CV

[Download CV PDF]

Education

• Master of Science: Computer Science, University of Stuttgart & University of Adelaide, 10/2022 - 03/2026 (expected)
  • Current Grade: 1.3 (Scale: 1.0 = Best) • Completed 114/120 ECTS
  • Semester Abroad at the University of Adelaide (Baden-Württemberg Scholarship Recipient)
  • Master Thesis: “Deep learning for anomaly detection in vehicle control units in trace files” (Supervisor Prof. Dr. Mathias Niepert)
• Bachelor of Science: Computer Science, University of Stuttgart, 10/2018 - 09/2022
  • Final Grade: 1.9 (Scale: 1.0 = Best) • Completed 180/180 ECTS
  • Bachelor Thesis: “Parameter-Dependent Self-Learning Optimization” (Supervisor Prof. Dr. Dirk Pflüger)

Research Experience

• Master Thesis: Deep learning for anomaly detection in vehicle control units in trace files, University of Stuttgart & Porsche AG, 09/2024 - 02/2025
  • Benchmarked LogLLM vs. LogBERT on proprietary Porsche and open-source data (BGL, ThunderBird)
  • Demonstrated that larger models (8B vs 1B) significantly increase F1-scores (e.g. BGL 0.419 to 0.912)
• AI Laboratory Course: Credit Card Fraud Detection, University of Stuttgart, 10/2023 - 03/2024
  • Compared DL methods vs. traditional Anomaly Detection on tabular data with 550k+ transactions
  • Achieved sota macro-average F1-score of 93% using OC-NN, outperforming kNN baselines (89%)
• Study Project: Automated Clustering of Small Molecules, University of Stuttgart, 10/2023 - 03/2024
  • Improved performance by 15% compared to university’s baseline using UMAP and MDAnalysis
• Bachelor Thesis: Parameter-Dependent Self-Learning Optimization, University of Stuttgart, 04/2022 - 09/2022
  • Developed a Learn-to-Optimize framework using RL (REINFORCE, PPO) to solve black-box problems
  • Demonstrated agent generalization to unseen parameter configurations in up to 10 dimensions

Work Experience

• Working Student (AI/LLM), Porsche AG, 10/2025 - today
  • Automated test case generation from hardware requirement specifications using LLMs and AWS
• Data Science Research Intern, Porsche AG, 03/2024 - 08/2024
  • Analyzed correlation of customer complaints and ECU faults in vehicles via Association Rule Discovery

Teaching

• Teaching Assistant, University of Stuttgart, 10/2019 - 09/2020
  • Taught weekly tutorials in “Data Structures and Algorithms” and “Theoretical CS” for 60+ students

Projects

• Blog Post: Mastering the Game of Go, University of Stuttgart, 10/2023 - 03/2024
  • Published technical breakdown of AlphaGo/AlphaZero concepts (MCTS, Deep RL) on GitHub Pages
• School For Talents, German Research Foundation, 04/2023 - 03/2024
  • Organized scientific workshops and keynotes about AI for 100+ students
• AI Incubator Batch #3 (Winner), Cyber Valley & Carl-Zeiss-Stiftung, 10/2023 - 11/2023
  • Won “Business Model Award” for “VectisFinance”, an AI-Fintech startup prototype

Extracurricular Activities

• AI Software Academy (AISA), University of Stuttgart, 10/2023 - 09/2025
  • Certificate of Advanced Studies (18 ECTS) focusing on the intersection of AI and Software Engineering
• AI Career Kickstart Program, AppliedAI Institute of Europe, 11/2023 - 11/2024
  • Training on interdisciplinary topics like “ML Operations”, “AI Regulations” and “ML Organizational Roles”

Skills & Expertise

• Reinforcement Learning: PPO, SAC, DQN, MCTS, DynaQ+, Policy Gradients, Bandits, (PO)MDPs
• Deep Learning Architectures: Transformers (LLMs), Diffusion Models, GANs, Autoencoders, CNNs, RNNs, GNNs
• Core Stack: Python, PyTorch, TensorFlow, JAX, CUDA, Hugging Face, Scikit-learn, Pandas, NumPy
• Languages: German (Native), English (C1/Fluent)

Publications

Parameter-dependent self-learning optimization

Abu El Komboz, Tareq. "Parameter-dependent self-learning optimization ". BS thesis. 2022.