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Benjamin G.BG

Benjamin G.

Rust Blockchain Developer, Polkadot Ecosystem

€450/day
Paris, FR
3-7 years

Average response time: 1 hour

About Benjamin

I’m Benjamin Gallois, a versatile developer with a Ph.D. in Physics who specializes in Blockchain, Computer Vision, and Data Analysis. My interdisciplinary expertise allows me to craft innovative, high-quality solutions across these cutting-edge fields. Whether building robust blockchain applications or developing advanced computer vision systems, I thrive on solving complex problems and delivering tailored solutions that drive meaningful results.

My career began in AI and computer vision, where I developed advanced algorithms, but I soon became fascinated by the rapidly emerging world of blockchain and Web3 technologies. This passion led me to focus on the Polkadot ecosystem, where I now specialize in the Substrate framework and Polkadot-SDK, developing efficient blockchain node implementations and building decentralized solutions.

With a unique blend of AI, computer vision, and blockchain development expertise, I bring a creative, interdisciplinary approach to problem-solving. My work spans various industries, from enterprise-level blockchain applications to research-driven AI solutions. I help clients build custom blockchain infrastructures and optimize data-driven systems.

Whether you need scalable blockchain solutions or insightful computer vision models, I’m here to help your projects thrive. Let’s discuss how I can leverage my skills to bring your vision to life and drive innovation within your team or business.
  • French

    Native or bilingual

  • English

    Fluent

Remote only
Primarily works remotely

Experience

  • Sorbonne université
    PHD Student
    RESEARCH
    October 2017 - March 2021 (3 years and 5 months)
    Paris, France
    My PhD research was a unique blend of neuroscience and physics, focusing on the chemical perception of young zebrafish. This interdisciplinary project, conducted in a physics laboratory, the laboratoire Jean Perrin, with Raphaël Candelier, is detailed in my thesis (English).

    Over these four years, I taught myself numerous skills, ranging from workshop tools (mechanical, electronic, CAD, and 3D printing) to designing and building complete experimental setups, as well as the latest computer vision algorithms and statistical analysis methods. I also developed GUI programs to interact with these experimental setups, integrating multiple sensor inputs and control modules. This part of my PhD taught me much about low-level programming, deploying software for non-technical users, and, more importantly, how to teach myself new skills.

    Another significant aspect of this project was realizing that many researchers in this field lacked computer skills and struggled to analyze their experiments. They often relied on small, "time-tested" opaque pieces code. To address this issue, I started FastTrack, a complete GUI tracking software that is performant, versatile, and easy to install.

    At that time, deep learning detection was emerging, but it was not easily accessible for non-technical users, and the tracking part was mainly specific to the tracked objects. Throughout my PhD, I developed complete tracking software that can be used on any computer to track any type of object, as well as several libraries and tools for data analysis.

    This part of the project significantly enhanced my computing skills and exposed me to industry standards in computer programming. FastTrack, the software I initiated, is still actively maintained and has garnered close to 100 stars on GitHub. It has also been widely used and cited in numerous research papers.
    Computer Vision Analyse de données Développement logiciel OpenCV Qt Python C++ Pandas Scipy Numpy Seaborn Matplotlib Arduino Raspberry Pi Mécanique des fluides Ingénierie mécanique Electronique
  • Institut Curie
    Master Research Intern
    RESEARCH
    January 2017 - July 2017 (6 months)
    Paris, France
    Six months of this year were dedicated to a research project I conducted at the Curie Institute in the lab of Emmanuel Farge, under the supervision of Tatiana Merle, a PhD student at the time. The project focused on the mechanical induction of the β-catenin pathway in Nematostella vectensis embryos. We prepared and observed Nematostella vectensis embryos at the gastrula stage under different mechanical constraints, using confocal microscopy to investigate the mechano-induction of mesoderm differentiation.

    My primary contribution involved developing an image analysis pipeline to process 3D images of the embryos and quantify β-catenin expression. The details of this work are in m2.pdf (English). This research laid the groundwork for a more detailed analysis, which was further developed after I departed from the lab. Tatiana Merle’s PhD thesis describes the continuation of this work, which culminated in its application in a study published in Frontiers in Cell and Developmental Biology.
    Analyse de données Computer Vision OpenCv Python Optique Biologie moléculaire
  • Université Paris Diderot
    Master Research Intern
    RESEARCH
    June 2016 - August 2016 (2 months)
    Paris, France
    A project at the MSC Laboratory with Vincent Fleury, where I studied the vascular properties of chick embryos and tested a potential cancer treatment.

    This project had two main components: preparing chick embryos to observe the vascular system of the chorioallantoic membrane and developing experimental setups and image analysis tools to quantify its hemodynamics. The detailed work can be found in m1.pdf (in French).

    The second part of the project involved testing a novel cancer treatment drug in collaboration with Antonio Claudio Tedesco from the University of São Paulo, who was visiting the lab at the time. I was responsible for inducing tumor growth on the chorioallantoic membrane of chick embryos and applying the treatment to study its influence on hemodynamics and quantify its impact. This work was later published as Sophie Richard, Amanda Brun, Antonio Tedesco, Benjamin Gallois, Naoual Taghi, Philippe Dantan, Johanne Seguin, and Vincent Fleury. "Direct Imaging of Capillaries Reveals the Mechanism of Arteriovenous Interlacing in the Chick Chorioallantoic Membrane." Communications Biology, 1(1):235, 2018.
    Computer Vision Mécanique des fluides Ingénierie mécanique

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Education

  • Doctor's Degree, Physics
    Sorbonne université
    2021
    Doctor's Degree, Physics
  • Doctor of Philosophy
    Sorbonne université
    2020
    Doctor of Philosophy - PhD, Physics

Skill set

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