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Department of Electrical and Computer Engineering

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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Vestergaard, R., Techel, J., Zhang, Q. & Lucani Rötter, D. E. (2022). Lightweight Compression for Severely Constrained IoT Devices. In European Wireless 2022; 27th European Wireless Conference (pp. 1-6). IEEE.

Vestergaard, R. (2021). Towards Scalable Randomly Accessible Data Compression. [PhD dissertation, Aarhus University]. Aarhus Universitet.

Verma, R. S., Raj, R. K., Soni, S., Shreya, S. & Pramanik, T. (2026). Nonlinear Skyrmion Motion Controlled by Voltage-Induced Magnetic Exchange Gradients. In 2026 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2026 - Proceedings IEEE. https://doi.org/10.1109/INTERMAGShortPapers68882.2026.11642624

Verholt, A. B., Foss, C. H., Hinrichsen, L. M., Madsen, L. H., Odderskov, C. S. N., Andersen, L. H. & Lietzen, L. W. (2026). Advancing a patient-centered and holistic approach for older patients with frailty in a vascular surgical department: a quality improvement initiative. European Geriatric Medicine, 17(2), 837-849. https://doi.org/10.1007/s41999-025-01355-0

Vathoopan Kannan, M., Boudjadar, J., Ramanujan, D., Borbolla Muñoz, A. & Aher, G. R. (2025). Dynamic Data–Model Integration to Infer Valid Manufacturing Service Simulation Sequences for Circular Product Design. Manuscript submitted for publication.

Vathoopan Kannan, M., Talasila, P., Boudjadar, J., Larsen, C., Bicocchi, N., Picone, M. & Melloni, M. (2026). Orchestrating Distributed Simulations for Circular Manufacturing-as-a-Service Ecosystems. In IEEE International Conference on Industrial Technology (ICIT) IEEE. https://doi.org/10.1109/ICIT64854.2026.11491518

Vathoopan, M., Boudjadar, J., Hertwig, M. M. & Lentes, J. (2025). Ontology-Driven Simulations for Quantified Service Discovery in Manufacturing Ecosystems. In D. Maga (Ed.), 2025 29th International Symposium on Distributed Simulation and Real Time Applications (DS-RT) IEEE. https://doi.org/10.1109/DS-RT68115.2025.11186005

Vathoopan, M., Boudjadar, J. & Ramanujan, D. (2026). Ontologies for Architecting Circular and Sustainable Manufacturing-as-a-Service Systems. In L. C. Tang (Ed.), Proceedings of the 12th International Conference on Industrial Engineering and Applications (pp. 453-465). Springer Science+Business Media. https://doi.org/10.1007/978-981-95-4717-3_41

Vassis, S., Todnem, L., Straadt, D., Pedersen, C. F., Noeldeke, B., Resnick, C. M., Glerup, M., Pedersen, T. K., Pauwels, R. & Stoustrup, P. (2025). Improving early detection of temporomandibular joint involvement in juvenile idiopathic arthritis with a clinically interpretable machine learning model. Scientific Reports, 15(1), Article 39120. https://doi.org/10.1038/s41598-025-25988-0

Vanommeslaeghe, Y., Gomes, C., Van Acker, B., Denil, J. & De Meulenaere, P. (2025). Adapting parallel DEVS semantics to FMI 3.0 co-simulation using synchronous clocks. Simulation. Advance online publication. https://doi.org/10.1177/00375497251393255

Vang, M., Grombacher, D., Griffiths, M. P., Liu, L. & Larsen, J. J. (2023). Technical note: High-density mapping of regional groundwater tables with steady-state surface nuclear magnetic resonance - three Danish case studies. Hydrology and Earth System Sciences, 27(16), 3115-3124. https://doi.org/10.5194/hess-27-3115-2023

Vang, M., Grombacher, D., Larsen, J. J. & Wilson, S. (2023). Small coil surface nuclear magnetic resonance in dynamic river systems in New Zealand. In 2nd Conference on Hydrogeophysics 2023, Held at Near Surface Geoscience Conference and Exhibition 2023, NSG 2023 European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202320070

Vang, M., Grombacher, D., Larsen, J. J. & Wilson, S. (2023). SMALL COIL SURFACE NUCLEAR MAGNETIC RESONANCE FOR SHALLOW RESOLUTION OF RIVERS IN NEW ZEALAND. Proceedings of the Symposium on the Application of Geophyics to Engineering and Environmental Problems, SAGEEP, 2023-April.

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Extrapolating sparse SNMR data sets onto dense TEM coverage using spatially variable correlations. Abstract from AGU Fall meeting 2024, Washington DC, United States.

