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PhD Course on "Robust and Reproducible Research"
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The number of scientific articles published in Computer Science (and similar fields) increases steadily every year. This is mainly due to breakthroughs like Deep Learning, and, more recently, Large Language Models.
Paradoxically, researchers are struggling even more to reproduce published research. This issue affects all possible aspects of research, including methodology, data curation, approach comparison, and implementation.
In this course, we'll introduce and discuss the concept of 'reproducibility' in research. In particular, we'll overview current issues in research and existing attempts to address them. We'll focus on data curation, experimental setup, model comparison, and programming best practices.
This course is recommended for all types of researchers, from those who have just embarked on their journey to those who have always wondered how certain research managed to get published. See Section Prerequisites for more details.
