Mo Siala
I am an Associate Professor in Computer Science at
INSA Toulouse
and
LAAS-CNRS.
I conduct my research activities as a member of the
ROC research group (Operations Research, Combinatorial Optimization, and Constraints) in LAAS-CNRS.
Prior to that, I was a postdoctoral researcher at Insight, Centre for Data Analytics, University College Cork, Ireland.
Most of my research is primarily focused on developing algorithms for diverse applications of combinatorial optimisation, machine learning, automated decision-making, and artificial intelligence in general. I am currently interrested to work on AI Safety and the alignment problem.
My PhD Thesis is available here .
A short version of my CV is available here . The long version is available upon request.
Most of my research is primarily focused on developing algorithms for diverse applications of combinatorial optimisation, machine learning, automated decision-making, and artificial intelligence in general. I am currently interrested to work on AI Safety and the alignment problem.
My PhD Thesis is available here .
A short version of my CV is available here . The long version is available upon request.
ORCID
Main News [February 2024]
February 2024
I gave a talk entitled
Learning User Preferences in Interactive
Constraint Programming at the AAAI 2024 Bridge on Constraint Programming and Machine Learning
.
The slides are available
here
January 2024
Our new preprint SoK: Taming the Triangle - On the Interplays between Fairness, Interpretability and Privacy in Machine Learning is now available
here
December 2023
Our paper
Probabilistic Dataset Reconstruction from Interpretable Models
is accepted to the second
IEEE Conference on Secure and Trustworthy Machine Learning (SatML).
A preprint is available here
Novembre 2022
Super proud of my Ph.D. student Julien Ferry
for his amazing work on exploiting fairness for privacy in machine learning.
The paper is accepted in
in the very first edition of the
IEEE Conference on Secure and Trustworthy Machine Learning (SatML).
The paper is entitled
Exploiting Fairness to Enhance Sensitive Attributes Reconstruction . A preprint will be available soon.
July 2022
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
July 2022
Our Constraint Programming solver Mistral-2.0 won multiple awards in the XCSP Constraint Programming competition including the first place in the mini optimisation track.
May 2022
Great news! Our paper
Improving Fairness Generalization Through a Sample-Robust Optimization Method is accepted for publication in
Machine Learning
February 2022
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.
December 2021
Our paper
Optimizing Binary Decision Diagrams with MaxSAT for classification is accepted for publication in
AAAI'22 , the Thirty-Sixth AAAI Conference on Artificial Intelligence.
September 2021
I am appointed as an academic advisor and coordinator for the AI and Big Data major at INSA Toulouse
July 2021
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!
September 2020
Our Constraint Programming solver Mistral-2.0 won two bronze medals for the
MiniZinc Challenge 2020 (free and parallel track).
September 2020
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.
June 2020
Our paper
Towards Formal Fairness in Machine Learning is accepted for publication in
CP 2020,
the 26th International Conference on Principles and Practice of Constraint Programming.
April 2020
Our paper
Learning Optimal Decision Trees with MaxSAT and its Integration in AdaBoost is accepted for publication in
IJCAI-PRICAI 2020,
the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence
February 2020
I gave a seminar at the Department of Philosophy, UCC, Ireland entitled :
"Computational Thinking and AI for Philosophers"
September 2019
I am a Distinguished Program Committee for
IJCAI 2019,
the 28th International Joint Conference on Artificial Intelligence !