learning Systems, 32(4), 1512-1524. Article 9070152. https://doi.org/10.1109/TNNLS.2020.2984831

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2022). Remote Multilinear Compressive Learning with Adaptive Compression. IEEE Internet of Things Journal, 9(9), 6905-6913. https://doi.org/10.1109/jiot.2021.3114743

Tran, D. T., Kanniainen, J. & Iosifidis, A. (2021). How informative is the Order Book Beyond the Best Levels? Machine Learning Perspective. Paper presented at NeurIPS 2021 Workshop on Machine Learning meets Econometrics. https://doi.org/10.2139/ssrn.3920827

Tran, D. T., Passalis, N., Tefas, A., Gabbouj, M. & Iosifidis, A. (2022). Attention-Based Neural Bag-of-Features Learning for Sequence Data. IEEE Access, 10, 45542-45552. https://doi.org/10.1109/ACCESS.2022.3169776

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

Tøttrup, D., Skovgaard, S. L., Sejersen, J. L. F. & de Figueiredo, R. P. (2022). A Real-Time Method for Time-to-Collision Estimation from Aerial Images. Journal of Imaging, 8(3), Article 62. https://doi.org/10.3390/jimaging8030062

Tøttrup, M. F., Hu, E. C., Kramer, B. A., Macedo, H. D. & Esterle, L. (2023). Using INTO-CPS Tools in the Development of a Digital Twin for the F1TENTH Race Car. In P. Masci, C. Bernardeschi, P. Graziani, M. Koddenbrock & M. Palmieri (Eds.), Software Engineering and Formal Methods. SEFM 2022 Collocated Workshops: International Conference on Software Engineering and Formal Methods (pp. 200-209). Springer. https://doi.org/10.1007/978-3-031-26236-4_18

Tola, D., Gonçalves Gomes, C. Â., Schultz, C. P. L., Schlette, C., Hansen, C. & Esterle, L. (2021). RoboCIM: Towards a Domain Model for Industrial Robot System Configurators. In A. Soylu, A. T. Nezhad, N. Nikolov, I. Toma, A. Fensel & J. Vennekens (Eds.), Proceedings of the 15th International Rule Challenge, 7th Industry Track, and 5th Doctoral Consortium @ RuleML+RR 2021 co-located with 17th Reasoning Web Summer School (RW 2021) and 13th DecisionCAMP 2021 as part of Declarative AI 2021 CEUR-WS.org. http://ceur-ws.org/Vol-2956/paper12.pdf

Tola, D. & Larsen, P. G. (2021). A Co-Simulation Based Approach for Developing Safety-Critical Systems. In Proceedings of the 18th International Overture Workshop https://arxiv.org/pdf/2101.07261.pdf#page=65

Tola, D., Madsen, E., Gomes, C., Esterle, L., Schlette, C., Hansen, C. & Larsen, P. G. (2022). Towards Easy Robot System Integration: Challenges and Future Directions. In 2022 IEEE/SICE International Symposium on System Integration (SII) (pp. 77-82). IEEE. https://doi.org/10.1109/SII52469.2022.9708846

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 Dataset and Analysis.

Tola, D. & Corke, P. (2023). Understanding URDF: A Survey Based on User Experience.

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., Gomes, C., Schultz, C., Schlette, C., Hansen, C. & Esterle, L. (2021). RoboCIM: Towards a domain model for industrial robot system configurators. CEUR Workshop Proceedings, 2956.

Tola, D. (2024). Enabling Digitalization in Modular Robotic Systems Integration. [PhD thesis, Aarhus University]. Aarhus University.

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

Thylstrup, B., Schrøder, S., Fabricius, V. A. V., Brummer, J. E., Kirk, H. B. & del Palacio González , A. (2025). AfterCare – udvikling og pilottest af mobilapplikation til forebyggelse af tilbagefald af alkohol- og cannabisbrug blandt unge voksne.

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 (pp. 1-12). 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, S. T., Brusatori, M. F., Arent, N. H., Kumar, R. R. & Volet, N. (2023). Frequency noise measurements using coherent self-heterodyne detection. Optics Letters, 48(24), 6372-6375. https://doi.org/10.1364/OL.505960

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 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

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., Lucani Rötter, D. E. & Zhang, Q. (2023). Zip to Zip-it: Compression to Achieve Local Differential Privacy. In GLOBECOM 2023 - 2023 IEEE Global Communications Conference (pp. 2196-2201). IEEE. https://doi.org/10.1109/GLOBECOM54140.2023.10437448

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

Taurone, F., Lucani, D. E. & Zhang, Q. (2025). Zeal -Differential Privacy Mechanism for IoT Enhancing Compression Efficiency. IEEE Internet of Things Journal, 12(14), 27160-27172. https://doi.org/10.1109/JIOT.2025.3565175

Taurone, F. (2025). Interplays between Compression, Privacy and Analytics for the Internet of Things. [PhD thesis, Aarhus University].

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

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

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