• 📓 PhD student in computer science, using AI to predict the onset of chronic diseases
• 🖥️ At work, I'm interested in: Managing Data Science projects, Teaching and Science Popularization, Object-Oriented Development, Data Science, and well-documented git repos ;)
• 🎨 At home, I'm interested in: Art (traditional and digital), Writing, Japanese Pop Culture, Video Games

Feel free to reach out if you want to discuss any of my projects, ask about my research, or just show off pictures of your cat 🐈

• 📫 Email: [email protected]
• 🔗 LinkedIn: Hadrien Salem

• A Python framework for the early prediction of diseases, which I actively work on for my PhD.
• An introduction course on data science, taught at École Centrale de Lille at master's degree level.
• A Discord bot to set alarms, a fun side-project I contributed to.

• 🌐 Languages
  • English (fluent)
  • French (native)
  • Japanese (self-taught beginner)
  • German (notions)
• ⌨️ Programming Languages
  • Python (incl. Data Science libraries and unit testing)
  • Kotlin (professional experience as Android Dev)
  • Java (used in school projects)
• 🛋️ Non-technical Skills
  • Teaching: taught for over 130 hours at master's degree level at École Centrale de Lille
  • Project management: led professional and student engineering projects using Agile frameworks (incl. Scrum)
  • Documentation and science writing: authored and co-authored 3 published papers in international journals and conferences
• 🖱️ Other tools
  • Git / GitHub (incl. GitHub Actions and GitHub Projects)
  • Photoshop & Clip Studio Paint
  • Notion, Jira, Clickup
  • Google suite (Docs / Slides / Sheets) and their MicroSoft equivalents
• ✍️ Currently Interested in Learning
  • Godot
  • Streamlit
  • Docker
  • Hosting apps on AWS

• Main research field: Artificial Intelligence for Predictive Analysis of Diseases from Biological Data
• Publications:
  • Predicting chronic kidney disease a year early with over 80% recall: Salem, H., Ben Othman, S., Broucqsault, M. and Hammadi, S., 2024, June. Combining Convolution and Involution for the Early Prediction of Chronic Kidney Disease. In International Conference on Computational Science (pp. 255-269). Cham: Springer Nature Switzerland.
  • Helping with the screening of prostate cancer without the use of a dedicated biomarker: Salem, H., Ben Othman, S., Broucqsault, M. and Hammadi, S., Using Machine Learning to Support Prostate Cancer Detection without a Dedicated Biomarker, presented in August 2024 at IEEE CASE 2024 (not yet available online)
  • Dynamic system for vehicle routing: Tresca, G., Salem, H., Cavone, G., Zgaya-Biau, H., Ben-Othman, S., Hammadi, S. and Dotoli, M., 2024. A Matheuristic Approach for Delivery Planning and Dynamic Vehicle Routing in Logistics 4.0. IEEE Transactions on Automation Science and Engineering.