- Safety-Critical Oracles for Metamorphic Testing of Deep Learning LiDAR Point Cloud Object Detectors. IEEE Open Journal of Intelligent Transportation Systems 6, 2025, 95-108 mehr…
- GeMTest: A General Metamorphic Testing Framework. 2025 IEEE/ACM 47th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), 2025, 41-44 mehr…
- Generating Latent Space-Aware Test Cases for Neural Networks using Gradient-Based Search. Proceedings of the 18th IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), 2025, 1-8 mehr…
- Deep learning with RGB and thermal images onboard a drone for monitoring operations. Journal of Field Robotics 39 (6), 2022 mehr…
Simon Speth, M.Sc.
Technische Universität München
Informatik 4 - Lehrstuhl für Software und Systems Engineering (Prof. Pretschner komm.)
Postadresse
Boltzmannstr. 3
85748 Garching b. München
- Tel.: +49 (89) 289 - 17836
- E-Mail: simon.speth(at)tum.de
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 | Master's |
| 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 |
Teaching
| Semester | Course |
|---|---|
| Winter 2022/2023 | Advanced Testing of Deep Learning Models - Towards Robust AI |
| Summer 2022 | Advanced Topics of Software Testing |
| Winter 2021/2022 | From Sub-Systems to Systems of Systems – Developing Autonomous Driving Functions (in cooperation with fortiss) |
| Summer 2021 | Requirements Engineering Requirements Engineering (Elite program) |