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

Sort by: Date | Author | Title

Maalandish, M., Hosseini, S. H., Sabahi, M., Rostami, N. & Khooban, M. H. (2024). Soft-switching multiport DC-DC converter for PV/EV applications with a bidirectional port. IET Renewable Power Generation, 18(12), 1862-1879. https://doi.org/10.1049/rpg2.13055

Ma, C., Rutz, D., Hofmeier, V., Janssen, R., Balafoutis, A., Vaiopoulos, K., Vandorou, F., Sørensen, C. A. G., Manolakos, D., Koutsouris, A., Paris, B., Papadakis, G., Borzecka, M., Wydra, M., Biševac, V., Creupelandt, D., Román, J., Rossi, D., Próchniak, M. ... Asín, M. (2022). Support for Decarbonizing the European Agriculture - The Agrofossilfree Project. In European Biomass Conference and Exhibition Proceedings (EUBCE 2022) (pp. 402-405). ETA-Florence Renewable Energies. http://www.etaflorence.it/proceedings/

Ma, C., Rutz, D., Balafoutis, A., Vaiopoulos, K., Vandorou, F., Kyriakarakos, G., Grøn Sørensen, C., Nørremark, M., Kristensen, E. F., Manolakos, D., Koutsouris, A., Kanaki, V., Paris, B., Papadakis, G., Borzecka, M., Wydra, M., Biševac, V., Vansintjan, D., Román, J. ... Hansen, A. G. (2023). SUPPORTING BIOMASS USAGE AND PRODUCTION TO DECARBONIZE AGRICULTURE INDUSTRY: THE AGROFOSSILFREE PROJECT. In 31st European Biomass Conference and Exhibition: Proceedings (pp. 373 - 378)

Ma, F., Cheng, H. V., Li, C. & Liu, L. (2026). TIMA: Text-Image Mutual Awareness for Balancing Zero-Shot Adversarial Robustness and Generalization Ability. In S. Koenig, C. Jenkins & M. E. Taylor (Eds.), Proceedings of the AAAI Conference on Artificial Intelligence (29 ed., pp. 24235-24243). Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v40i29.39603

Lyng, R., Bennedsen, J., Bettaieb, L., Bodsberg, N. R., Edström, K., Guðjónsdóttir, M. S., Roslöf, J., Solbjørg, O. K. & Øien, G. (2023). Editorial. In Proceedings of the 19th International CDIO Conference (pp. iv-v). NTNU Norwegian University of Science and Technology.

Lund, J., Jensen, L. B., Macedo, H. D. & Larsen, P. G. (2022). Towards UML and VDM Support in the VS Code Environment. In H. D. Macedo & K. Pierce (Eds.), Proceedings of the 20th International Overture Workshop (pp. 50-65) https://doi.org/10.48550/arXiv.2208.10233

Lund, J., Jensen, L. B., Battle, N., Larsen, P. G. & Macedo, H. D. (2023). Bidirectional UML Visualisation of VDM Models.

Lumer-Klabbers, G., Hausted, J. O., Kvistgaard, J. L., Macedo, H. D., Frasheri, M. & Larsen, P. G. (2021). Towards a digital twin framework for autonomous robots. In W. K. Chan, B. Claycomb, H. Takakura, J.-J. Yang, Y. Teranishi, D. Towey, S. Segura, H. Shahriar, S. Reisman & S. I. Ahamed (Eds.), 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC) (pp. 1254-1259). IEEE. https://doi.org/10.1109/COMPSAC51774.2021.00174

Lotlikar, V. S., Satpute, N. & Gupta, A. (2022). Brain Tumor Detection Using Machine Learning and Deep Learning: A Review. Current Medical Imaging, 18(6), 604-622. https://doi.org/10.2174/1573405617666210923144739

Lotfi, A., Maalandish, M., Aghaei, A., Samadian, A., Fathollahi, A., Hosseini, S. H. & Khooban, M. H. (2024). Novel multilevel inverter topology with low switch count. International Journal of Emerging Electric Power Systems, 25(3), 305-319. https://doi.org/10.1515/ijeeps-2022-0309

