News and Announcements

  • Habilitation degree in Electrical Engineering

    March 12, 2026

    Our team member Jorge Torres Gómez has received the certificate for Habilitation in the field of Electrical Engineering. The habilitation certifies the ability to conduct independent research and to teach courses at universities, and it formally qualifies the holder to supervise doctoral students and to pursue a professorship. His habilitation research work focused on developing communication systems that interact with biological processes at the nano- and microscales. This research direction lies at the intersection of telecommunications engineering, molecular communication, and bio-nanotechnology, contributing to the emerging vision of the Internet of Bio-Nano-Things. The habilitation procedure included a cumulative research thesis as well as academic examination components, including a habilitation colloquium and a teaching demonstration. Together, these elements assess both the candidate’s scientific contributions and their ability to teach at the university level.

  • TKN at Unesco House (IASEAI'26)

    March 12, 2026

    Our team member Osman Tugay Basaran participated in the Annual Summit of the International Association for Safe and Ethical Artificial Intelligence (IASEAI), held at the historic UNESCO House in Paris. The summit gathered a global cohort of researchers, policymakers, and industry leaders to address the critical challenge of ensuring AI development remains safe, ethical, and aligned with human values. Beyond broad governance, we contributed to the “AIxBio: Safety Evaluations, Governance, and Standards” workshop, organized by the Johns Hopkins Center for Health Security with the European Commission AI Office, to tackle the specific technical risks at the intersection of AI and life sciences. Our involvement focused on bridging the gap between high-level ethical principles and technical implementation, ensuring that as AI scales across diverse technological areas, it remains transparent and firmly aligned with human values.

  • New IEEE Transactions on Mobile Computing article

    March 07, 2026

    Our article Hierarchical Federated Learning in Device-to-Device Networks with Learning-Topology Co-Optimization has been accepted for publication in IEEE Transactions on Mobile Computing. Federated learning (FL) enables collaborative model training across distributed devices while preserving privacy. However, growing heterogeneity in device resources and communication links challenges conventional FL, especially when relying on a single central server. Hierarchical federated learning (HFL) mitigates these issues by organizing devices into clusters coordinated through intermediate aggregators. Yet, the effectiveness of HFL critically depends on how clusters are formed: intra-cluster communication must be efficient, device computational capacities should be balanced to reduce stragglers, and data heterogeneity must be managed to ensure stable convergence. In this work, we propose a learning–topology co-optimization framework for HFL in networks where nodes communicate with each other with links of varying quality (e.g., device-to-device (D2D) or mesh networks). Our method jointly optimizes device connection topology and learning directions, leading to communication-efficient clusters that remain well aligned in optimization space. We provide a convergence analysis under mild assumptions, showing how inter- and intra-cluster divergence affect learning stability. Extensive experiments demonstrate that our approach consistently improves HFL performance, yielding at least a 6% accuracy gain under unbalanced data distributions and over 16% reduction in training time for regression tasks compared with existing clustering algorithms.
    (link to more information)

  • TKN at WONS 2026

    March 04, 2026

    Our team member Dr. Doganalp Ergenc and guest researcher Elena Tonini presented their works at WONS 2026 in Switzerland. In his paper Multi-Link Scheduling with Restricted Target Wake Time in Wi-Fi 7, Doganalp presents a novel time-sensitive scheduling approach levaraging the new features of Wi-Fi 7. In Leveraging Mutual Information in Stochastic CSI Analysis for Wi-Fi Sensing, Elena investigates the existence of mutual information across different CSI measurements in the context of Wi-Fi sensing. Last but not least, our external researchers Laura Finarelli and Berk Buzcu took part in the conference as web chair and local organizer, respectively. We thank and congratulate all our researchers for their contributions!

