I am Eslam Sharaawy,
a data scientist
& ML developer
based in Germany.
About
Hi, I'm Eslam — a curious mind with a love for data, code, intelligent systems, and cooking. With a background in engineering and a Master's in Computational Science, I've dived deep into machine learning, computer vision, and everything in between. Whether it's building few-shot models or solving real-world problems with AI, I enjoy turning complex challenges into elegant solutions. When I'm not coding or analyzing data, you'll often find me experimenting in the kitchen. I'm always exploring, learning, and creating with purpose and passion.
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- Data Science
- Machine Learning
- Automation
- Software development
- Mathmatics
- Statistics
- Physics
Experience
Volkswagen Financial Services
Data Science - Internship
July 2024 - April 2025
Developed a damage cost prediction model combining ResNet-based visual features with vehicle data, using CatBoost to cut RMSE by 43%. Accelerated deep learning inference by 35% via hyperparameter tuning and data augmentation. Proposed AI-driven process improvements and, for a master’s thesis, built a few-shot learning method for detecting rare vehicle damages.
Volkswagen Financial Services
Working Student - IT Test Engineer
March 2023 - March 2024
Tested and validated new systems to identify and track errors in close collaboration with the development team. Automated reports using VBA, resulting in a 30% reduction in manual processing time. Supported the team in daily tasks to enhance overall efficiency.
TU Braunschweig
Working Student - Institute of Machine Tools and Manufacturing Technology
September 2022 - March 2023
Simulated a component of an injection molding machine by varying key process parameters and created a predictive model based on the simulation data to forecast outcomes without the need for repeated simulations. Utilized this data-driven approach to support the development of a digital twin, enabling real-time performance monitoring and predictive maintenance.
IT RANKS
Junior System Administrator
September 2020 - September 2021
Delivered technical support for servers, Exchange migrations, and client connectivity, escalating issues as needed to ensure stable IT operations. Maintained and secured infrastructure via backups, disaster recovery, system hardening, and compliance with security policies. Handled daily IT tasks, including documentation, storage planning, workstation/server upkeep, and software/network performance optimization.
AL-EMAM FOR ENGINEERING & PROJECTS
Technical Engineer
July 2019 - September 2020
Managed a major project in Egypt’s new administrative capital on behalf of Siemens, ensuring quality control and implementation of mechanical designs in accordance with internal Siemens standards, and provided regular progress reports to the client.
Education
Technische Universität Braunschweig
Master in Computational Science
March 2025
Achieved a final grade of (2.1 - German Grading System) with strong expertise in mathematics, programming, statistics, simulations, and physics applied to real-world problems. Specialized in artificial intelligence and data science, mastering data analysis, regression, classification, data modeling, classical machine learning methods like XGBoost and Random Forest, as well as advanced deep learning techniques including CNNs, attention mechanisms, and transformer models. Gained practical experience in both Generative AI—covering computer vision and large language models (LLMs)—and Classical AI, as well as physics-informed neural networks (PINNs). Completed a student project focused on semantic segmentation of infrastructure cracks using machine and deep learning. For the master’s thesis in collaboration with Volkswagen Financial Services, developed a few-shot computer vision pipeline that reduced annotation costs by 35% and enabled rapid detection of rare defects.
Helwan University - Cairo / Egypt
B.Sc. Degree in Mechanical Power Engineering
July 2019
Holds a Bachelor’s degree in Mechanical Power Engineering from Helwan University, Faculty of Engineering in El Matareya, completed in May 2019. Graduated with an overall grade of 86.6% and the distinction "Excellent," including an "Excellent" rating for the final project. The cumulative GPA of 80.44% earned the classification "Very Good with Honors." The program, accredited by Egypt’s National Authority for Quality Assurance of Education, provided a strong foundation in core areas such as Mathmatics, Physics, Mechanical Design, statistics, Programing, and Power Systems, with consistently high performance throughout the five years of study.
Skills
My current proficiency levels in the tools, technologies, and languages.
Projects
A selection of my key projects in AI, ML, and Data Science.
Semantic Segmentation of Infrastructure Cracks
Deep Learning (CNN, Transformer) for precise defect detection in infrastructure.
Risk Modeling for Leasing Returns
Multimodal ML models (ResNet + CatBoost) reducing RMSE by 43% for damage cost prediction.
