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Alex MakogonAM

Alex Makogon

Computer Vision/Artificial Intelligence Consultant

700 €/jour
Paris, FR
3-7 ans

Délai de réponse moyen : 1h

À propos de Alex

I help businesses automate inspections and analyze images with AI — fast, practical, and results-driven.

I’m a PhD in Materials Science & Data Science, specialized in computer vision and generative AI for industrial applications. I help SMEs and R&D teams turn manual visual inspections, lab images, or technical photos into actionable insights — saving time, reducing errors, and enabling smarter decisions.

What I bring to the table:

- Expertise in computer vision for quality control, corrosion detection, and materials analysis.

- Hands-on experience creating AI prototypes that work with real industrial data.

- Rapid delivery: working models, scripts, or interactive demos in 1–3 weeks.

- Guidance to scale prototypes into production-ready tools.

Typical projects / deliverables I handle:

- Detecting and grading corrosion, defects, or surface anomalies from images.

- Automated visual inspection pipelines for lab or production environments.

- AI-assisted analysis of microscopy or industrial imaging data.

- Retrieval-augmented assistants to help teams query visual or technical data quickly.

Proof-of-concept AI models that demonstrate ROI in days.

If your team spends hours on manual inspection or image analysis, I can deliver a working AI solution in days — no vendor lock-in, just tangible results.
  • Anglais

    Bilingue ou natif

  • Français

    Notions

  • Russe

    Bilingue ou natif

Accepte de travailler sur site
Paris (jusqu’à 50 km)

Expériences

  • Centre National de la Recherche Scientifique (CNRS),
    Doctoral Researcher — Machine Learning & Computer Vision
    février 2023 - décembre 2025 (2 ans et 10 mois)
    Paris, France
    • Developed computer vision and ML pipelines for automated corrosion and asset integrity analysis
    • Applied data-driven modeling to experimental materials science for reproducible ML based assessment
    • Integrated ML models into real experimental workflows considering data quality, physical constraints, and interpretability
    • Collaborated across disciplines, translating domain problems into deployable ML solutions
    • Research interests: explainable AI, scientific ML, vision-based analysis of physical pro cesses
    Computer Vision Data science Machine learning Anomaly Detection Python
  • NEW EIG
    Data Scientist / Quantitative Researcher
    août 2023 - décembre 2024 (1 an et 4 mois)
    • Designed and validated statistical and ML models for risk and probability estimation in financial systems
    • Handled high-noise, real-world data with robust validation and uncertainty quantification
    • Translated business and risk requirements into quantitative ML solutions for decision making
    • Operated across full ML lifecycle: data analysis, model building, evaluation
  • ICS RAS — Institute of Computational Sciences
    Research Engineer — Scientific Computing & Modeling
    octobre 2018 - février 2023 (4 ans et 4 mois)
    Saint Petersburg, Russie
    • Conducted full-cycle computational research in mathematical physics and applied model ing
    • Built custom numerical simulation and data analysis pipelines
    • Authored 10+ peer-reviewed scientific publications and presented internationally
    • Worked at the intersection of theory, computation, and data analysis

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Formations

  • PhD, Materials Science & Machine
    Universit ´ e Paris Cit
    2026
    PhD, Materials Science & Machine
  • MSc, Financial Engineering /
    WorldQuant University
    2022
    MSc, Financial Engineering /

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