Publications

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Evans, V. T., Gomes, C. & Lucani Rötter, D. E. (2025). Precision on Demand: Propositional Logic for Event-Trigger Threshold Regulation. IEEE Internet of Things Journal, 12(3), 2674-2689. https://doi.org/10.1109/JIOT.2024.3476922

Fan, W., Haiyang, Y., Zhongda, Z., Xiaobo, Z., Yuzhang, Z. & Haiyan, W. (2025). ESTMST-ST: An End-to-End Soft Threshold and Multiloss Self-Distillation Based Swin Transformer for Underwater Acoustic Signal Recognition. IEEE Transactions on Geoscience and Remote Sensing, 63, Article 4200813. https://doi.org/10.1109/TGRS.2024.3520860

Haiyang, Y., Ruige, G., Zhongda, Z., Yuzhang, Z., Xiaobo, Z., Tao, L. & Haiyan, W. (2025). U-TransCNN: A U-shape transformer-CNN fusion model for underwater image enhancement. Displays, 88, Article 103047. https://doi.org/10.1016/j.displa.2025.103047

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

Taurone, F., Lucani Rötter, D. E. & Zhang, Q. (Accepted/In press). Zeal - Differential Privacy Mechanism for IoT Enhancing Compression Efficiency. IEEE Internet of Things Journal.

Antonsen, M. M., Chinello, F. & Zhang, Q. (2024). Design Octree-Based Method to Improve Model-Mediated Teleoperation in Tactile Internet. In 2024 IEEE International Conference on Robotics and Automation, ICRA 2024 (pp. 15707-15713). IEEE. https://doi.org/10.1109/ICRA57147.2024.10610295

Antonsen, M. M., Liu, S., Xu, X., Steinbach, E., Chinello, F. & Zhang, Q. (2024). Digital Twin-empowered Model-Mediated Teleoperation using Multimodality Data with Signed Distance Fields. In 2024 IEEE Haptics Symposium, HAPTICS 2024 (pp. 353-359). IEEE. https://doi.org/10.1109/HAPTICS59260.2024.10520841

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2024). ACCURATE GIGAPIXEL CROWD COUNTING BY ITERATIVE ZOOMING AND REFINEMENT. In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 6510-6514). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP48485.2024.10446065

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2024). Efficient High-Resolution Deep Learning: A Survey. ACM Computing Surveys, 56(7), 1 - 35. Article 181. https://doi.org/10.1145/3645107

Gomes, C., Lucani Rötter, D. E., Iosifidis, A., Feng, H., Ejersbo, H. & Frasheri, M. (2024). Sensing and Communication of Data from the Physical Twin. In J. Fitzgerald, C. Gomes & P. G. Larsen (Eds.), The Engineering of Digital Twins (pp. 147-171). Springer. https://doi.org/10.1007/978-3-031-66719-0_7#citeas

Hudson, N., Khamfroush, H., Baughman, M., Lucani Rötter, D. E., Chard, K. & Foster, I. (2024). QoS-aware edge AI placement and scheduling with multiple implementations in FaaS-based edge computing. Future Generation Computer Systems, 157, 250-263. https://doi.org/10.1016/j.future.2024.03.035

Hurst, A., Lucani Rötter, D. E. & Zhang, Q. (2024). GreedyGD: Enhanced Generalized Deduplication for Direct Analytics in IoT. IEEE Transactions on Industrial Informatics, 20(4), 6954-6962. https://doi.org/10.1109/TII.2024.3353913

Hurst, A., Lucani Rötter, D. E. & Zhang, Q. (2024). PairwiseHist: Fast, Accurate, and Space-Efficient Approximate Query Processing with Data Compression. Proceedings of the VLDB Endowment, 17(6), 1432-1445. https://doi.org/10.14778/3648160.3648181

Kretsis, A., Kokkinos, P., Varvarigos, E., Syrivelis, D., Bakopoulos, P., Sipos, M., Fehér, M., Lucani Rötter, D. E., Bernabe, J. M., Skarmeta, A., Paez, I., Cominardi, L., Mercier, M., Velho, P., Georgiou, Y., Mainas, C., Nanos, A., Martin, J., Fernandez Gomez, A. ... Chintamani, K. (2024). EMPYREAN: Trustworthy, Cognitive and AI-driven Collaborative Associations of IoT Devices and Edge Resources for Data Processing. In HPDC 2024 - Proceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing (pp. 385 - 388). Association for Computing Machinery. https://doi.org/10.1145/3625549.3658814

