Sreejita has a Bachelors (IN) and Masters (NL) in Biomedical Engineering. She transitioned to intrinsically interpretable Machine Learning for her PhD (Bernoulli Institute, University of Groningen). She is interested in interdisciplinary research involving machine learning and statistics to help in improving and better understanding of complex issues in healthcare and public health. During her postdoc she will be using ML and statistical methods, especially causal inference and counterfactuals to identify and evaluate risk factors, and look for possible feasible solutions from a data-driven manner.
The environment we live in has a dominant impact on our health. It explains an estimated seventy percent of the chronic disease burden. Where we live, what we eat, how much we exercise, the air we breathe and whom we associate with; all of these environmental factors play a role. The combination of these factors over the life course is called the exposome. There is general (scientific) consensus that understanding more about the exposome will help explain the current burden of disease and that it provides entry points for prevention and ...
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