Armel SOUBEIGA

Armel SOUBEIGA

PhD student in Machine Learning

About

After more than three years in the industry as a data scientist and over a year as a data consultant at the World Bank, I am now completing my PhD in Machine Learning at the University of Clermont Auvergne doctoral school of Engineering Sciences, in collaboration with LIMOS and Simon Fraser University (SFU). I am fortunate to be supervised by Jonas KOKO, Violaine ANTOINE, and Sylvain MORENO.

My research explores Machine Learning with a strong focus on unsupervised learning. I am particularly interested in developing new clustering approaches, including evidential clustering, relational clustering, and multi-view or collaborative relational clustering. My work addresses challenges in analyzing complex real-world data, as longitudinal data, time series and uncertain data, aiming to develop robust and interpretable models.

Research interests:

  • Machine Learning for time series, and Uncertain data for trajectories analysis
  • Explainable Machine Learning and applications in real-world data
  • Big data analysis
  • Web scraping/scrawling and NLP
  • MLOps, and Interactive data visualisation for software engineering
  • Statistical computing and Exploratory data analysis

Here, take a look at my stuff

  • 👨‍💻 I am proficient in Python, R, and SQL
  • ✨ I like TensorFlow, PyTorch, Scikit-Learn, Keras, Rshiny, Django, Flask frameworks
  • 📚 I wrote web scraping with R, and I actively contribute to open source software.

Python R SQL SAS C++ Git


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