Foto von Simon Speth

Simon Speth, M.Sc.

Technische Universität München

Informatik 4 - Lehrstuhl für Software und Systems Engineering (Prof. Pretschner komm.)


Boltzmannstr. 3
85748 Garching b. München

  • Tel.: +49 (89) 289 - 17836
  • simon.speth(at)

About Me

I am a Ph.D. student at the Chair of Software and Systems Engineering headed by Professor Pretschner. My main research focus is on testing machine learning and deep learning models. Specifically, I am interested in a technique called metamorphic testing.


Thesis Topics

If you are interested in writing a thesis related to my research interests, please contact me by email.

Open Topics:

Title Type
Search-Based Robustness Testing for Deep Learning Systems Guided Research
Generation and Analysis of Metamorphic Test Cases for Neural Networks Any


Assigned Topics: 

Title Type
Data Augmentation in the Latent Space for Boosting Performance on Radar-Based Presence Sensing Applications Master's
Improving Robustness of Semantic Segmentation for Autonomous Driving Master's


Finished Topics: 

Title Type

Search-Based Robustness Testing for Deep Learning Computer Vision Systems

Metamorphic Testing of LiDAR/RADAR Obstacle Detection Systems Master's
Inverse Transparency for Cloud Architectures Bachelor's
Latent Space-Based Test Case Generation of Naturally Occurring Environmental Conditions for Traffic Sign Classifiers Master's


Semester                     Course
Winter 2022/2023 Advanced Testing of Deep Learning Models - Towards Robust AI
Summer 2022

Advanced Topics of Software Testing

Advanced Python Programming

Winter 2021/2022

Introduction to Informatics I

From Sub-Systems to Systems of Systems – Developing Autonomous Driving Functions (in cooperation with fortiss)

Seminar: Software Quality

Summer 2021

Requirements Engineering

Requirements Engineering (Elite program)

Seminar: Software Quality


  • Speth, Simon; Gonçalves, Artur; Rigault, Bastien; Suzuki, Satoshi; Bouazizi, Mondher; Matsuo, Yutaka; Prendinger, Helmut: Deep learning with RGB and thermal images onboard a drone for monitoring operations. Journal of Field Robotics 39 (6), 2022 more…