Problem Solver
Bart J.S.W. Smeets 
Proven Solver
Areas Bart J.S.W. Smeets is Knowledgeable in:
Healthcare (hospitals, patient care processes, outcome analysis, costing analysis) and finance (settlements)
Techniques Bart J.S.W. Smeets Uses:
(non-)linear optimization, discrete-event simulation, monte carlo simulation, regression / classification algorithms (random forests, gradient boosting, ...), visual interface building skills (e.g. HTML5)
Bart J.S.W. Smeets's Problem Solving Experience:
- - I am the co-author of simmer, the only discrete event simulation package for R
- I worked on multiple (quantitative) process optimisation projects in the University Hospital of Leuven
- I have a strong knowledge on machine learning techniques, focussing on classification and regression, with an practical expertise in healthcare and finance