  • New IEEE Transactions on Control Systems Technology article

    March 03, 2026

    Our article Decentralized Model Predictive Control for Platooning: Enhancing Human-Driver Collaboration has been accepted for publication in IEEE Transactions on Control Systems Technology. Recent advances in cooperative adaptive cruise control have demonstrated the potential for vehicle platooning to revolutionize road transportation through enhanced safety, reduced congestion, and improved energy efficiency. While autonomous vehicle technology continues to evolve rapidly, current regulatory frameworks and safety considerations necessitate the human driver supervision. This creates a unique challenge in developing control systems that can effectively balance autonomous operation with human intervention. To enhance the human-driver collaboration with autonomous vehicle platooning, in this paper, we present a novel decentralized model predictive control framework that explicitly incorporates human-driver interaction while maintaining desired inter-vehicle distances and velocities in platoon formations. This framework employs a distributed architecture where each vehicle operates independently and exchanges local measurements through vehicle-to-vehicle communication. To overcome the inherent unreliability of wireless communications in real-world scenarios, we develop a robust distributed state estimation strategy. This approach enables each vehicle to combine local sensor measurements with received data to construct accurate estimates of the full platoon state. Based on these estimates, vehicles compute optimal control actions locally while achieving performance comparable to an ideal centralized controller with perfect communication.
    (link to more information)

  • Presentation at xG-Incubator Networking Event

    February 20, 2026

    At the xG-Incubator networking event, our team member Jorge Torres Gómez presented the BACT-ID device concept, a microfluidic circuit for early detection of bacterial infections. The core idea is to embed physical signal processing directly into the geometry of a microfluidic chip, allowing it to amplify weak biomarker signals without increasing power consumption or system complexity. The concept integrates micro-sampling, BioFET sensing, and Bluetooth connectivity into a portable device. We aim to significantly improve sensitivity while reducing false positives to enable faster, more reliable detection of pathogen-specific biomarkers. Such a device would be used for applications including wound monitoring, sepsis screening, and antibiotic testing.

  • New staff member: Dr. Dilara Aktas

    February 20, 2026

    We welcome Dr. Dilara Aktas who joined our group in February 2026.

  • Plenary Talk at IEEE ICNC 2026

    February 17, 2026

    Falko Dressler gave a plenary talk titled Virtualized Edge Computing: Bridging Communications, Computing, and AI at the IEEE International Conference on Computing, Networking and Communications (ICNC 2026), which was held in Maui, HI.
    (link to more information)

  • New IEEE Transactions on Parallel and Distributed Systems article

    February 16, 2026

    Our article Fed-Grow: Federating to Grow Transformers for Resource-Constrained Users without Model Sharing has been accepted for publication in IEEE Transactions on Parallel and Distributed Systems. The growing resource demands of large-scale transformer models pose significant challenges for resource-constrained users, particularly in distributed environments. To address this issue, we propose a federated learning framework called Fed-Grow, which enables multiple participants to collaboratively learn a lightweight scaling operation that transfers knowledge from pretrained small models to a large transformer model. In Fed-Grow, we introduce the Dual-LiGO (Dual Linear Growth Operator) architecture, consisting of Local-LiGO and Global-LiGO components. Local-LiGO addresses model heterogeneity by adapting each participant’s pre-trained model to a common intermediate form, while Global-LiGO facilitates knowledge sharing across participants without sharing local models or raw data, ensuring privacy preservation. This federated approach offers a scalable solution for growing large transformers in a distributed manner, where only the Global-LiGO is shared, significantly reducing communication overhead while maintaining comparable model performance under the same communication constraints.
    (link to more information)

  • Tutorials at IEEE CCNC 2026

    January 09, 2026
    TKN presented two tutorial lectures at the IEEE Consumer Communications and Networking Conference (CCNC 2026), which was held in Las Vegas, NV. Doğanalp Ergenç and Nurefşan Sertbaş Bülbül talked about IEEE 802.1 Time-Sensitive Networking Beyond Theory: Convergence, Resilience, and Practical Insights. In parallel, Falko Dressler and Onur Altintas talked about Cooperative Computing and AI on Cars using 6G Virtualized Edge Computing.

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Last modified: 2024-04-28