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

Lord, W., Teagle, S., Alton, J., Bannister, G., Beuchert, J., Bjerge, K., Carbone, D., Segura, A. G., Howson, T., Høye, T. T., Lawson, J., Ravivarma, A., Roy, D. B., Rylett, D., Skinner, G., Warwick, A. & August, T. (2026). Automated monitoring of insects system: building a non-lethal and scalable solution for monitoring of nocturnal insects. HardwareX, 27, Article e00822. https://doi.org/10.1016/j.ohx.2026.e00822

Loft, J. C., Gardner, A. B., Gravesen, K. B., Tønning, P., Stanton, E. J., Volet, N. & Ulsig, E. Z. (2026). Visible light propagation loss of LPCVD Si₃N₄ thin films and waveguides: impact of high-temperature annealing. Optics Letters, 51(8), 2332-2335. https://doi.org/10.1364/OL.596082

Liu, Z., Liang, J., Zhang, S. & Kayacan, E. (2022). ANN-Based vibration control of an aerial refueling hose system with input nonlinearity and prescribed output constraint. Journal of the Franklin Institute, 359(6), 2627-2645. https://doi.org/10.1016/j.jfranklin.2022.01.006

Liu, L., Grombacher, D., Griffiths, M., Vang, M. & Larsen, J. J. (2023). Signal Processing Steady-State Surface NMR Data. IEEE Transactions on Instrumentation and Measurement, 72, Article 6502313. https://doi.org/10.1109/TIM.2023.3264033

Liu, B., Wang, Y., Mofid, O., Mobayen, S. & Khooban, M. H. (2024). Barrier Function-Based Backstepping Fractional-Order Sliding Mode Control for Quad-Rotor Unmanned Aerial Vehicle under External Disturbances. IEEE Transactions on Aerospace and Electronic Systems, 60(1), 716-728. https://doi.org/10.1109/TAES.2023.3328801

Liu, H., Yang, Y., Wu, Q., He, B., Liao, Y. & Zhou, P. (2024). FacGNN: Multi-faceted Fairness Enhancement for GNN through Adversarial and Contrastive Learning. In 2024 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN60899.2024.10649939

Liu, L., Domenzain Gonzalez, D., Vela, I., Maurya, P. K., Kühl, A. K., Bording, T., Ejlskov, P., Auken, E., Larsen, J. J. & Christiansen, A. V. (2025). An efficient cross-borehole direct current resistivity monitoring instrument. Geophysics, 90(2), D61-D70. https://doi.org/10.1190/geo2023-0518.1

Liu, J. (2020). Mobile Edge Computing in 5G. [PhD dissertation, Aarhus University].

Liu, S., Lang, X., Wu, J. & Rehman, N. U. (2025). Selective Noise Empirical Mode Decomposition. IEEE Signal Processing Letters, 32, 2823-2827. https://doi.org/10.1109/LSP.2025.3588082

Liu, Q., Zheng, Y., Wu, H., Michalek, L., Ronchini, M., Mow, R. K., Wang, W., Park, H., Ji, X., Yu, Z., Yao, Z. F., Nishio, Y., Zhao, C., Pei, J. & Bao, Z. (2026). Intrinsically stretchable complementary circuits based on direct photo-patternable polymer semiconductors. Nature Electronics, 9(5), 507-518. https://doi.org/10.1038/s41928-026-01599-z

Lindahl Petersen , K., Ladegaard Jensen, K., Back Nielsen, M., Pas, L.-C., Jensen, N.-P., Nielsen, P. R., Bøjer, O. M., Nyholm Jørgensen, R., Laursen, M. S., Teimouri, N. & Hartmann, B. (2021). Analyse af mulige herbicidbesparelser ved brug af erfaringer og data fra RoboWeedMaPS. Datalogisk Institut. https://datalogisk.dk/wp-content/uploads/2021/03/MST_20rapport_version_2_2002092021.pdf

Lin, P.-C., Abbaszadeh, E., Mobayen, S., Rouhani, S. H., Su, C.-L., Haddad-Zarif, M. & Khooban, M. H. (2024). Soft variable structure fractional sliding-mode control for frequency regulation in renewable shipboard microgrids. Ocean Engineering, 296, Article 117065. https://doi.org/10.1016/j.oceaneng.2024.117065

Lillelund, C. M., Pedersen, C. F., Harbo, M. & Fibiger Smed, C. (2021). Vejen til genoptræning går gennem data. Medicoteknik, 8(3), 18-19. https://ipaper.ipapercms.dk/TechMedia/Medicoteknik/2021/3/?page=18

