Welcome to the Computer Networks group!

The Computer Networks group conducts research and teaching activities focusing on networked systems of all kinds, ranging from large-scale cloud data centers to tiny low-power IoT devices. The group is headed by Prof. Lin Wang

We are looking for multiple postdocs, PhDs, and SHKs to join our group. Please check the vacancies here.


  • 03.2024: Paper on autoscaling of inference serving systems accepted to ACM EuroMLSys@EuroSys 2024.
  • 01.2024: Paper on efficient serverless GNN serving accepted to ACM The Web Conference (WWW) 2024.
  • 12.2023: Two papers accepted to IEEE INFOCOM 2024.
  • 11.2023: RICS received the Best Paper Award at IEEE IPCCC 2023.


We focus our research on networked systems and we strive to create concepts and methods to make networked systems more efficient, scalable, usable, and sustainable. Our focus is on creating better programming tools, middleware, and protocols, leveraging the capabilities offered by emerging hardware. Our research has been generously supported by various funding sources including the German Research Foundation (DFG), the Dutch Research Council (NWO), Google Research, and Intel. 

In-Network Acceleration

The emergence of programmable network devices (P4 switches, SmartNICs, and DPUs) has motivated a new concept called in-network computing. We are exploring how programmable network elements can better contribute to computation acceleration in the post-Moore's law era.

Sustainable IoT

IoT systems are ubiquitous nowadays. Yet, virtually all IoT devices rely on battery to function. Batteries are hazardous, prone to disasters, and hard to maintain --- all indicating that current IoT systems are not sustainable. We are working towards sustainable IoT systems by removing completely the batteries from IoT devices.

Systems for Machine Learning

Machine learning is powering many of our intellegent services in our daily life. Yet, serving computation-intensive machine learning workloads while meeting their stringent throughput/latency requirements remains a critical challenge. We are developing efficient network systems across the cloud and edge to support machine learning inference.


Lecture: Computer Networks

In this lecture-based course we will explore the principles underlying the design of computer networks and the Internet. We will discuss the layered architecture of the network stack and dive into the network protocols at each layer that make data communication happen from one place to another.

Lecture: Advanced Networked Systems

This lecture-based course will cover concepts and designs for modern networked systems adopted by the Internet and cloud data centers to meet the ever-increasing demands of data transfer and computation driven by big data and machine learning applications.

Seminar: In-Network Computing

In this seminar, we dive into the different aspects of in-network computing, aiming to understand the driving technologies and applications. We focus on three different areas: hardware architecture, programming support, and applications (machine learning and security).


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.


Prof. Dr. Lin Wang

Computer Networks

Room O3.149
Paderborn University
Pohlweg 51
33098 Paderborn