What is a Fachgespr?ch?

Fachgespr?che are a low-key version of workshops, organized (among others) by the Communication and Distributed Systems group of the Gesellschaft für Informatik. They foster community building by organizing meetings on topics of current interest, with a low entry barrier. The intended audience primarily comprises advanced Master’s students and early-stage PhD researchers, but of course everybody is welcome. Participants are invited to submit full papers, early-stage research ideas, extended abstracts, or work in progress.

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What is MaLeNe?

MaLeNe is one such Fachgespr?ch, dedicated to the interaction of machine learning and networking. Earlier editions can be found here: 2020a, 2020b, 2021 (1^st?NetSys workshop), 2022, 2023 (2^nd?NetSys workshop), 2025 (3^rd?NetSys workshop).
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In recent years, communication networks have become highly flexible through the employment of virtualization and softwarization paradigms. Still, networks are highly complex, dynamic, and time-varying systems, such that the statistical properties of networks and network traffic cannot be easily understood and modeled. Furthermore, the interplay between networking and the dynamic and heterogeneous requirements, expectations, and experiences of applications and users increases the complexity of the systems, which makes fault, configuration, performance, and security management in networks a hard problem. As observed in other disciplines, the successful application of machine learning can help to overcome these issues by following a more data-driven approach. In the networking domain as well, technological advancements in the area of machine learning, the increasing availability of network analytics data, and the flexibility of programmable networks and virtualized network resources have made this approach applicable, which creates exciting new opportunities.
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MaLeNe 2026 aims to provide a forum for researchers addressing emerging concepts and challenges related to machine learning in networking. The Fachgespr?ch will address opportunities where machine learning can bring benefits to networking in different facets, such as network monitoring, management, and security. Together with flexible and programmable networks, this paves the way toward a more proactive and autonomous network design and “self-driving” networks. The long-term vision is that configuration decisions can be made in real time in an automated fashion before service and experience degradation occurs. The Fachgespr?ch will feature original paper presentations that foster discussions and joint work among participants.

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Call for Paper

Paper submission can be made via Call for Papers. Papers submitted and presented for MaLeNe 2026 will be included in proceedings, which are published open access via OPUS. We reserve the right to remove any paper from the proceedings if the paper is not presented at the workshop.

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Registration

Further details on registration, fees, and deadlines can be found on the Registration page.

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Locality

The 7th edition of the KuVS Fachgespr?ch "Machine Learning in Networking (MaLeNe)" will be held on March 19–20, 2026 at the University of Augsburg in Augsburg, Germany.
Additional information on travel, accommodation, and local arrangements is available on the Locality page.

Organizers

• Michael Seufert (University of Augsburg)
• Andreas Blenk (Siemens AG)
• Bj?rn Richerzhagen (Siemens AG)