Physics-Informed Neural Networks
Hybrid ML + PDE approach for predicting physical systems.
Digital Twin from Simulation & Experimental Data
Combining simulation and real measurements for accurate digital twin creation.
Few-Shot Object Detection for Rare Automotive Defects
CV pipeline with minimal annotations, reducing labeling costs by 35%.
Satellite-Based Natural Disaster Prediction
ML + statistics applied to satellite data for disaster forecasting (IGP, TU Braunschweig).
Skin Defect Detection & Treatment Recommendation
Computer vision system to detect skin defects and recommend treatments.
Semantic Segmentation of Infrastructure Cracks
Developed a both Machine learning and deep learning pipeline using classical ML Solutions, CNN and Transformer architectures to detect and segment cracks in roads and bridges with high precision.
Risk Modeling for Leasing Returns
Built multimodal ML models combining ResNet image features with structured data via CatBoost, reducing RMSE in cost predictions by 43%.
Physics-Informed Neural Networks
Implemented a hybrid approach combining partial differential equations with neural networks to predict physical system behavior more accurately.
Digital Twin from Simulation & Experimental Data
Created a digital twin model integrating high-fidelity simulations with experimental sensor data for real-time system monitoring and optimization.
Few-Shot Object Detection for Rare Automotive Defects
Developed a few-shot learning CV pipeline to detect rare automotive defects, significantly reducing the need for labeled data and cutting annotation costs by 35%.
Satellite-Based Natural Disaster Prediction
Applied ML and statistical analysis to satellite imagery for early detection and prediction of natural disasters, in collaboration with IGP, TU Braunschweig.
Skin Defect Detection & Treatment Recommendation
Created a CV-based system to identify skin conditions and suggest relevant treatments using image classification and medical datasets.
References
Endorsements from supervisors, collaborators, and institutions I’ve worked with.
Volkswagen Financial Services
Data Analytics & AI Department
Mr. Sharaawy displayed initiative at all times and impressed us with his very keen motivation to work. He proved himself to be an assiduous employee with a good ability to work under pressure, and he also handled all assignments well, even under difficult working conditions. His intellectual grasp enabled him to quickly and successfully familiarize himself with new assignments. Mr. Sharaawy was in possession of solid specialist knowledge. The quality of Mr. Sharaawy's work was consistently good. The scope and pace of his work exceeded our expectations at all times. He could always completed all assignments to our full satisfaction. Mr. Sharaawy was a responsible and universally respected employee who always had a good working relationship with his superiors and colleagues. Owing to his high level of professional performance and very good social skills, he quickly earned the respect and recognition of his colleagues. His good team skills and ability to cooperate with others were valued and recognized by all. His conduct towards superiors, colleagues, other employees and customers was exemplary. View Reference.
Prof. Dr.-Ing. Mohamed Nabil Metwally
Helwan University
This to certify that I have known engineer: Mr. Sharaawy, enrolment as an undergraduate student in the Mechanical Power Engineering Department of the Faculty of Engineering at Helwan University, Cairo/Egypt, who was graduated in summer 2019. He is a hard-working, intelligent, very cooperative with others and I rank him among my distinguished students, especially through my teaching courses , also the discussion of his Graduation Project. I recommend him, without any reservation, for any qualified engineering position, as well as for post-graduate study registration. View Reference.
Dr.Mohamed Abdelwahab Shahein
Helwan University
I wish to recommend Eng. Sharaawy; I have known Eng. Eslam for more than four years that he has been a student in our Department. Eng. Sharaawy has been a brilliant student throughout his five years of graduation. His diligence and hard work have always been appreciated by various faculties. Being among the top 3% student of our department, he pursued a number of different aspects when it comes to his education. His studies have never been a deterrent for him to participate in extracurricular activities and he has shown his hidden talents in fields like photography and learning foreign languages. It has been a wonderful experience having Eng. Sharaawy in my classes, as he is a hardworking and encouraging student. He actually works with other students to help and encourage them in their studies as well. I believe wholeheartedly that he is going to be the perfect candidate for your tasks and highly recommend him as so. View Reference.
Get In Touch
I love to hear from you. Whether you have a question or just want to chat about tech, Arts or anything interesting — shoot me a message.