Gwen Maudet

Portrait of Gwen Maudet

Postdoctoral Researcher
University of Luxembourg · SnT · PCOG

I work at the intersection of mathematical optimization, machine learning, and algorithm design, with applications to industrial optimization and networking problems.

Research profile

Mathematical modelling · Combinatorial optimization · Machine learning for exact solvers · MILP instance similarity · Massive IoT

Experience & Education

Dec. 2023 — Present

Postdoctoral Researcher

University of Luxembourg · SnT · Esch-sur-Alzette, Luxembourg

Machine learning for Mixed-Integer Linear Programming. Developing learning-based strategies for exact optimization solvers, studying generalization across heterogeneous MILP instances, and formulating networking and industrial optimization problems.

Teaching Master's students, supervising research projects, and co-supervising PhD research within the Ultra Big Optimization project.

2020–2023

PhD in Computer Science

IMT Atlantique · Rennes, France

Exploiting Sensor Similarity to Enhance Data Collection in Massive IoT Networks. Research on sensor similarity, energy-efficient data collection, message scheduling, and redundancy reduction in large-scale IoT networks.

PhD thesis · PhD defense video

Apr. — Sep. 2020

Research Intern

Inria · Rennes, France

Detecting bias in search engines. Developed bias-detection tools and contributed to the SNIDE platform.

2016–2020

Engineering Degree

IMT Atlantique · Nantes, France

Computer Science for Decision Support.

Focus on computer science, machine learning, mathematical optimization, and graph-based methods.

Jun. — Aug. 2019

Research Intern

Acklio · Rennes, France

Header compression for IoT networks. Developed clustering-based methods to identify similarities between transmission headers and generate compression rules based on RFC 8724.

2014–2016

Intensive Preparatory Program for Engineering Schools

Lycée Rabelais · MPSI → MP · France

Research

Overview

2023–Now

Machine Learning for Mixed-Integer Linear Programming

Postdoc in ML for exact solvers, with a focus on:

  • Human-readable ML strategies for solver component improvement.
  • MILP instance similarity and portfolio approaches for generalization of ML across heterogeneous instances.
  • Mathematical modelling of networking and industrial problems.

2020–2023

Sensor Networks & IoT

PhD research on data collection in Massive IoT networks, with a focus on:

  • Sensor similarity based on sensing transmissions.
  • Energy-efficient monitoring through scheduling and redundancy reduction in communications.

Publications

International Journals

  • P. Maillé, G. Maudet, M. Simon, B. Tuffin, “Are Search Engines Biased? Detecting and Reducing Bias using Meta Search Engines,” Electronic Commerce Research and Applications, 2022. (SJR: Q1) Link

International Conferences

  • A. Vorokhta, G. Maudet, G. Danoy, “Selecting the Best Lower-Bound Strategy in a Branch-and-Bound Algorithm Using Genetic Programming,” International Workshop on Big Optimization, 2026. Link
  • G. Maudet, G. Danoy, “A Distance Metric for Mixed Integer Programming Instances,” European Conference on Artificial Intelligence, 2025. (CORE: A) Link
  • G. Maudet, G. Danoy, “Search Strategy Generation for Branch and Bound Using Genetic Programming,” Association for the Advancement of Artificial Intelligence, 2025. (CORE: A*) Link
  • G. Maudet, M. Batton-Hubert, P. Maillé, L. Toutain, “Energy Efficient Message Scheduling with Redundancy Control for Massive IoT Monitoring,” IEEE WCNC, 2023. (CORE: B) Link
  • G. Maudet, M. Batton-Hubert, P. Maillé, L. Toutain, “Emission Scheduling Strategies for Massive-IoT: Implementation and Performance Optimization,” IEEE/IFIP NOMS, 2022. (CORE: B) Link

Extended Abstracts and National Conferences

  • M. Da Cunha, G. Maudet, G. Danoy, “Cutting Plane Selection for Mixed-Integer Linear Programming Using Genetic Programming,” Extended Abstract, Conference on Optimisation and Learning, 2026.
  • B. Blé, G. Maudet, G. Danoy, “Distance-based Portfolio Learning for Mixed-Integer Programming,” Extended Abstract, Conference on Optimisation and Learning, 2026.
  • G. Maudet, G. Danoy, “Une Distance pour les Instances de Programmation Linéaire en Nombres Entiers Mixtes,” ROADEF, February 2026.
  • G. Maudet, G. Danoy, “A Distance Metric for Mixed Integer Programming Instances,” ORBEL, February 2026.
  • A. Vorokhta, G. Maudet, G. Danoy, “Generating LB Computation Strategies in a B&B Algorithm: Application to the PFSP,” Extended Abstract, Conference on Optimisation and Learning, 2025.
  • G. Maudet, M. Batton-Hubert, P. Maillé, L. Toutain, “Grouper les Capteurs Similaires Grâce à leurs Données dans le Contexte de Massive IoT,” ALGOTEL, May 2024. HAL
  • G. Maudet, M. Batton-Hubert, P. Maillé, L. Toutain, “Réduction de la Redondance de Messages des Capteurs dans un Contexte Massive IoT,” ALGOTEL, May 2023. HAL

