Ansgar Boss Henrichsen
Ph.d. Fellow
Om
In the current world with a growing use of and demand for machine learning models I try to increase both transparency and control of these models through the use of traditional means such as statistics and mathematical optimization.
With my research I address the need for greater transparency and understanding of machine learning models and operational research. With the availability of vast amounts of data and computational power machine learning models become more complex and opaque, while on the other hand, the use and implementation of these models becomes more common. I attempt to address this gap by proposing and modifying current machine learning models to increase transparency, control and help stakeholders challenge obstacles such as the lack of transparency in the decision-making process, tackle biases imposed by unregulated machine learning models, among other challenges.
In addition to this, I combine the field of operational research and machine learning to investigate how the mathematical optimization approaches of operational research and more direct control of these approaches can be used to complement the field of machine learning, as well as vice versa, how machine learning can complement the field of operational research.
The research I do is relevant for researchers and companies in the private as well as public sector.
Outside activities
, - ongoing
Helping out and assisting at the EURO online seminar series of the operational research society