Larsen, P. G., Fitzgerald, J., Gomes, C., Woodcock, J., Basagiannis, S., Ulisse, A., Esterle, L., Lucani Rötter, D. E., Hansen, S. T. & Oakes, B. J. (2024). Future Directions and Challenges. In J. Fitzgerald, C. Gomes & P. G. Larsen (Eds.), The Engineering of Digital Twins (pp. 363-386). Springer. https://doi.org/10.1007/978-3-031-66719-0_15

Rask, C. D. & Lucani Rötter, D. E. (2024). RAGE for the Machine: Image Compression with Low-Cost Random Access for Embedded Applications. In 2024 IEEE International Conference on Image Processing, ICIP 2024: Proceedings (pp. 1987-1993). IEEE. https://doi.org/10.1109/ICIP51287.2024.10647293

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., 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., Dorsch, J., Zhang, Q. & Lucani Rötter, D. E. (Accepted/In press). TRIC: Triage Compressed Data at the Edge for Efficient Data Transmission in Anomaly Detection. In IEEE Globecom Workshops IEEE.

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2023). Crowd Counting on Heavily Compressed Images with Curriculum Pre-Training. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 559-564). IEEE. https://doi.org/10.1109/SSCI52147.2023.10371805

Bakhtiarnia, A., Milošević, N., Zhang, Q., Bajović, D. & Iosifidis, A. (2023). Dynamic Split Computing for Efficient Deep Edge Intelligence. In ICASSP 2023: 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) IEEE. https://doi.org/10.1109/ICASSP49357.2023.10096914

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2023). PromptMix: Text-to-image diffusion models enhance the performance of lightweight networks. In 2023 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN54540.2023.10191962

Cavagna, A., Li, N., Iosifidis, A. & Zhang, Q. (2023). Semantic Communication Enabling Robust Edge Intelligence for Time-Critical IoT Applications. In 2023 IEEE International Conference on Communications Workshops (ICC Workshops) (pp. 1617-1622). IEEE. https://doi.org/10.1109/ICCWorkshops57953.2023.10283786

Ghassabi, K., Pahlevani, P. & Lucani Rötter, D. E. (2023). Deduplication of Textual Data by NLP Approaches. In 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring) IEEE. https://doi.org/10.1109/VTC2023-Spring57618.2023.10199538

Hurst, A., Lucani Rötter, D. E., Assent, I. & Zhang, Q. (2023). GLEAN: Generalized Deduplication Enabled Approximate Edge Analytics. IEEE Internet of Things Journal, 10(5), 4006-4020. https://doi.org/10.1109/JIOT.2022.3166455

Kontodimas, K., Soumplis, P., Kretsis, A., Kokkinos, P., Fehér, M., Lucani Rötter, D. E. & Varvarigos, M. (2023). Secure Distributed Storage Orchestration on Heterogeneous Cloud-Edge Infrastructures. IEEE Transactions on Cloud Computing , 11(4), 3407-3425. https://doi.org/10.1109/TCC.2023.3287653

Kuldeep, G. & Zhang, Q. (2023). Lightweight electrocardiogram signal compression. Biomedical Signal Processing and Control, 85, Article 105012. https://doi.org/10.1016/j.bspc.2023.105012

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, H., Zhang, Q. & Kuldeep, G. (2023). Demo: 3TierView: A Three-tier Privacy-preserving Live Video Surveillance IoT System. In MobiSys '23: 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., Bennis, M., Iosifidis, A. & Zhang, Q. (Accepted/In press). Spatiotemporal Attention-based Semantic Compression for Real-time Video Recognition. In IEEE Globecom 2023 IEEE. https://arxiv.org/pdf/2305.12796.pdf

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 ICC 2023 - IEEE International Conference on Communications (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 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

