About 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.
English
Native or bilingual
French
Basic
Russian
Native or bilingual
Can work on-site
Paris (up to 50km)
Experience
- Centre National de la Recherche Scientifique (CNRS),Doctoral Researcher — Machine Learning & Computer VisionFebruary 2023 - December 2025 (2 years and 10 months)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
- NEW EIGData Scientist / Quantitative ResearcherAugust 2023 - December 2024 (1 year and 4 months)• 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 SciencesResearch Engineer — Scientific Computing & ModelingOctober 2018 - February 2023 (4 years and 4 months)Saint Petersburg, Russia• 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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Education
- PhD, Materials Science & MachineUniversit ´ e Paris Cit2026PhD, Materials Science & Machine
- MSc, Financial Engineering /WorldQuant University2022MSc, Financial Engineering /