Welcome to the Computer Networks Research Group

The Computer Networks group conducts research and teaching activities focusing on networked systems of all kinds, ranging from cloud data centers to mobile devices. In the era of AI proliferation, networked systems have become critical infrastructures for supporting both the training and inference of large machine learning models. Our research explores how to make such networked systems more efficient and sustainable.

Open Po­si­ti­ons

PhD Researcher

We are looking for a PhD student (pay grade TV-L E13) working on efficient networked systems for machine learning. We are particularly interested in candidates with experience in machine learning systems.

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Student Research Assistant

We are continuously looking for student research assistants (WHB) to work on systems for machine learning.

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News

Left to right: Huzaifa Shaaban Kabakibo, Eric Schniedermeyer, Artem Burchanow

Pro­ject Group Pre­sen­ted Their Re­sea­rch Re­sults

On July 25, 2025, Master's students at the Computer Networks group presented their research results on sustainable Internet of Things (IoT). During the last two semesters, two subgroups of students focused on making battery-free IoT systems more efficient and enabling the fast and accurate inference of large language models (LLMs) on resource-constrained IoT devices, respectively.

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Pa­per Ac­cep­ted to ACM Mo­bi­Com 2025

Our paper titled "Uirapuru: Timely Video Analytics for High-Resolution Steerable Cameras on Edge Devices" has been accepted to the 31st Annual International Conference On Mobile Computing And Networking (MobiCom) to be held in Hong Kong, China during November 4-8, 2025.

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PhD De­fen­se of Ga­os­heng Liu

Gaosheng Liu successfully defended his PhD thesis titled "Efficient Communication and Data Aggregation in Battery-Free Internet-of-Things" on April 2, 2025 at VU Amsterdam.

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Re­sea­rch

Detailaufnahme des Großcomputers Noctua an der Universität Paderborn.

We focus our research on networked systems and we strive to create concepts and methods to make networked systems, ranging from data centers to mobile/IoT devices, more efficient and sustainable for modern machine learning applications. Our goal is to create better programming tools, systems, and protocols, leveraging the capabilities offered by emerging hardware. Main research topics include: machine learning inference in data centers, time-sensitive on-device AI inference, data center in-network computing, and battery-free Internet-of-Things. 

Current Research Areas Publications

Te­a­ching and The­sis

Our teaching is focused on networked systems. Our recent, current, and upcoming course offerings are listed below. Note that the upcoming ones are projections based on offerings in last year and may be subject to changes. We offer thesis projects at both bachelor and master levels continuously. Please check this page for currently offered thesis/project topics.

 

The following modules will be offered regularly in the coming years. 

  • Lecture: Computer Networks (BSc) - Winter Semsters
  • Lecture: Distributed Systems (BSc) - Winter Semester
  • Lecture: Advanced Networked Systems (MSc) - Summer Semsters

Team

We are a dynamic, international team with members coming from different countries and with different backgrounds. Please check this page to know more about our group and all members.

Con­tact

Prof. Dr. Lin Wang

Rechnernetze

Raum O3.149
Universität Paderborn
Pohlweg 51
33098 Paderborn

+49 5251 60-5375 E-Mail schreiben Wegbeschreibung

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