Laurent Simon

Full Professor (Bordeaux INP / Univ. Bordeaux / LaBRI)
(Professional page)

Most recent news

(list of all news)

Three Internships + PhD Opportunities in AI !

(09 November 2022)

Thanks to the “Trustworthy AI” chair that hast just been launched in september 2022, we have three internships opportunities available, each of them with a secured PhD funding (one if...


Panel discussion on a trustworthy digital world at Unesco (Université de la terre)

(26 November 2022)

As part of the “Université de la terre” 2022, organised at Unesco, Paris, I was able to take part in panelist discussion, for general audience, on the problems of trust...


The LaBRI web site was unavailale for 4 days

(21 November 2022)

Due to some important construction work around the LaBRI building, a central electrical board exploded, leading to an emergency shutdown of all (yes, all) of the Lab’s servers, including the...


Meeting Day of the French Regional Network R3IA

(19 October 2022)

Since 2021, the members of the regional AI research network have been initiating numerous actions around Artificial Intelligence (e.g. AI4Industry, Dataquitaine or even IA Pau) The first meeting took place...


Dagstuhl Seminar on SAT

(12 October 2022)

I had the pleasure to participate to another Dagstuhl Seminar on Theory and Practice of SAT and Combinatorial Solving this week. Dagstuhl is a remote castle in Germany, a computer...

Explanations during a presentation

Short Presentation

I hold a full Professor position at the Bordeaux-INP engineering school and I am conducting my resarch in the Formal Methods group of the Computer Science Lab of Bordeaux (laBRI), University of Bordeaux, since September, 2013.

Since 2021, I am in charge of the Computer Science department of the ENSEIRB-MATMECA Engineering School, with more than 300 students in the department and more than thousands students for the whole school. The ENSEIRB-MATMECA is the largest engineering school member of the Bordeaux INP group.

⊆ Computer Science Dep. ⊆ ENSEIRB-MATMECA ⊆ Bordeaux-INP ⊆ INP ⊆

Drones during the celebration of the 100 years of ENSEIRB-MATMECA

I am pleased to teach at the National Polytechnical Institute of Bordeaux, member of the national engineering school network INP). Of course, I’m teaching in the ENSEIRB-MATMECA engineering school, member of Bordeaux-INP, and in the computer Science department.

Picture of the Bordeaux INP Engineering School

Amongst the important tasks I am involved in, I spend a lot of time with the following activities:

(Previously, I was member of the LRI laboratory in the University of Orsay Paris 11, in the Artificial Intelligence and Inference System group (IASI))

Research Topics

Picture of the LaBRI Computer Science Laboratory

My main research activities are conducted at the LaBRI laboratory (see picture above). My interests are on propositional-based reasoning, SAT solving and
efficient Prime Implicates generation / Knowledge Base Compilation with a strong appetite on experimental study of AI tools (SAT Solvers essentially). I used to work
on decentralized approaches of some of these topics (reasoning on top of P2P and social networks, and ensuring diagnosability of designed systems). Since a few years, I am working on trustworthy AI, especially in the context of critical decisions or when an explanation is needed. To tackle these problems, logic / formal methods will be essentials.

About the Glucose SAT solver

Medals of our Glucose SAT Solver in the 2017 competition

Glucose is a SAT solver based on a particular scoring scheme for the clause learning mechanism, based on the paper Gilles Audemard and I wrote at IJCAI’09. Solver’s name is a contraction of the concept of “glue clauses”, a particular kind of clauses that glucose detects and preserves during search. Glucose is heavily based on Minisat, so please do cite Minisat also if you want to cite Glucose.

There is a dedicated page for the solver. In 2022, we decided to reboot it with the glucose 5.0 version.

What is SAT?

SAT is a fundamental problem of computer science that, intuitively, captures all the easiest of the hard problems. Hard problems mean problem that cannot be solved efficiently (you'll need more time than the universe had on large problems!). If you want to read more about it, why not taking your with the Wikipedia page about SAT ?