Wang, X., Mukherjee, M., Kumar, V., Mavromoustakis, C. X., Shoufan, A., Guo, M. & Zhang, Q. (2023). Rendering Delay Minimization in RIS-assisted Edge Computing for IIoT with VR Streaming. In 2023 IEEE Globecom Workshops (GC Wkshps) (pp. 1319-1324). IEEE. https://doi.org/10.1109/GCWkshps58843.2023.10465022

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2022). Single-layer vision transformers for more accurate early exits with less overhead. Neural Networks, 153, 461-473. https://doi.org/10.1016/j.neunet.2022.06.038

Dong, Z., Li, N., Iosifidis, A. & Zhang, Q. (2022). Design and Prototyping Distributed CNN Inference Acceleration in Edge Computing. ArXiv. https://doi.org/10.48550/arXiv.2211.13778

Fehér, M., Lucani Rötter, D. E. & Chatzigeorgiou, I. (2022). An Adaptive Column Compression Family for Self-Driving Databases. Paper presented at Thirteenth International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures, Sydney, New South Wales, Australia. https://arxiv.org/abs/2209.02334

Fehér, M., Lucani Rötter, D. E., Hansen, M. T. & Vester, F. E. (2022). Stream Compression of DLMS Smart Meter Readings. In ICC 2022 - IEEE International Conference on Communications (pp. 5517-5522). IEEE. https://doi.org/10.1109/ICC45855.2022.9838758

Gu, X., Wang, X., Feng, Y., Long, Y., Mukherjee, M., Pan, Z., Guo, M. & Zhang, Q. (2022). Demo: TINGLE: Pushing Edge Intelligence in Synchronization and Useful Data Transfer for Human-Robotic Arm Interactions. In INFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops IEEE. https://doi.org/10.1109/INFOCOMWKSHPS54753.2022.9798353

Hosseinzadeh, M., Wachal, A., Khamfroush, H. & Lucani Rötter, D. E. (2022). QoS-Aware Priority-Based Task Offloading for Deep Learning Services at the Edge. In 2022 IEEE Annual Consumer Communications & Networking Conference (CCNC) (pp. 319-325). IEEE. https://doi.org/10.1109/CCNC49033.2022.9700676

Kuldeep, G. & Zhang, Q. (2022). Design Prototype and Security Analysis of a Lightweight Joint Compression and Encryption Scheme for Resource-constrained IoT Devices. IEEE Internet of Things Journal, 9(1), 165-181. https://doi.org/10.1109/JIOT.2021.3098859

Kuldeep, G. & Zhang, Q. (2022). Multi-class privacy-preserving cloud computing based on compressive sensing for IoT. Journal of Information Security and Applications, 66, Article 103139. https://doi.org/10.1016/j.jisa.2022.103139

Kumar, V., Mukherjee, M., Lloret, J., Zhang, Q. & Kumari, M. (2022). Delay-optimal and Incentive-aware Computation Offloading for Reconfigurable Intelligent Surface-assisted Mobile Edge Computing. IEEE Networking Letters, 4(3), 127-131. https://doi.org/10.1109/LNET.2022.3187720

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). 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, 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

Mørup, C., Kloborg, A. & Lucani Rötter, D. E. (2022). Extreme Bitmapping: Efficiently Sorting Data for Cloud Compression. In 2022 IEEE 11th International Conference on Cloud Networking (CloudNet) (pp. 247-251). IEEE. https://doi.org/10.1109/CloudNet55617.2022.9978780

Mukherjee, M., Kumar, V., Zhang, Q., Mavromoustakis, C. X. & Matam, R. (2022). Optimal Pricing for Offloaded Hard- and Soft-Deadline Tasks in Edge Computing. IEEE Transactions on Intelligent Transportation Systems, 23(7), 9829-9839. https://doi.org/10.1109/TITS.2021.3117973

Mukherjee, M., Kumar, V., Kumar, S., Mavromoustakis, C. X., Zhang, Q. & Guo, M. (2022). RIS-assisted Task Offloading for Wireless Dead Zone to Minimize Delay in Edge Computing. In 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings (pp. 2554-2559). IEEE. https://doi.org/10.1109/GLOBECOM48099.2022.10001478

Displaying results 1 to 50 out of 360

Revised 10.08.2023

Daniel Enrique Lucani Rötter