Picture of Nawal Benabbou

Nawal Benabbou:

I am an assistant professor at Sorbonne Université in Paris, working in the DECISION team of the LIP6 laboratory of computer science. Before that, I was a postdoctoral research fellow at NUS University in Singapore, School of Computing, hosted by Dr. Yair Zick. Prior to that, I was a PhD student under the supervision of Professor Patrice Perny at Sorbonne Université (LIP6) in Paris.

Email: nawal.benabbou@lip6.fr

Address: boîte courrier 169, couloir 26-00, étage 4, bureau 422, 4 place Jussieu, 75005 Paris, France.

Research interests:

    • algorithmic decision theory,

    • artificial intelligence,

    • multicriteria decision making,

    • multiobjective combinatorial optimization,

    • decision making under uncertainty/risk,

    • computational social choice,

    • preference elicitation,

    • fair allocation,

    • voting.

Awards and Honors:

  • 2021-2025: Holder of the "Prime d'Investissement Unique" (PIU).

  • 2018: Artificial Intelligence Dissertation Award, Association Française pour l'Intelligence Artificielle (AFIA), France.

  • 2017: AIJ/IJCAI Travel Award, International Joint Conference on Artificial Intelligence, Melbourne.

  • 2016: ECCAI/EurAi Travel Award, European Conference on Artificial Intelligence, The Hague.

  • 2014: ECAI'14 Best Student Paper Award [FILE].

  • 2013: Diploma of Excellence in Computer Science (summa cum laude), Sorbonne Université, Paris, France.

Education:

  • 2013-2017: PhD student in Preference Elicitation & Multiobjective Optimization (see my PhD thesis), under the supervision of prof. Patrice Perny. Sorbonne Université, Paris, France.

          • Patrice PERNY (Thesis Advisor), Sorbonne University

          • Jérôme LANG (Rapporteur), Paris-Dauphine University

          • Marc PIRLOT (Rapporteur), University of Mons

          • Clarisse DHAENENS (Examiner), Lille 1 University

          • Nicolas MAUDET (Examiner), Sorbonne University

          • Vincent MOUSSEAU (Examiner), CentraleSupélec

          • Daniel VANDERPOOTEN (Examiner), Paris-Dauphine University

  • 2011-2013: Master's degree in Artificial Intelligence & Decision Making (summa cum laude). Sorbonne Université, Paris, France.

  • 2008-2011: Bachelor’s degree in Applied Mathematics & Computer Science. Sorbonne Université, Paris, France.

Academic Activities:

  • 2018-present: Assistant professor, Sorbonne Université, Paris, France.

  • 2017-2018: Postdoctoral research fellow, National University of Singapore (NUS), Singapore.

  • 2016-2017: Temporary teaching and research assistant, Sorbonne Université, Paris, France.

  • Senior PC member: IJCAI (2021).

  • PC member: IJCAI (2018, 2019, 2020), AAAI (2019, 2020, 2021), AAMAS (2019, 2020, 2021), ECAI (2018, 2020), UAI (2021), COMSOC (2018), CoopMAS (2017), FAMAS (2019), GAIW (2020, 2021).

  • Reviewer: EJOR, AGNT, MCDA, 4OR, IJITDM.

Teaching Responsibilities:

  • 2021-present: Responsible for the course "IT projects" (~30 bachelor students, ~12 professors), Sorbonne Université, Paris, France.

  • 2020-present: Responsible for the course "Data Structures" (~300 bachelor students, , ~20 instructors), Sorbonne Université, Paris, France.

  • 2019-present: Co-responsible of the Bachelor’s degree in Mathematics and Computer Science called PIMA, Sorbonne Université, Paris, France.

  • 2019-present: Lecturer for the course "Artificial Intelligence and Games" (~120 bachelor students, ~6 instructors), Sorbonne Université, Paris, France.

PhD students:

  • Nathanaël Gross Humbert (2020-present): Group Fairness and Diversity Constraints.

  • Cassandre Leroy (2019-present): Preference Elicitation for Multi-Objective Combinatorial Optimization.

Master students:

  • Nesrine Benamor (Feb-Aug 2020)

  • Nathanaël Gross Humbert (Feb-Aug 2020)

  • Cassandre Leroy (Feb-Aug 2019)

Projects:

  • ANR Project THEMIS (2021-2025): THeory and Evidence to Measure Influence in Social structures.

  • FSI Starting Grant (2020-2021): Group Fairness, Diversity Constraints and Preference Elicitation.

  • CNRS International Emerging Action INDICOD (2020): INteractive DEcision-making for COmplex Domain.

  • LIP6 Project (2020): Group Fairness in Allocation Problems.

  • Gaspard Monge Project (2019-2021): Interactive Methods and Preference Elicitation for Solving Hard Multiobjective Combinatorial Optimization Problems.

  • RFSI Project APERO2 (2019-2021): Apprentissage interactif des PreférencEs pour la Résolution de problèmes d'Optimisation combinatoire multi-critères.

  • RFSI Project APERO (2018-2019): Apprentissage interactif des PreférencEs pour la Résolution de problèmes d'Optimisation combinatoire multi-critères.

  • ANR Project COCORICO (2014-2019): Computation, Communication, Rationality and Incentives in Collective and Cooperative Decision Making.

  • ANR Project ELICIT (2014-2016): Efficient eLIcitation of preferences based on Choquel InTegrals.