Grégoire Danoy

Grégoire Danoy

Research Scientist

University of Luxembourg

Dr. Grégoire Danoy is a Research Scientist at the University of Luxembourg (UL) and Deputy-Head of the Parallel Computing and Optimisation Group (PCOG).

His current research interests include artificial intelligence techniques applied to unmanned autonomous systems (e.g., drones), satellite communications, vehicular networks, bioinformatics, high-performance and cloud computing.


  • Swarm Intelligence,
  • Metaheuristics,
  • Machine Learning,
  • Unmanned Autonomous Systems,
  • Smart Cities


  • Authorisation to direct research (ADR), 2019

    University of Luxembourg, Luxembourg

  • PhD in Computer Science, 2008

    Ecole des Mines of Saint-Etienne, France

  • Master in Computer Science, 2004

    Ecole des Mines of Saint-Etienne, France

  • Industrial Engineer degree in Computer Science, 2003

    Luxembourg University of Applied Sciences (IST)



Deputy Head of the PCOG

FSTM/DCS - SnT, University of Luxembourg

Jan 2020 – Present Luxembourg
Co-direction of the Parallel Computing and Optimisation Group - 25 researchers and engineers

Research Scientist

FSTM/DCS - SnT, University of Luxembourg

Jan 2011 – Present Luxembourg
  • Research in Artificial Intelligence, Optimisation, Smart Cities, Unmanned Autonomous Vehicles.
  • Research and technology transfer funding acquisition: FNR (Luxembourg), EDA (EU), ONRG (USA)
  • Project management: PI and work package leader
  • Founder and manager of the SwarmLab
  • Supervision of doctoral and postdoctoral researchers
  • Organisation of international scientific conferences and workshops
  • Reviewer for international scientific conferences, journals and research agencies
  • Teaching smart cities and optimisation at Bachelor, Master and PhD levels (academic and professional audience)
  • Several invited talks on Smart Cities (ISACA Luxembourg, World Standards Day, ILNAS Breakfasts)
  • Co-authoring of a book on “Evolutionary algorithms for mobile ad hoc networks”

Research Associate

FSTC-CSC, University of Luxembourg

Aug 2008 – Dec 2010 Luxembourg
* Research in Artificial Intelligence, Optimisation, Smart Cities, Vehicular Networks
* Research funding acquisition: FNR (Luxembourg), Eureka-Celtic (EU)
* Project management: Work package and task leader
* Daily advisory to doctoral and postdoctoral researchers
* Reviewer for international scientific conferences and journals
* Teaching optimisation at Bachelor and Master levels

Research Assistant

FSTC-CSC, University of Luxembourg

Aug 2004 – Jul 2008 Luxembourg
  * Initiator/Leader of the Dafo project, a distributed multi-agent framework for business problems optimisation
  * Teaching UML and algorithmics at Bachelor and Master levels


Research Projects



Technology Transfer Projects



  • 2022 - ICAART 2022 : Best Student Paper Nomination
  • 2018 - US Navy (Office of Naval Research Global - ONRG)
  • 2017 - IEEE CybConf: Best Paper Award.
  • 2016 - ACM GECCO : Best Paper Nomination.
  • 2009 - ACM GECCO : Best Paper Nomination.
  • 2003 - Prize of the Revue technique Luxembourgeoise of the ALIAI (Association Luxembourgeoise des Ingénieurs, Architectes et Industriels).


Past and current teaching activities at University of Luxembourg

Education Management:

  • 2021 - Present: Master in Technopreneurship - Responsible of the modules Smart ICT Technologies I and Smart ICT Technologies II. Member of the MTECH Jury
  • 2015-2016 and 2017-2018: Smart ICT for business innovation - Responsible of the Smart Platforms 1 and Smart Platforms 2 modules for the two promotions of the Certificate. Member of the Certificate Jury for the two promotions of the Certificate

Bachelor Level:

  • 2007 - 2008: GA introduction, Bachelor in Computer Science 2, University of Luxembourg
  • 2006 - 2009: Analysis and Design using UML, Bachelor in Computer Science 2, University of Luxembourg
  • 2004 - 2008: Advanced Algorithmics, Bachelor in Computer Science 2, University of Luxembourg