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Clustering on SNMR and TEM parameters over a saline-freshwater interface to resolve hydrogeological layers. In NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420102

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Wilson, S. (2025). Efficient mapping of complex groundwater systems associated with braided rivers using small coil surface nuclear magnetic resonance. Geophysics, 90(3), 1-12. https://doi.org/10.1190/geo2023-0765.1

Vang, M., Larsen, J. J., Christiansen, A. V. & Grombacher, D. (2025). Alleviating interpretational ambiguity in hydrogeology through clustering-based analysis of transient electromagnetic and surface nuclear magnetic resonance data. Hydrology and Earth System Sciences, 29(20), 5315-5329. https://doi.org/10.5194/hess-29-5315-2025

van der Meer, L., Esterle, L., Cools, M. & Loidl, M. (2026). Cities aren't rocket engines: the maturity of digital twins in human-centred urban planning. International Journal of Digital Earth, 19(1), Article 2630452. https://doi.org/10.1080/17538947.2026.2630452

Vahedifar, M. A., Akhtarshenas, A., Rafatpanah, M. M. & Sabbaghian, M. (2025). Shapley-Based Data Valuation with Mutual Information: A Key to Modified K-Nearest Neighbors. In 2025 IEEE 35th International Workshop on Machine Learning for Signal Processing (MLSP) https://doi.org/10.1109/MLSP62443.2025.11204262

Vahedifar, M. A. & Zhang, Q. (2025). Signal Prediction for Loss Mitigation in Tactile Internet: A Leader-Follower Game-Theoretic Approach. In 35th IEEE International Workshop on Machine Learning for Signal Processing: Signal Processing in the Age of Lorge Language Models, MLSP 2025 IEEE Computer Society Press. https://doi.org/10.1109/MLSP62443.2025.11204284

Vahedifar, M. A. & Zhang, Q. (2026). Discrete Mode Decomposition Meets Shapley Value: Robust Signal Prediction in Tactile Internet. In INFOCOM 2026 - IEEE Conference on Computer Communications IEEE. https://doi.org/10.1109/INFOCOM59046.2026.11571681

Vahdanjoo, M. & Grøn Sørensen, C. (2021). Novel Route Planning Method to Improve the Operational Efficiency of Capacitated Operations. Case: Application of Organic Fertilizer. AgriEngineering, 3(3), 458-477. https://doi.org/10.3390/agriengineering3030031

Vahdanjoo, M., Nørremark, M. & Grøn Sørensen, C. (2021). A System for Optimizing the Process of Straw Bale Retrieval. Sustainability, 13(14), Article 7722. https://doi.org/10.3390/su13147722

Vahdanjoo, M., Gislum, R. & Grøn Sørensen, C. (2023). Operational, Economic, and Environmental Assessment of an Agricultural Robot in Seeding and Weeding Operations. AgriEngineering, 5(1), 299–324. Article 5. https://doi.org/10.3390/agriengineering5010020

Vahdanjoo, M., Gislum, R. & Grøn Sørensen, C. (2024). Estimating Fuel Consumption of an Agricultural Robot by Applying Machine Learning Techniques during Seeding Operation. AgriEngineering, 6(1), 754-772. https://doi.org/10.3390/agriengineering6010043

Vahdanjoo, M., Gislum, R. & Grøn Sørensen, C. (2024). Three-dimensional area coverage planning model for robotic application. Computers and Electronics in Agriculture, 219, 1-15. Article 108789. https://doi.org/10.1016/j.compag.2024.108789

Vahdanjoo, M., Grøn Sørensen, C. & Nørremark, M. (2025). Digital transformation of the agri-food system. Current Opinion in Food Science, 63, Article 101287. https://doi.org/10.1016/j.cofs.2025.101287

Ulsig, E. Z. & Volet, N. (2021). Second-order nonlinear effects in InGaAsP waveguides for efficient wavelength conversion to the mid-infrared. In P. G. Schunemann & K. L. Schepler (Eds.), Nonlinear Frequency Generation and Conversion: Materials and Devices XX Article 116700U SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2581819

Ulsig, E. Z. & Volet, N. (2021). Design study of efficient far-UVC second-harmonic generation using an integrated approach. In M. Bertolotti, A. V. Zayats & A. M. Zheltikov (Eds.), Nonlinear Optics and Applications XII (Vol. 11770). Article 117700P SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2592408

Ulsig, E. Z., Degli Eredi, I. & Volet, N. (2022). Efficient frequency conversion of low-intensity light in AlGaAs-on-insulator waveguides. In P. G. Schunemann & V. Petrov (Eds.), Nonlinear Frequency Generation and Conversion: Materials and Devices XXI Article 119850D SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2607179

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 dissertation, 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 dissertation, Aarhus University].

Troldborg, K. B., Skov, S. I., Fathollahi, A. & Pedersen, J. H. (2026). Advanced Machine Learning Approach for Fast Temperature Estimation in SiC-Based Power Electronics Converters †. Electronics, 15(6), Article 1325. https://doi.org/10.3390/electronics15061325

Troldborg, K. B., Skov, S. I., Fathollahi, A. & Pedersen, J. H. (2026). Intelligent Machine Learning-Based Scheme for Fast Temperature Estimation of SiC Power Modules in Electric Vehicle Power Converters. In 2026 IEEE Intelligent Vehicles Symposium, IV 2026 (pp. 1034-1039). IEEE. https://doi.org/10.1109/IV66570.2026.11623879

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

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