👋 Hi! My name is Ričards Marcinkevičs. 🎓 Currently, I am a PhD student at the Institute for Machine Learning, Department of Computer Science, ETH Zurich. I am a Medical Data Science group member supervised by Prof. Dr. Julia E. Vogt and co-advised by Prof. Dr. Fanny Yang.
🤖 At the moment, I am broadly interested in interpretable and explainable machine learning. In particular, I would like to understand what are the inductive biases for neural networks that may render the model interpretable in specific use-cases and how such inductive biases may be incorporated into the model? Moreover, how can we leverage interpretations and explanations to obtain actionable insights about the data or the model itself, for instance, to perform scientific discovery or make our models fairer and more robust? From the application perspective, I work on time series and survival analysis and enjoy participating in interdisciplinary projects and leveraging ML methods to analyse biomedical data.
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