Industrial Engineering Level:

  • 2004 - 2007: Advanced Algorithmics, fourth year industrial engineering in computer science, Luxembourg Institute of Applied Sciences (IST), Luxembourg

Master Level:

  • 2021 - Present: Smart ICT Module Introduction / IoT Latest Developments / Smart Cities, Master in Technopreneurship (MTECH), University of Luxembourg
  • 2016, 2018: Smart Cities, Smart ICT Certificate, ILNAS/University of Luxembourg.
  • 2016, 2018: Smart Cities, Master in Entrepreneurship and Innovation, University of Luxembourg
  • 2008 - Present: Optimisation for Computer Science, Master in Computer Science (MICS 2), University of Luxembourg
  • 2005 - 2008: Co-evolutionary Genetic Algorithms, Master in Computer Science (MICS 2), University of Luxembourg

Students Supervision

PhD level


  • Maria Hartmann, University of Luxembourg, Distributed machine learning for swarm-based space systems (with the ILNAS) (2022 - )
  • Florian Felten, University of Luxembourg, Multi-objective hyper-heuristics (2021 - )
  • Gabriel Duflo, University of Luxembourg, Automated design of drone swarming algorithms (2019 - )
  • Nader Samir Labib, University of Luxembourg, Unmanned Aerial System Traffic Management With Distributed Decision Making, (with the ILNAS) (2017 - 2021)

Daily Advisor

  • Hedieh Haddad, Advanced Building Information Modelling (with the ILNAS) (2022 - )
  • Guillaume Helbecque, Cooperative parallel combinatorial optimisation for large scale supercomputers (2021 - )
  • Manuel Combarro Simon, Trustworthy ICT (with the ILNAS) (2021 - )
  • Ayman Makki, Optimisation of giant deep neural networks (2020 - )
  • Antonio Fiscarelli, Digital History and Hermeneutics (with the C2DH) (2016 - 2020)
  • Boonyarit Changaival, Evolutionary clustering of biological knowledge, (2016 - 2019)
  • Emmanuel Kieffer, Bi-level optimisation algorithms (2015 - 2019)
  • Sune S. Nielsen, Diversity Preserving Genetic Algorithms - Application to the Inverted Folding Problem and Analogous Formulated Benchmarks (with the LCSB) (2011 - 2016)
  • Agata Grzybek, Community-based vehicular networks for traffic information systems (2011 - 2015)
  • Mateusz Guzek, Holistic, Autonomic, and Energy-aware Resource Allocation in Cloud Computing (PPP with Tri-ICT) (2011 - 2014)
  • Apostolos Stathakis, Satellite payload reconfiguration optimization (PPP with SES S.A.) (2010 - 2014)
  • Patricia Ruiz, Efficient communication protocols for ad hoc networks (2009 - 2013)

Students Supervision

Master & Bachelor level

Bachelor Level

  • 2020 - Noe Jager, BICS II, University of Luxembourg - Drone(s) mobility management in a 3D environment
  • 2019: Noe Jager and Spadoni Gabriel, BICS I, University of Luxembourg - Robot Programming in Python
  • 2018 - Youri Falomir, INP Bordeaux, France - Usage of Hololens for the control of UAVs
  • 2006: Tom Martins, University of Luxembourg - hybrid coevolutionary genetic algorithm. Work led to one publication in IEEE HIS 2006.

