Youssef Karouma
DATASCIENTIST/AI ENGINEER
Lyon
Summary
Recent graduate engineer from école Centrale de Lyon, with foundational knowledge in applied mathematics and computer science, and hands-on experience gained through academic projects and internships. Demonstrates strong teamwork, problem-solving, and time-management skills. Prepared to start career and make meaningful contributions with commitment and drive.
Overview
2025
2025
years of professional experience
5
5
years of post-secondary education
3
3
Languages
Work History
Final-Year Internship : Datascientist Intern
STMicroelectronics
4 2024 - 9 2024
- Development of a generative AI to automate a machine code generation. This code is used to validate electronic chips design.
- Detection of anomalies in the generated machine code and error correction.
- Deployment of the AI on a large scale, using MLflow and streamlit, with the generative part pluged with the corrective part, which allowed to save 80% of the time of the industrial process.
Research Internship in Computer Vision/Deep Learning
CNRS
5 2023 - 7 2023
- Collection and analysis of images and videos containing humans in motion.
- Implementation of Deep Learning algorithms for 3D reconstruction of the human body during movement, such as densepose estimation.
- Enhance the performance of algorithms by 3D data-augmentation, using Blender.
- Achievement of 85% in accuracy of human body reconstruction.
Application Project : Develop a School ChatBot
Ecole Centrale de Lyon
01.2024 - 03.2024
- Data collection and cleaning on school fee regulations (QA, PDF documents, FAQs).
- Fine-tuning of LLMs on tasks such as sentiment analysis and question answering.
- Utilization of RAG (Retrieval-Augmented Generation) techniques to extract answers for students questions, from PDF documents.
- Achievement of 5 as a score in the CSAT (Customer Satisfaction Score), which is the best score to achieve for a chatBot.
Research School Project
FFTT (French Table Tennis Federation)
09.2022 - 04.2023
- Participated in regular status meetings with the French Table Tennis Federation (FFTT), providing updates on the development of deep learning models (YOLOv5, YOLOv8) for ball tracking and detection, and addressing any technical concerns or questions from team members.
- Conducted comprehensive literature reviews on advanced computer vision techniques, contributing valuable insights for optimizing the analysis of table tennis performance data.
- Improved experimental design for data analysis and model performance by continuously refining ball tracking algorithms based on collected feedback and iterative testing. Achievement of 80% in accuracy of ball detection.
- Applied critical thinking skills to troubleshoot technical challenges in computer vision and deep learning, resulting in enhanced model accuracy and system performance, directly supporting French athletes’ preparation strategies for the 2024 Olympic Games.
Education
Master of Science - Computer Science-Data Science
Université Lyon I
Lyon, France 04.2023 - 01.2024
Master of Science - Machine Learning, Statistical Analysis
Ecole Centrale De Lyon
Ecully, France 04.2021 - 01.2024
High School Diploma -
Lycée D'excellence De Benguerir Maroc
Ben Guerir, Morocco 04.2019 - 01.2021
Skills
Statistical analysis
Primary Assets
- Strong sense of initiative
- Perseverance
- Collaborative mindset
- Adaptability
Accomplishments
Own the 3rd price in Challenge sciences 2024, a prestigious competition for innovative engineering projects in France.
Timeline
Application Project : Develop a School ChatBot
Ecole Centrale de Lyon
01.2024 - 03.2024
Master of Science - Computer Science-Data Science
Université Lyon I
04.2023 - 01.2024
Research School Project
FFTT (French Table Tennis Federation)
09.2022 - 04.2023
Master of Science - Machine Learning, Statistical Analysis
Ecole Centrale De Lyon
04.2021 - 01.2024
High School Diploma -
Lycée D'excellence De Benguerir Maroc
04.2019 - 01.2021
Final-Year Internship : Datascientist Intern
STMicroelectronics
4 2024 - 9 2024
Research Internship in Computer Vision/Deep Learning
CNRS
5 2023 - 7 2023
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