Markus Hofbauer

Markus Hofbauer

Research Associate and Software Engineer

Technical University of Munich


I am a doctoral candidate in the research group of Prof. Dr.-Ing. Eckehard Steinbach at the Technical University of Munich (TUM). I studied Electrical and Computer Engineering at TUM for both Bachelor and Master. From 2016 to 2018, I was a software engineer at the Objective Software GmbH and Luxoft Inc and worked in cooperation with the BMW Group in the area of Automotive and Autonomous Driving. In January 2019, I joined the Chair of Media Technology at the Technical University of Munich as a research and teaching associate and doctoral candidate.

My current research is focused on video processing, compression, and transmission of multi-camera systems for autonomous and teleoperated driving.

  • Teleoperated Driving
  • Adaptive Video Streaming
  • Software Engineering
  • M.Sc. in Electrical and Computer Engineering, 2016

    Technical University of Munich

  • B.Sc. in Electrical and Computer Engineering, 2014

    Technical University of Munich


Objective Software GmbH / Luxsoft Inc.
IT-Consultant/Software Engineer
Sep 2016 – Dec 2018 Munich
Software Engineer in the automotive industry working on autonomous driving.
Chair of Media Technology
Doctoral Candidate
Jan 2019 – Present Munich
Research and Teaching Associate working on adaptive video streaming for teleoperated driving.

Recent & Upcoming Talks

Adaptive Multi-View Live Video Streaming for Teledriving Using a Single Hardware Encoder
Scale your Workflow
Introduction to different tools and methods for an efficient, scalable, and maintainable workflow.
Test Driven Development
General Introduction to Unit Tests and Test Driven Development by the example of C++.
SOLID Principles
General Introduction to the SOLID Principles at the example of C++.

Recent Publications

Posters & Publications

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Automated Quality Assessment for Compressed Vibrotactile Signals Using Multi-Method Assessment Fusion
Preprocessor Rate Control for Adaptive Multi-View Live Video Streaming Using a Single Encoder
Pixel-Wise Failure Prediction for Semantic Video Segmentation
Situation-Aware Model Refinement for Semantic Image Segmentation
Trajectory-Based Failure Prediction for Autonomous Driving