Mohamed Hassan
Machine Learning Engineer Intern
Experience
Machine Learning Engineer Intern
Kautex Textron
- Developed deep learning models for industrial shape optimization
- Built deployment pipelines for production-ready ML systems
Research Assistant
University of Bonn
- Worked on scalable deep learning in HPC environments
- Supported teaching in ML/DL courses
Teaching Assistant
Bonn-Rhein-Sieg University
Electrical Engineer
NECE
- Conducted testing and commissioning of HV substations, including GIS switchgears, power cables, control panels, and distribution boards
- Configured and tested protection relays (ABB, Alstom, GE, Schneider, MICOM) for grid stability and fault protection
- Ensured compliance with IEC standards and safety protocols during system energization
Electrical Engineer
Al-Babtain
- Specialized in protection relay configuration for MV feeders, transformer differential protection, and line distance protection
- Performed troubleshooting and modifications of protection schemes to enhance system reliability
- Developed detailed test procedures and documentation for quality assurance
Industry Experience
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Experienced in Utilities, Automotive, Manufacturing, Education, and Energy.
Business Area Experience
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Experienced in Operations, Quality Assurance, Research and Development, and Information Technology.
Summary
Results-driven Electrical Engineer with 4+ years of experience in HV substation testing, commissioning, and protection systems. Skilled in configuring protection relays (ABB, GE, Schneider) and ensuring compliance with industry standards.
Moreover, I bring theoretical expertise and hands-on experience in AI, machine learning, and automation. Experienced in designing and deploying solutions to real-world challenges, I specialize in deep learning, NLP, computer vision, and MLOps. My toolkit includes LLMs, agentic AI, RAG, FastAPI, and Docker, enabling the development of scalable, production-ready AI systems.
Skills
Gaussian-centered Cropping For Contrastive Learning – Computer Vision, Pytorch, Unsupervised Learning, Cnns
Proposed Gaussian-centered Cropping (Gcc) To Reduce False Positives In Ssl.
Achieved +2.7–12.4pp Accuracy Vs. Randomcrop With No Extra Compute.
Preprint: Taming The Randomness – [Arxiv Link]
Multimodal Sentiment Analysis Via Emotional Embeddings – Nlp, Llm, Transformers, Lstm
Leveraged Emotional Embeddings From Goemotions To Classify Yelp Reviews.
Demonstrated Transfer Learning Preserved Sentiment Signals Across Domains.
Power Systems: Testing & Commissioning, Hv/mv/lv Systems, Ct/vt
Protection Systems: Relay Configuration (Abb, Ge, Schneider, Alstom), Scada
Data & Modeling: Sql, Mysql, Feature Engineering, Statistics, Predictive Modeling, Python (Numpy, Pandas, Scipy), R
Rag & Llms: Langchain, Chromadb, Llamaindex, Hugging Face Transformers
Model Deployment & Mlops: Fastapi, Docker, Kubernetes, Aws Cloud (Sagemaker, Ec2, S3), Mlflow, Git, Ci/cd Pipelines
Multi-modal Ai: Computer Vision, Nlp, Audio Processing, 3d Meshes/point Clouds
Visualization: Tableau, Plotly, Matplotlib, Seaborn
Languages
Education
Bonn-Rhein-Sieg University of Applied Sciences
M.Sc. Autonomous Systems · Autonomous Systems · Germany · GPA: 1.3
Zagazig University
B.Sc. Electrical Engineering · Electrical Engineering · Egypt · Very Good
Certifications & licenses
Certified by Saudi Electricity Company (SEC) National Grid
Statistics
Experience
Global Experience
Expertise
Qualifications
Profile
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