About me

I am currently doing my postdoctoral research in IMPT project on improving parameterizations of gravity wave momentum fluxes in climate models, using statistical and machine learning methods, under supervision of Aurélie Fischer (LPSM - Université Paris Cité) and Riwal Plougonven (LMD/IPSL - École polytechnique). I am from Cambodia.

I did my Ph.D. in Applied Mathematics at UPMC - Sorbonne Université under supervision of Mathilde Mougeot and Aurélie Fischer. I also worked as a teaching assistant at UFR mathematics of Université de Paris (Paris 7) during my thesis.

Here are my Ph.D. Thesis and Slides.

Research interests

My Ph.D. research focuses on consensual aggregation techniques for combining a given number (small or large) of predictors in supervised machine learning problems. Moreover, I developed a methodology (KFC-procedure) for constructing predictions using both supervised and unsupervised machine learning methods including consensual aggregation methods and clustering. I provide theoretical contributions and applications of the methods on several simulated and real (energy) data.

I am interested in the following topics:

  • Combination of unsupervised and supervised machine learning methods, ensemble learning, clustering and aggregation methods.
  • Deep learning, neural networks, artificial intelligence, online learning, big data…

Teaching (Université Paris Cité)

  • M2MO : TD of Statistical Modeling.
  • M1ISIFAR : TP R-programming of Data Analysis.
  • M2ISIFAR : TP R-programming of Data Mining.
  • M1MIDS : TP R-programming of Exploratory Data Analysis.
  • L3 Info : TP of Algorithm and programming in Python.
  • M1 Math-Info : TP of Big data technology with Spark and Python.