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Mikaël Dusenne, Full-stack Developer in Rouen, France
Mikaël Dusenne

Full-stack Developer in Rouen, France

Member since April 26, 2022
Mikaël is a full-stack developer and data analyst with a doctorate in medicine and a master's degree in medical informatics. He focuses on medical informatics applied to data science and DevOps and freelances as a full-stack developer. Mikaël excels in working with data to create valuable and efficient interfaces. He maintains tight feedback loops with clients and remains motivated and cheerful as he works through challenges and opportunities.
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Portfolio

  • Rouen University Hospital
    Docker, Python, Vue, Natural Language Processing (NLP), BERT, Data Analysis...
  • BlackPool (Freelance)
    AWS Lambda, Vercel, Web3.js, APIs, Python, Vue, Docker, Blockchain, GraphQL...
  • Freelance
    Docker, Python, Vue, MongoDB, Front-end, Node.js, Amazon Web Services (AWS)...

Experience

Location

Rouen, France

Availability

Part-time

Preferred Environment

Linux, Amazon Web Services (AWS), Docker, Python, JavaScript, Vue, Git, Haskell, Web3.js, Scikit-learn

The most amazing...

...was enabling a client to stop emailing Excel files and switch to a web page using secure tools and a proper UI, greatly improving efficiency and attractivity.

Employment

  • MD and Biomedical Informatics Researcher

    2020 - PRESENT
    Rouen University Hospital
    • Performed NLP research in healthcare, consuming the Wikimedia API to augment medical thesaurus translations: https://mikaeldusenne.com/wikimesh.
    • Conducted research on using BERT NLP embeddings applications on medical documents and BERT on the hospital's clinical data warehouse.
    • Researched medical ontologies and data quality improvements by augmenting existing terminologies in the Medical Subject Headings (MeSH) thesaurus by adding translations from Wikipedia.
    • Developed the API consumer in Python, the demonstrator in Vue.js, and evaluated the performance and usability of the solution.
    Technologies: Docker, Python, Vue, Natural Language Processing (NLP), BERT, Data Analysis, APIs, Pandas, Big Data, Data Science, API Development, Flask, Web Development, Web Scraping, Jupyter, Data Analytics, TypeScript, REST APIs, SQLAlchemy, NoSQL, YAML, Python 3, Document Parsing, Scraping

  • Full-stack Developer

    2021 - 2022
    BlackPool (Freelance)
    • Developed a subdomain of the website related to the company's Sorare fantasy NFT football game. This involves ETL from an API and provides custom data analytics tools: https://sorare.blackpool.finance.
    • Queried a GraphQL API to obtain data related to the company using a serverless architecture. Used AWS Lambda and Scheduler to automatically feed the cloud-housed MongoDB database.
    • Displayed the raw data using Vue.js and a static website deployed via Vercel. Created custom aggregated reports to provide advanced analytics tools for statistical analysis and exploration to provide accurate insights.
    Technologies: AWS Lambda, Vercel, Web3.js, APIs, Python, Vue, Docker, Blockchain, GraphQL, Serverless Architecture, Front-end, React, Non-fungible Tokens (NFT), Amazon Web Services (AWS), CSS, HTML, Bootstrap, Responsive Web Design (RWD), Databases, Pandas, Big Data, Data Science, API Integration, API Development, Flask, Web Development, Next.js, Tailwind CSS, Lambda Functions, Data Analytics, TypeScript, REST APIs, NoSQL, YAML, Ajax, CSS Grid, Python 3, Document Parsing, Scraping, Amazon S3 (AWS S3)

  • Full-stack Developer

    2020 - 2021
    Freelance
    • Enabled my client to update his workflow and stop sending and receiving Excel files via email. Developed a complete website for my client and his clients.
    • Improved the client's UX and attractivity by replacing Excel-based questionnaires with a web platform featuring secure user authentication and a UI created with HTML with Vue.js.
    • Added a data processing pipeline, replacing Excel formulas with documented and debuggable Python scripts.
    • Increased productivity by automating processes, reduced errors by eliminating copy-paste, and added new functionalities that had been too hard to implement.
    • Improved the ease of use and user confidence by adding a secure payment module that allowed users to make purchases through the platform instead of making manual arrangements with my client.
    Technologies: Docker, Python, Vue, MongoDB, Front-end, Node.js, Amazon Web Services (AWS), CSS, HTML, Bootstrap, Responsive Web Design (RWD), Databases, NumPy, Pandas, API Integration, API Development, Flask, Web Development, Web Scraping, Lambda Functions, Jupyter, Data Analytics, TypeScript, REST APIs, SQLAlchemy, NoSQL, jQuery, YAML, Ajax, CSS Grid, Python 3, Document Parsing, Scraping, Amazon S3 (AWS S3)

