For my up-to-date resumé, see: https://cjvanlissa.github.io/resume/
My research revolves around three themes: The “theory crisis” in social sciences, cumulative knowledge acquisition, and reliability of research findings. My primary veni-funded research line uses machine learning for rigorous exploration, and uses the resulting data-driven insights to complement blind spots in theory. My secondary research line focuses on evidence synthesis: Summarizing existing knowledge, e.g. through systematic reviews and meta-analysis. Specifically, I develop machine learning methods to account for heterogeneity in meta-analysis and to qualitatively summarize published literature. My third research line revolves around open science, in particular computational reproducibility. As statistical co-author, I support research in many societally relevant areas.
The choice for an academic career was partly motivated by my passion for teaching. Since I had the opportunity to teach workgroups in my bachelor's degree (2007), I have continuously taught students with diverse background knowledge and motivation: from talent education for highschool students to summer schools for colleagues and evening classes for professionals. I take students seriously and focus on interactivity in my lectures; for example, by using a "flipped classroom": Students watch my lectures on YouTube, and lecture time is used for in-depth discussion and follow-up questions. I received the 2021 "Teacher of the year" award from USocia. I invest in educational innovation, particularly with regard to open science education, problem-based learning, and constructive alignment.
I strongly value collaboration. If you have an idea you want to discuss, please contact me for a meeting. For my ongoing collaborations, see my online resume.