Lillelund, C. M., Jensen, H. B. & Pedersen, C. F. (2022). Cloud K-SVD for Image Denoising. SN Computer Science, 3(2), Article 151. https://doi.org/10.1007/s42979-022-01042-y

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

Lillelund, C. M., Magris, M. & Pedersen, C. F. (2023). Uncertainty Estimation in Deep Bayesian Survival Models. In BHI 2023 - IEEE-EMBS International Conference on Biomedical and Health Informatics, Proceedings IEEE. https://doi.org/10.1109/BHI58575.2023.10313466

Lillelund, C. M., Magris, M. & Pedersen, C. F. (2025). Efficient Training of Probabilistic Neural Networks for Survival Analysis. IEEE Journal of Biomedical and Health Informatics, 29(9), 6157-6166. https://doi.org/10.1109/JBHI.2024.3417369

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

Lillelund, C. M., Kalra, S. & Greiner, R. (2025). A meaningful prediction of functional decline in amyotrophic lateral sclerosis based on multi-event survival analysis. PLoS One, 20(11 ), Article e0336476. https://doi.org/10.1371/journal.pone.0336476

Liang, W., Amer, A., Mehndiratta, M., Chen, Z., Yao, B. & Kayacan, E. (2025). Adaptive Robust Control Integrated With Gaussian Processes for Quadrotors: Enhanced Accuracy, Fault Tolerance and Anti-Disturbance. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 55(5), 3235-3248. https://doi.org/10.1109/TSMC.2025.3539707

Liang, P., Yang, M., Wu, Z., Zhou, P. Y. & Liao, Y. (2026). DiSCo: Disrupting Semantic Consistency for Transferable Cross-Modal Adversarial Attacks. In J. Lokoc, L. Peška, J. Zahálka, S. Rudinac, U. Sharma, M. Kastner, J. Chen, M.-C. Hu & J. Wu (Eds.), MultiMedia Modeling - 32nd International Conference on Multimedia Modeling, MMM 2026, Proceedings (pp. 16-30). Springer Science+Business Media. https://doi.org/10.1007/978-981-95-6957-1_2

Li, B., Schultz, C. P. L., Melzner, J., Golovina, O. & Teizer, J. (2020). Safe and Lean Location-based Construction Scheduling. In H. Osumi, H. Furuya & K. Tateyama (Eds.), Proceedings of the 37th International Symposium on Automation and Robotics in Construction (ISARC 2020): From Demonstration to Practical Use - To New Stage of Construction Robot - (pp. 1409-1416). International Association for Automation and Robotics in Construction (IAARC). https://doi.org/10.22260/ISARC2020/0195

Li, B., Schultz, C. P. L., Dimyadi, J. & Amor, R. (2021). Defeasible reasoning for automated building code compliance checking. In V. Semenov & R. J. Scherer (Eds.), ECPPM 2021 – eWork and eBusiness in Architecture, Engineering and Construction: Proceedings of the 13th European Conference on Product & Process Modelling (ECPPM 2021), 15-17 September 2021, Moscow, Russia (pp. 229-236). CRC Press. https://doi.org/10.1201/9781003191476

Li, B., Schultz, C., Teizer, J., Golovina, O. & Melzner, J. (2022). Towards a unifying domain model of construction safety, health and well-being: SafeConDM. Advanced Engineering Informatics, 51, Article 101487. https://doi.org/10.1016/j.aei.2021.101487

Li, B., Fitzgerald, J. & Schultz, C. (2022). Modelling the impacts of crowds on occupants in the built environment—A static, rule-based approach to human perception and movement. Advanced Engineering Informatics, 51, Article 101452. https://doi.org/10.1016/j.aei.2021.101452

Li, N., Iosifidis, A. & Zhang, Q. (2022). Collaborative edge computing for distributed CNN inference acceleration using receptive field-based segmentation. Computer Networks, 214, Article 109150. https://doi.org/10.1016/j.comnet.2022.109150

Li, N., Iosifidis, A. & Zhang, Q. (2022). Receptive Field-based Segmentation for Distributed CNN Inference Acceleration in Collaborative Edge Computing. In ICC 2022 - IEEE International Conference on Communications (pp. 4281-4286). IEEE. https://doi.org/10.1109/ICC45855.2022.9838547

