Daniel Schmidt

Background

About Daniel Schmidt

I have over 20 years experience worked in the field of statistics and machine learning. My particular interests are the Bayesian approach to statistics. I am also engaged in research in the areas of time series (forecasting, classification), information theoretic machine learning and statistical genomics. I am strongly committed to teaching in both academia and industry. I believe it is important to pass on the knowledge I have accumulated to the next generation of data scientists; as such I currently lecture in data science units at Monash University and mentor a number of honours and postgraduate students. I have extensive experience in the development and application of novel statistical methodology and machine learning tools. I have written a number of statistical/machine learning packages which have been used these in the analysis of time series/genetic/medical/biological data. Expertise- Machine learning, high dimensional statistics, prediction - Bayesian statistics, MCMC, information theory - Time series analysis, signal processing - Programming: MATLAB, C++, R