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Summer School 2026 Nice · 7–9 September

About

About the Summer School

The Summer School on Data and Algorithms for Science, Technology & Innovation Studies is an annual gathering for researchers working with large-scale data on science and innovation.

About STI

The school started in Leuven as a small, low-pressure event run by a handful of PhD students. The idea was simple: get together to learn from each other and from experts about what is going on with patent and publication data — what it can do, where the pitfalls are, and how to leverage these types of data for research purposes. Informal by design, with the pizza-truck dinner that veterans may still remember.

As it turned out, there was genuine interest beyond PhD students, especially from the data providers and other practitioners who were curious to know their academic users better. The school grew into a small conference. Still today, we deliberately keep it informal and small, sticking to a single track: the topic is sufficiently homogeneous for everyone to benefit from seeing everything, and informal exchange is much easier when nobody has to choose between rooms.

We have been fortunate that leading scholars in the community keep supporting the school with their keynotes, comments, and presence — bridging the data and methods that we work on with the substantive contributions that our field wants to make. That, after all, is the point: better metrics and better algorithms should help our field answer better questions and make stronger contributions to the literature. We are always open to input from participants on how to stick to this objective; reach out anytime.

Why join?

  • Learn state-of-the-art methods. Keynotes and practitioner sessions take you to the current frontier of what data and algorithms can — and cannot — do for ST&I research.
  • Present and discuss your work. Pitches and full presentations cover work at any stage, including early-stage ideas. The conversation continues over coffee, dinner, and on the beach.
  • Connect with the community. PhD students, postdocs, and senior scholars working with the same data and questions. You will find that the community knows much more than what a Google search or an LLM prompt will tell you.
  • Have fun nerding out. Few of us get to discuss the intricacies of patent data at length around our kitchen tables or at family dinners. Three days at Valrose make up for this.

Who should attend?

Researchers at any career stage working with data on science, technology, and innovation — PhD students, postdocs, faculty, senior scholars — plus practitioners and representatives from organizations that produce or rely on ST&I data.

You are welcome to attend, whether or not you present. See the Call for Papers for submission details, or head straight to registration.

Past editions