Marthinus Christoffel (Christo) du Plessis
Assistant Professor, University of Tokyo

Education

Bachelor, Bachelor (Hons), cum laude

• Computer Engineering
• University of Pretoria
• Best software engineering project

Master of Engineering, cum laude

• Computer Engineering
• University of Pretoria
• Thesis title: “Non-stationary signal classification for radar transmitter identification”
• Supervisor: prof. J.C. Olivier

Doctor of Engineering

• Computer Science (Machine learning)
• Thesis title: “Learning under Class-Balance Change:  Distribution Matching via Direct Divergence Estimation”
• Supervisor: prof. M. Sugiyama

Work Experience

The University of Tokyo, Assistant Professor

• 2014.4 – current
• Research in machine learning
• Implementation of algorithms in C/C++ and Python

The University of Tokyo, Post-doctoral researcher
Tokyo Institute of Technology, Post-doctoral researcher

• 2013.4 – 2013.9 (Tokyo Inst. Tech), 2013.10 – 2013.3 (UTokyo)
• Research in machine learning (several papers at ICML/NIPS)
• Implementation of algorithms in C/C++ and Python

Skills and competencies

• Strong mathematics and statistics foundation
• Data visualization experience with a variety of packages (MATLAB, Matplotlib toolkit)
• Skilled in data manipulation
• Excellent knowledge of machine learning methods for high-dimensional dataset analysis (dimensionality reduction, feature selection, sparsity inducing regularization, etc…)
• Experience in application of high-volume learning methods and development of new methods (see my online learning publications)
  In-depth knowledge of a wide variety of data analysis methods:
  • Cluster analysis (k-means, spectral clustering, etc…)
  • Classification (SVM, neural networks, logistic regression, boosted decision trees, etc…)
  • Regression analysis (least-squares, Huber loss, SVR, etc…)
  • Anomaly/outlier detection (1-class SVM, SVDD, PU learning)
• Programming languages: Python (numpy/scipy, scikit), Matlab/Octave, C++
• Databases: SQL (MySQL)