Charles Vin

Junior Research Engineer

Project Spotlight


  1. Research Internship - Self-supervised Learning on Satellite Image Time Series

    • Conducted extensive literature review on state-of-the-art methods in self-supervised learning (SSL) applied to Satellite Image Time Series (SITS).
    • Reproduced and benchmarked baseline models to ensure robust performance comparisons.
    • Developed and implemented an innovative image retrieval pretext task utilizing a specialized hierarchical loss function to train SSL models on SITS data.
    • Actively participated in research lab activities.
  2. Freelance - Frontend web developpement

    • Frontend development of an e-commerce website.
    • Implementation of a backend using Docker and creation of a CI/CD pipeline for the frontend.
    • Configuration of a mail server and a newsletter manager.
    • Effective communication with non-technical individuals to explain constraints and possibilities.
    • Project management within specific deadlines.
  3. Research project - Explainable insects classification

    • Development of a convolutional neural network for insect classification.
    • Use of gradient-based approaches and the LIME and SHAP frameworks.
    • Takeover, adaptation and documentation of the project.
    • Experiences monitoring and evaluation of different models with WandB.
  4. Intership - Signal Processing and Data Analysis

    • Processed raw EMG/ECG signals and AXCPT task data.
    • Employed data visualization techniques.
    • Utilized statistical tests to uncover group differences.
    • Delivered presentations and reports to communicate findings effectively.
  5. Temporary - SCALab Laboratory

    • Developed an algorithm to recommend sports categories to practice based on motivation profile, sport tolerance, and activity level.
    • Explored various approaches including Neural Networks (NN), K-Prototype, Discriminant Function Analysis (DFA) and XGBoost.
    • This contract marked my inaugural foray into the realm of Machine Learning.
    • Conducted some data visualization on the survey data.
    • Data were coming from approximately 2000 survey responses which included the following psychological test :
      • Physical Activity and Leisure Motivation Scale (PALMS): Discerne factors driving participation in sports, such as psychological factors or appearance.
      • Sport Tolerance (PRETIE-Q): Assesses the participant's ability to persevere in high-intensity physical activities, even when uncomfortable.
      • Activity Level (IPAC): Categorize participants as high or low activity level.
      • A comprehensive list of sports practised by each participant.
  6. Research Project - INRIA

    • Study of the trade-off between observation and action in reinforcement learning (subject details)
    • Understanded, independently, a cutting-edge problem in reinforcement learning.
    • Demonstrated perseverance and determination in the face of technical challenges.
    • Implemented an experimental plan.
  7. Temporary - SCALab Laboratory

    • Verification and validation of MATLAB code processing thermal camera data to ensure compliance with the researcher's requirements for publication.
    • Various computer-related tasks
  8. Intership - SCALab Laboratory

    • Assessed the reliability of a new model of eye-tracking glasses that were using machine learning.
    • Wrote a user manual for these glasses.
    • Data processing and visualization for other researchers on the platform.


  1. Master's Degree in Computer Science - Specialisation Data, Machine Learning, and Knowledge (DAC)

    Relevant courses:

    • Image and signal processing
    • Mathematics for ML (statistics/probability, Markov Chain, ...)
    • Databases: SQL, XML, JSON, distributed databases
    • Machine Learning: classification, neural networks, decision trees
    • Natural language processing, information retrieval
    • Opening courses from Master of Mathematics: statistical learning and convex optimization.
    Learn more
  2. Bachelor's degree, Mathematics and Computer Science applied to Cognitive Science

    Grade: Highest Honours

    Relevant courses:

    • Decision statistics: practical work in R.
    • Probability and measurement theory
    • Cognitive science

    Relevant academic projects:

    • Bayesien Tweet Classifier: "Positive" or "Negative" tweets classifier
    • Basic ML algorithm from scratch: KNN, KMean, linear/polynomial regression
    Learn more

My main sports



Last 4 weeks

13 km


67 min

Moving Time

Total Activities

Fetched using Strava API


Me & Cooking

Let me introduce my cooking philosophy throught a few key points

  • Passionate Home Cooking: I cook often at home, driven by a deep passion for creating incredible food.
  • Relaxed Approach: I don't sweat the small stuff. I'm all about enjoying the process and flavors, not stressing over perfection.
  • Feeding Loved Ones: I love cooking for my family and friends, and I believe there's nothing quite like a homemade meal to show you care.
  • Budget-Friendly Goodness: I'll show you how to make delicious meals that won't break the bank.


I drew my inspiration and passion from a multitude of talented YouTubers. Here's a curated list of some of the best who have played a significant role in shaping my culinary journey:

Plants & Gardening

I've always had a deep appreciation for nature, growing up in the countryside helps a lot. However, my passion for plants truly blossomed during a high school biology class when I witnessed chloroplasts moving under a microscope. Those tiny green organelles, brimming with life and releasing oxygen bubbles, captivated me.

My journey into the world of plants began in my high school years, largely influenced by YouTube. Over time, my interests expanded to gardening, agriculture, and eventually led me to explore "self-sufficiency" YouTubers. These individuals are dedicated to achieving energy and food self-sufficiency (without delving into extreme survivalism). It all intertwined with my fascination for culinary pursuits like making jams and preserving food.

My passion for music, particularly electronic music, ignited during my middle school years when I stumbled upon YouTube channels like MrSuicideSheep and Monstercat. From that moment on, I never stopped listening. I take pride in exploring the entire spectrum of electronic music.

If you're curious about what's currently playing in my world, I invite you to check out my profile, which aggregates my Soundcloud listens and gives you a glimpse into my musical journey.