Daniel Kaiser

MSc student, Machine Learning Research Group

Daniels research focusses on the application of Deep Learning to bridge fundamental and market valuations of firms, modelling market events via reinforcement learning, and using unsupervised Machine Learning methods to solve data quality problems such as missing value imputation. He researches for a MSc under the supervision of Dr. Jan-Peter Callies, Prof. Stephen Roberts, and Ass. Prof. Amir Amel-Zadeh. Prior to joining OMI, Daniel studied Econometrics at the Vienna University for Business and Economics, conducting research on the effect of public filings via EDGAR on equity markets.