Master level

  • 2022 - Mathis Lamiroy, ENS Lyon, France - Distributed Machine learning for swarms of autonomous systems.
  • 2020 - Raphaël Duflo, Normandy University, France - Development of an Android Ground Control Station interface for UAV swarms.
  • 2018 - Matthieu Vuillez, University of Lorraine, France - Evolutionary Game theory for UAV swarming
  • 2018 - Gabriel Duflo, Normandy INSA Rouen, France - Hyper-heuristics for the automatic generation of UAV swarming behaviours
  • 2015: Christof Ferreira Torres, University of Luxembourg - preference-based genetic algorithm (PBGA). This work led to two publications in ESCIM 2015 and GECCO 2016
  • 2015: Atten Christophe, University of Luxembourg - Nature-inspired mobility models for fleets of drones. This work led to one publication in EvoApps 2016
  • 2015 - Abdeslam Bourkane, University of Luxembourg - Study of Satellite Communication Channels and The Effect of the Atmospheric Attenuation (with SES S.A.)
  • 2014 - Emmanuel Kieffer, University of Lorraine, France - Multi-objective Satellite Payload Optimization (with SES S.A.)
  • 2013: Sasan Jafarnejad, University of Luxembourg - Multi-Objective Satellite Payload Optimization
  • 2013 - Luke Scott, University of Luxembourg - A method for coordinating unrelated space-time topologies in multi-agent, multi-scale simulations (with the BC3 research centre, Spain)
  • 2012: Alexios Aravanis, National Technical University of Athens, Greece - Resource Optimization in Multi-Beam Satellites. This work led to one publication in IEEE Transactions on Wireless Communications.
  • 2009: Imen Laabidi, Sup’Com, Tunis, Tunisia - High-fidelity simulation for vehicular and urban ad hoc networks

PhD Boards

Participation to PhD Boards

  • 2022 - Christian Cintrano, University of Malaga, Spain - Jury Member
  • 2022 - Saharnaz Dilmaghani, University of Luxembourg - Jury Member
  • 2021 - Antonio Fiscarelli, University of Luxembourg - Jury Member
  • 2019 - Boonyarit Changaival, University of Luxembourg - Jury Member
  • 2019 - Emmanuel Kieffer, University of Luxembourg - Jury Member
  • 2017 - Esteban López Camacho, University of Malaga, Spain - Reviewer
  • 2017 - Santiago Iturriaga, Universidad de La Republica, Uruguay - Reviewer
  • 2017 - Jean-Thomas Camino, LAAS, Toulouse, France - Jury Member
  • 2017 - Anh Quan Nguyen, University of Luxembourg - Jury Member
  • 2016 - Sune S. Nielsen, University of Luxembourg - Jury Member
  • 2015 - Juan Jose Palacios Alonso, University of Oviedo, Spain - Jury Member
  • 2015 - Agata Grzybek, University of Luxembourg - Jury Member
  • 2014 - Mateusz Guzek, University of Luxembourg - Jury Member
  • 2014 - Apostolos Stathakis, University of Luxembourg - Jury Member
  • 2013 - Patricia Ruiz, University of Luxembourg - Jury Member
  • 2010 - Apivadee Piyatumrong, University of Luxembourg - Jury Member

Recent Publications

Metaheuristics-based Exploration Strategies for Multi-Objective Reinforcement Learning

Overcoming partitioning in large ad hoc networks using genetic algorithms

Target Tracking Optimization of UAV Swarms Based on Dual-Pheromone Clustering

From communities to protein complexes: A local community detection algorithm on PPI networks

Identifying protein complexes in protein-protein interaction (ppi) networks is often handled as a community detection problem, with algorithms generally relying exclusively on the network topology for discovering a solution. The advancement of experimental techniques on ppi has motivated the generation of many Gene Ontology (go) databases. Incorporating the functionality extracted from go with the topological properties from the underlying ppi network yield a novel approach to identify protein complexes. Additionally, most of the existing algorithms use global measures that operate on the entire network to identify communities. The result of using global metrics are large communities that are often not correlated with the functionality of the proteins. Moreover, ppi network analysis shows that most of the biological functions possibly lie between local neighbours in ppi networks, which are not identifiable with global metrics. In this paper, we propose a local community detection algorithm, (lcda-go), that uniquely exploits information of functionality from go combined with the network topology. lcda-go identifies the community of each protein based on the topological and functional knowledge acquired solely from the local neighbour proteins within the ppi network. Experimental results using the Krogan dataset demonstrate that our algorithm outperforms in most cases state-of-the-art approaches in assessment based on Precision, Sensitivity, and particularly Composite Score. We also deployed lcda, the local-topology based precursor of lcda-go, to compare with a similar state-of-the-art approach that exclusively incorporates topological information of ppi networks for community detection. In addition to the high quality of the results, one main advantage of lcda-go is its low computational time complexity.