Mikaël Dusenne, Developer in Rouen, France
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Mikaël Dusenne

Verified Expert  in Engineering

Full-stack Developer

Location
Rouen, France
Toptal 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.

Portfolio

Rouen University Hospital
Docker, Python, Vue, Generative Pre-trained Transformers (GPT)...
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

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.

Work Experience

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), GPT, Generative Pre-trained Transformers (GPT), 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, Generative Pre-trained Transformers (GPT), GPT, 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

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.

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, Vercel, 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, GPT, Generative Pre-trained Transformers (GPT), Word2Vec, Slurm Workload Manager, Job Schedulers, BERT, 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

2016 - 2018

Master's Degree in Medical Informatics

Paris XIII University and Harvard Medical School - Paris, France | Boston, MA, USA

2007 - 2016

Doctorate in Medicine

Lille University of Medicine - Lille, France

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