Preprint

  • G. Maudet, M. Batton-Hubert, P. Maillé, L. Toutain, “Grouping Sensors Based on Observations in a Massive IoT Deployment.” HAL

Ongoing Work

  • “Adaptive Lower Bound Evaluation for the Permutation Flowshop Scheduling Problem,” in collaboration with Alisa Vorokhta. Under review.
  • “SkyHOSTop: Cost-Aware Multi-Cloud Streaming Overlay Optimization,” in collaboration with Muhammad Arslan Tariq. Under review.
  • “Cutting Plane Selection for Mixed-Integer Linear Programming Using Genetic Programming,” in collaboration with Mathis Da Cunha. Under review.
  • “Performance Driven Portfolio Approach to Generalize Machine Learning for Mixed Integer Programming.” In progress.
  • “Distance Based Clustering of the Mixed-Integer Programming Space for Portfolio-Based Machine Learning Generalization,” in collaboration with Baka Junior Cedric Blé. In progress.

PhD Thesis

Exploiting Sensor Similarity to Enhance Data Collection in Massive IoT Networks

Thesis on HAL · PhD defense video

Mentors

My PhD research was conducted within the SRCD department of IMT Atlantique and IRISA, under the supervision of:

My current postdoctoral research is conducted within the PCOG group at the University of Luxembourg, under the mentorship of:

Supervision

PhD Students

  • 2026–Present · Simon Renard — Enhancing solver branching strategies through machine learning.
  • 2026–Present · Muhammad Arslan Tariq — Streaming through multi-cloud, multi-path connections; path optimization using MILP formulations.
  • 2023–Present · Alisa Vorokhta — Machine learning for improving lower-bound computation.

Interns

  • 2025 · Baka Junior Cedric Blé — Clustering the mixed-integer programming space; 5 months.
  • 2025 · Mathis Da Cunha — Cutting-plane selection in Branch & Bound; 5 months.
  • 2022 · Issam Belhorma — Kriging techniques for sensor position estimation; 5 months.
  • 2021 · Carlos Delgado — Sensor deployment in green walls; 3 months.

Student Projects & Jobs

  • 2025 · Diptaraj Sen — Evaluating instance benchmarks using distances between optimization instances; 3 months, 5 h/week.
  • 2024 · Daniele Ferrario — Understanding a reinforcement-learning framework for cutting-plane selection; 5 months, 5 h/week.

Teaching

Teaching across mathematical foundations, theoretical computer science, optimization algorithms, and computational methods, connecting theory with practical problem solving.

Mathematical Foundations
Algebra Probability & Statistics Signal Processing
Optimization Algorithms
MILP Branch & Bound Branching & Search Population-Based Algorithms
Computational Practice
Python MATLAB Data Science SCIP DEAP Jupyter Notebooks

University of Luxembourg · 2024–2025

Project supervision: Semester-long projects with teams of three Master's students, around four hours of group work per week.

  • 2024 — Lower-bound strategies in Branch & Bound for the Permutation Flowshop Problem.
  • 2025 — Cutting-plane selection in Branch & Bound.

Lectures: Master's students in Information and Computer Sciences.

  • Winter 2024: 4 × 1.5-hour lectures · 58 students.
  • Winter 2025: 6 × 1.5-hour lectures · 62 students.

Lecture resources:

  • Introduction to Branch & Bound — Slides
  • Searching and Branching in Branch & Bound — Slides
  • Population-Based Algorithms — Slides
  • Travelling Salesman Problem — Exercises · Correction

IMT Atlantique · Rennes · 2022–2023

Practice teaching in the international Master's program in Information Technology.

  • 2022: 49 hours · 12 students.
  • 2023: 40 hours · 24 students.

Topics: Algebra, probability and statistics, Python, data science, MATLAB, signal processing, operations research and problem solving.

Reviewing & Service

  • Shadow PC Chair — ALGOTEL-Cores 2025; reviewer recruitment, review methodology, and paper discussions.
  • Reviewer — IEEE Transactions on Network and Service Management, IEEE Sensors Journal, and IPDPS Workshop; shadow reviewer for ALGOTEL/Cores.

Academic Service & Associations

  • President, Association of PhD Students and Young Researchers, IMT Atlantique Rennes · 2022–2023.
  • PhD Student Representative, SPIN Doctoral School, IMT Atlantique Rennes · 2023.

Other Interests

  • 🌱 Gardening & permaculture — From seed to fruit, including edible and inedible plants, flowering plants, and anything else that happens to grow.
  • 🫙 Fermentation & experimental cooking — Kombucha, lacto-fermented vegetables, homemade vinegar from questionably old alcohol.
  • 🧗 Sports — Indoor and outdoor bouldering, rope climbing, trail running and hiking, cyclotourism, and a black belt in judo.
  • 🎵 Music — Post-punk, rap, indie rock, and French variété.

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