Li, N., Iosifidis, A. & Zhang, Q. (2022). Distributed Deep Learning Inference Acceleration using Seamless Collaboration in Edge Computing. In ICC 2022 - IEEE International Conference on Communications (pp. 3667-3672). IEEE. https://doi.org/10.1109/ICC45855.2022.9839083

Li, N., Iosifidis, A. & Zhang, Q. (2022). Graph Reinforcement Learning-based CNN Inference Offloading in Dynamic Edge Computing. In 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings (pp. 982-987). IEEE. https://doi.org/10.1109/GLOBECOM48099.2022.10001067

Li, R., Shreya, S., Ricci, S., Bridarolli, D., Ielmini, D., Farkhani, H. & Moradi, F. (2023). Thermal-Induced Multi-State Memristors for Neuromorphic Engineering. In IEEE International Symposium on Circuits and Systems (ISCAS): Proceedings IEEE. https://doi.org/10.1109/ISCAS46773.2023.10182122

Li, H., Zhang, Q. & Kuldeep, G. (2023). Demo: 3TierView: A Three-tier Privacy-preserving Live Video Surveillance IoT System. In MobiSys 2023 - Proceedings of the 21st ACM International Conference on Mobile Systems, Applications and Services: Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services (pp. 594–595). Association for Computing Machinery. https://doi.org/10.1145/3581791.3597289

Li, N., Iosifidis, A. & Zhang, Q. (2023). Attention-Based Feature Compression for CNN Inference Offloading in Edge Computing. In M. Zorzi, M. Tao & W. Saad (Eds.), ICC 2023 - IEEE International Conference on Communications (pp. 967-972). IEEE. https://doi.org/10.1109/ICC45041.2023.10279110

Li, N., Bennis, M., Iosifidis, A. & Zhang, Q. (2023). Spatiotemporal Attention-based Semantic Compression for Real-time Video Recognition. In IEEE Globecom 2023 (pp. 1603-1608). IEEE. https://doi.org/10.1109/GCWkshps58843.2023.10465187

Li, C., Kies, A., Zhou, K., Schlott, M., Sayed, O. E., Bilousova, M. & Stöcker, H. (2024). Optimal Power Flow in a highly renewable power system based on attention neural networks. Applied Energy, 359, Article 122779. https://doi.org/10.1016/j.apenergy.2024.122779

Li, B. & Schultz, C. P. L. (2025). Clingo2DSR - A clingo-based software system for declarative spatial reasoning. Spatial Cognition & Computation, 25(1), 69-119. https://doi.org/10.1080/13875868.2024.2324875

Li, R., Rezaeiyan, Y., Böhnert, T., Schulman, A., Ferreira, R., Farkhani, H. & Moradi, F. (2024). Temperature effect on a weighted vortex spin-torque nano-oscillator for neuromorphic computing. Scientific Reports, 14(1), Article 10043. https://doi.org/10.1038/s41598-024-60929-3

Li, H., Ma, L., Shi, H., Hao, Y., Liao, Y., Cheng, L. & Zhou, P. Y. (2025). 3D-GOI: 3D GAN Omni-Inversion for Multifaceted and Multi-object Editing. In A. Leonardis, E. Ricci, S. Roth, O. Russakovsky, T. Sattler & G. Varol (Eds.), Computer Vision – ECCV 2024 - 18th European Conference, Proceedings (pp. 390-406). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-73033-7_22

Li, H., Shi, H., Zhang, W., Wu, W., Liao, Y., Wang, L., Lee, L. H. & Zhou, P. Y. (2025). DreamScene: 3D Gaussian-Based Text-to-3D Scene Generation via Formation Pattern Sampling. In A. Leonardis, E. Ricci, S. Roth, O. Russakovsky, T. Sattler & G. Varol (Eds.), Computer Vision – ECCV 2024 - 18th European Conference, Proceedings (pp. 214-230). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-72904-1_13

Li, N., Iosifidis, A. & Zhang, Q. (2025). Dynamic Semantic Compression for CNN Inference in Multi-Access Edge Computing: A Graph Reinforcement Learning-Based Autoencoder. IEEE Transactions on Wireless Communications, 24(3), 2157-2172. https://doi.org/10.1109/TWC.2024.3518399

Displaying results 651 to 700 out of 1554

Revised 16.10.2026

AU Engineering