Christian Lübben, M. Sc.

Research Associate
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Postal address

  • Institut für Informatik der
  • Technischen Universität München
  • Lehrstuhl I8
  • Boltzmannstr. 3
  • 85748 Garching bei München - Germany


Consultation hours

By arrangement


  • Smart Space Orchestration
  • Distributed Systems
  • Machine learning
  • Anomaly detection


Lab Course iLab2

  • The iLab2 is a practical lab course covering selected network topics including IPv6, BGP, IoT Soft-/Hardware, WWW-Security.
    • Students can do hands-on network experiments in our designated lab room where they have access to the required hardware.
      • In times of COVID restrictions, the course is held entirely virtual with adapted lab experiments.
    • In addition, participants create their own small course module about a selected network topic using the same environment.
    • Based on student created lab modules, participants can choose topics such as advanced network protocols, selected network attacks, machine learning and IoT protocols.
  • Roles: Organization, Lecturer
  • Semesters: SS2019, WS2019/20, SS2020, WS2020/21, SS2021, WS2021/22, SS2022, WS2022/23

iLabX Block Course at TUM

  • The iLabX can also be taken as block course at TUM at the end of each semester. The block course consists of the digital MOOC part and selected exercises from the iLab1 and iLab2 in the physical lab environment at the chair.
  • Roles: Lecturer
  • Semesters: WS2019/20

Massive Open Online Course (MOOC) iLabX on edX

  • The iLabX is designed as Massive Open Online Course (MOOC) about the basics of networking, which is globally available for free on edX: iLabX - The Internet Masterclass.
  • A key feature of the iLabX is that relevant networking information is not only taught by video or text, but can be directly experienced as hands-on during the course.
    • For this purpose, the vLab was developed which allows participants to run network experiments in a network emulator on their own computer.
    • This brings the lab courses already available at TUM (iLab1/2) to a much broader audience, as it removes the requirement of having multiple PCs, routers and other components usually required to form a network.
  • Roles: Lecturer, Course Creation

Activities before I started as Research Associate at the chair:

Lecture "Grundlagen Rechnernetze und Verteilte Systeme"

About Me

Christian Lübben is a research associate and PhD student at the chair of Network Architectures and Services at Technical University of Munich (TUM).

He received his Master degree in Informatics from TUM in May 2018. His main area of interest is in Internet of Things and Smart Space research. His research focus lies on optimizing IoT smart spaces using Artificial Intelligence (AI) based data analytics. Challenges include security, usability, resilience, scalability, and performance.

Another field of interest is teaching. With the iLab2 he is advising a practical networking course held at TUM as well as maintaining a Massive Open Online Course (MOOC) aimed at teaching computer network fundamentals using practical exercises in a virtual eLearning environment (iLabX - The Internet Masterclass).

Supervised Theses


Title Type Advisors Year Links
IoT Smart Space Service Management MA Christian Lübben 2020 Pdf
Self-Learning Firewall for Smart Spaces (MA) MA Christian Lübben 2020 Pdf

In progress

Student Title Type Advisors Year Links
tba Design and Implementation of a Web-Based Collaborative Editing Tool for Hardware-Based Lab Courses IDP Christoph Schwarzenberg, Manuel Simon, Christian Lübben, Florian Wiedner 2023 Pdf
Oliver Scheit Git based platform for the management of collaborative teaching content IDP Christoph Schwarzenberg, Christian Lübben, Marc-Oliver Pahl 2022


Author Title Type Advisors Year Links
Maximilian Eder Analyzing eLearning statistics to improve digital teaching methods MA Christoph Schwarzenberg, Christian Lübben, Florian Wiedner, Lars Wüstrich 2022
Jan Oesterle Survey on AI-based Methods for Network Anomaly Detection BA Christian Lübben, Dr. Holger Kinkelin, Lars Wüstrich 2021 Pdf
Nadja Schricker Creating Traffic Causality Graphs from Network Captures and Application Logic MA Lars Wüstrich, Christian Lübben, Holger Kinkelin, Marc-Oliver Pahl 2021
Janik Nier Analysis and Comparison of Attack Sequences BA Lars Wüstrich, Christian Lübben 2021
Achref Aloui Traffic Causality Graphs for Industrial Networks BA Lars Wüstrich, Christian Lübben, Holger Kinkelin 2021 Pdf
Florian Wachter Explainable AI for Anomaly Detection MA Christian Lübben, Lars Wüstrich, Holger Kinkelin 2021 Pdf
Lorenz Lehle Efficient Processing of Large Network Captures BA Lars Wüstrich, Johannes Zirngibl, Christian Lübben 2021 Pdf
Alexander Castendyck Methods for Performance Anomaly Detection in Distributed, Heterogeneous Systems MA Christian Lübben, Marc-Oliver Pahl 2020
Bassam Jaber Quantifying Middleware Interoperability via Emulation MA Erkin Kirdan, Christian Lübben, Marc-Oliver Pahl 2020
Florian Bauer Machine Learning supported IoT Data Modeling BA Marc-Oliver Pahl, Christian Lübben 2020
Simon Schäffner Continuous Microservice Placement in the IoT BA Marc-Oliver Pahl, Christian Lübben 2020
Benjamin Löhner Analyzing User Statistics to Give Individual Learning Feedback and Improve Course Content BA Christian Lübben, Marc-Oliver Pahl 2020
Hande Akin Self-Learning Models for Anomaly Detectin in Smart Spaces MA Christian Lübben, Lars Wüstrich, Marc-Oliver Pahl 2020
open Automated Talk Recording with the Videocube HiWi Christian Lübben, Marc-Oliver Pahl 2020 Pdf
Mohammed Said Derbel AI-based anomaly classification BA Christian Lübben, Lars Wüstrich, Dr. Holger Kinkelin 2020 Pdf
Tobias Wasner Assisted correction of free text answers BA Christian Lübben, Christoph Schwarzenberg, Marc-Oliver Pahl 2020
Sebastian Vogl A Reusable Measurement Framework for optimizing IoT Systems MA Marc-Oliver Pahl, Christian Lübben, Stefan Liebald 2019
Marco Eggersmann Autonomous IoT Service Update and Migration Management MA Marc-Oliver Pahl, Christian Lübben, Stefan Liebald 2019
Julian Ulrich Self-Adapting IoT User Interfaces BA Marc-Oliver Pahl, Christian Lübben, Stefan Liebald 2019
Sebastian Borchers Stream connections in P2P Overlays MA Marc-Oliver Pahl, Stefan Liebald, Christian Lübben 2019
Paulius Sukys IoT Service Modelling MA Marc-Oliver Pahl, Stefan Liebald, Christian Lübben 2019


2021-11-01 Satu Paiho, Jussi Kiljander, Roope Sarala, Hanne Siikavirta, Olli Kilkki, Arpit Bajpai, Markus Duchon, Marc-Oliver Pahl, Lars Wüstrich, Christian Lübben, Erkin Kirdan, Josef Schindler, Jussi Numminen, Thomas Weisshaupt, “Towards Cross-Commodity Energy-Sharing Communities – A Review of the Market, Regulatory, and Technical Situation,” Renewable and Sustainable Energy Reviews, vol. 151, p. 111568, Nov. 2021. [Url] [DOI] [Bib]
2020-01-01 Christian Lübben, Marc-Oliver Pahl, Mohammad Irfan Khan, “Using Deep Learning to Replace Domain Knowledge,” in IEEE ISCC 2020, 2020. [Bib]