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Ibrahim AyedIA

Ibrahim Ayed

data scientist, deep learning researcher

€1,000/day
2 projects
Paris, FR
3-7 years
Machine learning
Data science
Deep Learning
Technical writing
Pytorch

Average response time: 1 hour

Freelancer profile translated to English.
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About Ibrahim

After joining the École polytechnique, specializing in applied mathematics, I then improved my skills within the Master 2 Mathematics, Vision, Learning (MVA) at ENS Cachan.

I am currently a doctoral student at Sorbonne Université with Mr. Patrick Gallinari on topics related to Deep Learning, with several presentations and publications at national and international conferences. I have also already worked on projects with diverse subjects: finance (with Mr. Emmanuel Bacry in particular), geophysical data (at the University of Cambridge), image processing,...

I can help you to:
-Analyze your problem and guide you towards the right technological choices
-Prototype Machine Learning models
-Build and train Neural Network models (CNNs, ResNets, GANs, LSTMs,...)
-Implement Neural Network models (Pytorch)
-Train your teams on these different technologies
-Train your teams on best practices in Data Science

  • French

    Native or bilingual

  • Arabic

    Native or bilingual

  • Japanese

    Basic

  • English

    Fluent

  • Spanish

    Fluent

  • Italian

    Conversational

Can work on-site
Paris (up to 50km)

Experience

  • Sorbonne Université
    AI Researcher (PhD student)
    RESEARCH
    April 2018 - Today (8 years and 2 months)
    Paris, France
    AI models for complex systems:
    -Development of a state-of-the-art model for predicting complex dynamics
    -Applications to geophysical sciences, the medical field, fluid dynamics,...
    -Publications accepted at national and international conferences
    Machine learning Pytorch Python
  • Societe Generale SA
    Long project in applied mathematics
    BANKING AND INSURANCE
    October 2015 - May 2016 (8 months)
    Paris, France
    Design and analysis of automated trading strategies from financial time series:
    -Definition of strategies
    -Systematic study and back-testing
    -Parameter optimization
    Python Optimization Time series
  • Schlumberger Gould Research Center / University of Cambridge
    Applied Mathematics Researcher (intern)
    ENERGY AND UTILITIES
    April 2017 - August 2017 (4 months)
    Cambridge, United Kingdom
    Design and development of a seismic model learning program:
    -Mathematical modeling
    -Solving a highly non-convex optimization problem
    -Implementation (Python) from scratch
    Python Machine learning Non-convex Optimization

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Education

  • Diploma of École polytechnique
    École polytechnique
    2018
    Mathématiques, Mathématiques appliquées, Informatique, Économie, Physique
  • Master 2 Mathematics, Vision, Learning
    École Normale Supérieure Paris-Saclay
    2018
    Deep Learning, Kernel Methods, Optimization, Computer Vision, Online learning, Reinforcement Learning

Skill set

Python
Scikit-learn
NLP
Data mining
Pandas
Data analysis
Keras
C++
Text mining
Statistics
Jupyter
Optimization
Time series
Non-convex Optimization

Categories