  • Medical Resident | Medical Informatics Researcher

    2019 - 2020
    Rouen University Hospital
    • Explored the utilisability of an NLP neural network-based embedding technique for medical document classification. Published an article https://www.mikaeldusenne.com/article_ia_sante_export.pdf and presentation: https://www.mikaeldusenne.com/ias/.
    • Presented the research during a French national congress on artificial intelligence in healthcare.
    • Implemented Doc2Vec to generate an embedding representation of medical documents in the hospital's clinical data warehouse.
    • Used the embeddings to perform automatic classification of medical document types with great accuracy, improving the data quality in the clinical data warehouse.
    • Created a Vue.js interface to test the model, allow medical doctors to easily classify documents to doctors to evaluate the model's performance, and generate automatic reports.
    Technologies: Doc2Vec, Docker, Vue, Python, Word2Vec, Natural Language Processing (NLP), Plotly, Front-end, CSS, HTML, Bootstrap, Responsive Web Design (RWD), Databases, NumPy, PyTorch, Web Development, Web Scraping, Jupyter, Data Analytics, REST APIs, NoSQL, jQuery, YAML, Ajax, CSS Grid, Python 3

  • Medical Resident | Medical Informatics Researcher

    2018 - 2019
    Harvard Medical School, Avillach Lab at the Department of Biomedical Informatics
    • Analyzed a clinical registry to identify comorbidity associations in patients presenting with an orphan disease. Published an article written as a medical thesis: https://dumas.ccsd.cnrs.fr/dumas-03116249.
    • Explored machine learning techniques to answer the research question using an SQL database and R for analysis.
    • Used the department computer cluster with the Slurm job scheduler to perform parallelized computation.
    Technologies: Computer Science, Data Analysis, DevOps, Docker, R, Machine Learning, SQL, Slurm Workload Manager, Job Schedulers, Python 3, Document Parsing, Amazon S3 (AWS S3)

  • Back-end Developer

    2017 - 2019
    Inserm: National Institute of Health and Medical Research (Freelance)
    • Implemented the semantic interoperability module for the C3-Cloud project, a European project aiming to improve medical decisions for aging patients with multiple comorbidities.
    • Wrote a REST API in Python (Flask) with an SQLite database, exposing manually curated mappings between several medical terminologies compliant with the FHIR standard. Demonstrator: https://rubis.limics.upmc.fr/c3-cloud/#/.
    • Deployed Docker containers with a well-documented and reproducible deployment procedure, enabling easy integration with the other project components.
    • Collaborated with international teams developing other modules, provided a well-documented and flexible deployment process, and maintained good communication with the teams.
    Technologies: Docker, Python, Vue, Python 3

Experience

  • Analytics Tool for Sorare NFT Cards
    https://sorare.blackpool.finance

    A website to explore a company's owned assets, record the assets' characteristics, and provide interactive reporting and data aggregation tools to provide tailored data insights. The site provides interactive data exploration tools and interactive plots while respecting the company's desired look and feel by integrating its CSS and styling policy.

    The original data comes from the Sorare API (https://sorare.com). AWS Lambda automatically fetches new data from the API and feeds a cloud-hosted MongoDB instance. A Vue.js website is served statically and deployed by Vercel, consuming the MongoDB resources via a custom API deployed over Vercel Lambda (similarly to AWS Lambda).

    This project was initially deployed using a more common infrastructure on an Amazon EC2 server and a Docker Compose stack combining a Python Flask API behind an Nginx reverse proxy, a MongoDB database, and a Vue.js front end. The serverless deployment proved effective at reducing infrastructure costs.

Skills

  • Languages

    Python, JavaScript, CSS, HTML, Python 3, Haskell, R, TypeScript, YAML, SQL, GraphQL

  • Frameworks

    Flask, Bootstrap, Next.js, Tailwind CSS

  • Libraries/APIs

    Vue, REST APIs, Scikit-learn, Node.js, React, NumPy, Pandas, API Development, SQLAlchemy, jQuery, Web3.js, PyTorch

  • Tools

    Jupyter, Git, Doc2Vec, Plotly

  • Platforms

    Linux, Docker, Amazon Web Services (AWS), AWS Lambda, Blockchain

  • Other

    Medicine, Computer Science, SSH, Web Development, Web Scraping, Data Analytics, Document Parsing, Scraping, Data Analysis, Machine Learning, Natural Language Processing (NLP), APIs, Front-end, Big Data, Lambda Functions, Ajax, CSS Grid, Word2Vec, Slurm Workload Manager, Job Schedulers, BERT, Vercel, Serverless, Non-fungible Tokens (NFT), API Integration

  • Paradigms

    DevOps, Responsive Web Design (RWD), Data Science, Serverless Architecture

  • Storage

    MongoDB, Databases, NoSQL, Amazon S3 (AWS S3), MySQL

Education

  • Master's Degree in Medical Informatics
    2016 - 2018
    Paris XIII University and Harvard Medical School - Paris, France | Boston, MA, USA
  • Doctorate in Medicine
    2007 - 2016
    Lille University of Medicine - Lille, France

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