Markus is a PhD Student at UCL and an Enrichment Student at The Alan
Markus’ research is on supervised learning with time-series/panel data, i.e. observations on multiple independent individuals (e.g. customers, patients or machines) collected repeatedly over time. In particular, his goals are to
- Create a practical, consistent and statistically solid workflow for modelling and evaluating supervised learning strategies with time-series/panel data,
- Design and implement an open-source Python toolbox that allows to put the workflow into practice,
- Develop probabilistic supervised learning methods based on point process models for panel data containing sequences of events with exact timestamps rather than regular time-series.
He is inspired by software development projects like scikit-learn, a popular machine learning toolbox in Python which not only makes supervised learning methods widely available but also easily understandable through an intuitive and consistent API design.
Moreover, his research involves a number of real-world datasets through ongoing industry collaborations, including the loyalty-card data from a UK high-street retailer (via the Consumer Data Research Centre), the fitness-training data from a supplier of cloud-connected gym equipment, and the biochemical data from a pharmaceutical company.