I am a computer scientist interested in various areas of computation, including algorithmic analysis,
combinatorial optimisation, formal methods, reasoning, and machine learning.
I currently hold a position as an Associate Professor of Computer Science at
INSA Toulouse
and LAAS-CNRS.
My research is conducted within the
ROC group
(Operations Research, Combinatorial Optimization, and Constraints) at LAAS-CNRS.
My early research broadened the use of Constraint Programming and Boolean Satisfiability for
sequencing, scheduling, and preference-based matching. My current focus is on trustworthy machine
learning through automated reasoning and formal methods. In the long term, I aim to develop resilient
computational systems that integrate reasoning and learning with rigorous guarantees, while remaining
adaptable to change, uncertainty, and undesirable outcomes.
I spent an amazing month in Montréal visiting the team of
Sébastien
Gambs and other researchers in
ETS,
UQAM,
and
Polytechnique
Montréal.
During the visit I gave a seminar entitled
Declarative Combinatorial
Optimisation for Machine
Learning .
The slides are available
here
Our paper
Leveraging Integer Linear Programming to Learn Optimal Fair Rule
Lists is
accepted for publication in
CPAIOR'22 ,
the 19th International Conference on the Integration of Constraint
Programming, Artificial
Intelligence, and Operations Research.
Check out our Python library, FairCORELS, for
learning fair and certifiably optimal rule lists.
This work is published in our paper "FairCORELS, an Open-Source Library
for Learning Fair
Rule Lists" in CIKM 2021, the 30th ACM International Conference on
Information and
Knowledge Management!
I am a co-chair of the CPAIOR
Master class 2020.
The theme of the master class is "Recent Advances in Optimisation
Paradigms and Solving
Technology".
You can watch the talks in youtube here.
