CV
A one-page PDF copy of my CV is available here.
Education
Ph.D in Computer Science , Technische Universität Berlin, 2025 (expected)- Doctoral Thesis: "Towards a Deeper Understanding of the Lifecycle of Out-of-Distribution Data
in Autonomous Perception Systems", emphasis on robust detection, analysis, and mitigation
and recovery strategies for OoD data in automated-driving applications. - Supervisor: Prof. Dr. Hanno Gottschalk
M.Sc. in Computer Science, Universität Bonn, 2022- Thesis: "Link Prediction for Dynamic Communications Networks using Graph Neural Networks"
- Supervisor: Dr. Michael Gerz, Prof. Dr. Petra Mutzel
- Awards: AFCEA Bonn e.V 3rd place master thesis award
- Cumulative GPA: (1.2/5)
B.Sc. in Computer Science, German University in Cairo, 2020- Cumulative GPA: (1.28/5) -Excellent with High Honors-
Bachleor Thesis, Technische Universität Dresden, 2019- Thesis: "Evaluation of Classifiers using Resampling Methods"
- Supervisor: Prof. Dr. Wolfgang E. Nagel, Prof. Dr. Slim Abdennadher
Work experience
Sept 2022 - Present : Machine Learning Researcher- Continental AG (Berlin, Germany)
- Part of the Research and Advanced Engineering department, where I work on developing
and implementing AI-based methods and tools to collect and process data efficiently. - Developed methods for uncertainty estimation, out-of-distribution detection, anomaly
segmentation, object tracking, and information retrieval for a data curation and
active learning use case. - Developed automated data quality assessment and silent testing methods
to detect model errors and validate perception algorithms.
Nov 2020 - July 2022: Research Assistant- Fraunhofer FKIE (Bonn, Germany)
- Part of the Interoperability and Testing group, where I worked on setting up simulation
environments and used reinforcement learning methods for optimization and testing. - Implementation and evaluation of reinforcement learning algorithms for multi-agent environments.
- Investigated the use of graph neural networks for creating a digital twin of a
5G communication network for a reinforcement learning network optimization framework. - Recommendation Letter
October 2020 - December 2020: Data Engineer- Monikit, (Bonn, Germany)
- Member of the monikit startup working on an automatic detector for epileptic seizures.
- Preprocessing and labelling electrocardiogram (EKG) data from hospital records for use by the machine learning team.
- Visualization and reporting features and meta-data of available data records.
- Recommendation Letter
Feb 2019 - July 2019: Research Assistant- Center for Information Services and High Performance Computing (ZIH), (Dresden, Germany)
- Investigated the use of deep learning methods in a distributed computing environment.
- Comparison of different model and data parallelism techniques for different architectures.
- Proof of Work
Skills
- Python (NumPy, Pytorch)
- C/C++ (CUDA)
Publications
Shoeb, Y., Nowzad, A. & Gottschalk, H. (2025). "Out-of-Distribution Segmentation in Autonomous Driving: Problems and State of the Art " Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops.
Shoeb, Y., Nayal, N., Nowzad, A., Güney, F. and Gottschalk, H. (2025). " Segment-Level Road Obstacle Detection Using Visual Foundation Model Priors and Likelihood Ratios " Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP.
Shoeb, Y., Nowzad, A. & Gottschalk, H. (2025). "Adaptive Neural Networks for Intelligent Data-Driven Development " IEEE Intelligent Vehicles Symposium (IV).
Uhlemeyer, S., Lienen, J., Shoeb, Y., Hüllermeier, E. and Gottschalk, H. (2024). " Unsupervised Class Incremental Learning using Empty Classes " Proceedings of British Machine Vision Conference Workshops.
Nayal, N.*, Shoeb, Y.*, & Güney, F. (2024). A Likelihood Ratio-Based Approach to Segmenting Unknown Objects." International Journal of Computer Vision (IJCV).
Shoeb, Y., Chan, R., Schwalbe, G., Nowzad, A., Güney, F. & Gottschalk, H. (2024). "Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes." Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Patents
Vehicle, Apparatus, Computer Program, and Method for Out-of-Distribution Object Detection
European Patent Office (EP4465250A1) | WIPO (WO2024235674)
Vehicle, Apparatus, Computer Program, and Method for Detecting an Out-of-Distribution Object
European Patent Office (EP23214166)
Professional Service
- Reviewer
- Session Moderator
