[Proof Complexity] Caleidoscope Complexity School: Call for Participation

Thomas Seiller seiller at lipn.fr
Thu Feb 6 14:50:08 CET 2020

*** Call for participation ***

Caleidoscope: Research School in Computational Complexity

Paris, 15-19 June 2020


Dear all,

We are delighted to announce the second edition of the Caleidoscope Research School in Computational Complexity, to take place in Paris, 15-19 June 2020. The school is aimed at graduate students and researchers who already work in some aspects of computational complexity and/or who would like to learn about the various approaches.


Computational complexity theory was born more than 50 years ago when researchers started asking themselves what could be computed efficiently. Classifying problems/functions with respect to the amount of resources (e.g. time and/or space) needed to solve/compute them turned out to be an extremely difficult question. This has led researchers to develop a remarkable variety of approaches, employing different mathematical methods and theories.

The future development of complexity theory will require a subtle understanding of the similarities, differences and limitations of the many current approaches. In fact, even though these study the same phenomenon, they are developed today within disjoint communities, with little or no communication between them (algorithms, logic, programming theory, algebra...). This dispersion is unfortunate since it hinders the development of hybrid methods and more generally the advancement of computational complexity as a whole.

The goal (and peculiarity) of the Caleidoscope school is to reunite in a single event as many different takes on computational complexity as can reasonably be fit in one week.  It is intended for graduate students as well as established researchers who wish to learn more about neighbouring areas.


1. Algorithms and lower bounds. Lecturer: Ryan Williams, MIT.
2. Hardness of Approximation. Lecturer: Luca Trevisan, Bocconi University.
3. Higher-Order Complexity. Lecturer: Bruce Kapron, University of Victoria.
4. Parametrized Complexity. Lecturer: Daniel Marx, Max Planck Institute Saarbrucken.

In addition to these broad-ranging themes, there will also be three tutorials on more focussed topics.

5. Quantum Computation and Complexity. Lecturer: Elham Kashefi, CNRS and Sorbonne University.
6. Static Complexity Analysis. Lecturer: Georg Moser, University of Innsbruck.
7. Complexity Theory for Black-Box Optimization Heuristics. Lecturer: Carola Doerr, CNRS and Sorbonne University.


Registration to the school is free but mandatory. This is to help us plan tea/coffee breaks and social activities.



There may be opportunities for financial support for participants. We will make relevant information available via the webpage.

Damiano Mazza — CNRS & Université Sorbonne Paris Nord
Sylvain Perifel — Université Paris 7
Thomas Seiller — CNRS & Université Sorbonne Paris Nord


European Mathematical Society (EMS)
DIM RFSI - Région Île-de-France (https://dim-rfsi.fr/)
CNRS (https://www.cnrs.fr/en)
Université Sorbonne Paris Nord (https://www.univ-paris13.fr/en/)
Laboratoire d'Informatique de Paris Nord (https://lipn.univ-paris13.fr/)
Université Paris 7 (https://www.univ-paris-diderot.fr)
Institut de Recherche en Informatique Fondamentale (https://www.irif.fr/en/index)

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