
Yehia Ahmed
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Fähigkeiten und Kenntnisse
Werdegang
Berufserfahrung von Yehia Ahmed
- 7 Monate, Sep. 2024 - März 2025Fraunhofer IKS
MSc Thesis Project: Probabilistic DL for Safety Monitoring in ADS
- Trained multimodal probabilistic time series Transformer model for safety critical metrics and uncertainty on CARLA - ROS2 setup. - Enhanced safety assurance monitoring in autonomous driving systems through advanced DL and sequential modeling. - Data collection and parallel training using Slurm HPC cluster and use of containerization tools like docker. - Accepted by COPA 2025 and featured in PMLR, Volume 266. Counted as TUM MSc Thesis joint project with the company .
- 1 Jahr und 10 Monate, Dez. 2022 - Sep. 2024Fraunhofer IKS
ML Research Engineer: Safety Assurance for AI
- Conducted an in-depth review, reproduction, and evaluation of state-of-the-art literature on Out-of-Distribution (OOD). - Developed ML applications via Streamlit and pipelines focusing on Robustness, XAI, OOD, data imbalance, and other activities.
- Lead, designed, & implemented a new target AURIX TC3xx and safety mechanisms modules. - Built knowledge base, integrated, tested, & configured for a new MCAL layer while reporting bugs to suppliers. - Developed & configured, via Vector tools, project-specific features, RTE, OS, memory, and comm. stacks. - Implemented AUTOSAR modules using C/C++ compliant with Valeo & Automotive industry standards & practices. - Created automation scripts to improve code quality & save time across the company.
- 8 Monate, Nov. 2020 - Juni 2021
ML Graduate Researcher
The America University in Cairo
- Developed then integrated ML models into an ensemble one with Pytorch. Also, participated in Research activities.
- 6 Monate, Apr. 2018 - Sep. 2018
Python Developer
Paymob Solutions
- Designed, developed, tested, and documented secure open APIs on Django. Deployed and setup AWS servers.
Ausbildung von Yehia Ahmed
- 3 Jahre und 6 Monate, Okt. 2021 - März 2025
Computer Science
Technical University of Munich
GPA: 1.7 - Focus: Machine and Deep Learning, Computer Vision, Reinforcement Learning, and SW engineering - Authored a review paper on the state-of-the-art research in Input Dependent Randomized Smoothing Methods. - Courses: Computer Vision III, Machine Learning for Graphs & Sequential Data, Deep Learning , Machine Learning, Explainable AI for ML (xAI), Adv DL in Medicine (ADLM)
- 4 Jahre und 10 Monate, Sep. 2012 - Juni 2017
Computer Engineering
The American University in Cairo
- GPA: 3.64/4.0 - Minor in Business Administration. - Courses: Practical Machine Deep Learning, Secure Sys., Distributed Sys., Embedded Sys., Software Eng, Object Oriented Programming (C++), Analysis & Design of Algorithms, Compiler Design. Extensive in C++. - Graduation Project: Lynks (Nodejs & Electron). Developed P2P decentralized distributed cloud storage system distributing data over many nodes across the network and using DHT, correction codes, and security encryption and design concepts.
Sprachen
Englisch
C2 (Verhandlungssicher / Muttersprachlich)
Deutsch
B1-B2 (Gute Kenntnisse)
Arabisch
C2 (Verhandlungssicher / Muttersprachlich)
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