Fragkiskos D. Malliaros logo

Fragkiskos D. Malliaros

Assistant Professor
CentraleSupélec, Paris-Saclay University
OPIS team, Inria Saclay


About me

I am an Assistant Professor at CentraleSupélec, Paris-Saclay University, working in the Center for Visual Computing, and the OPIS team of Inria Saclay. My research interests span the broad area of data science, with focus on graph mining, social network analysis, applied machine learning and natural language processing.

Right before that, I spent a wonderful year as a data science postdoctoral fellow in the Department of Computer Science and Engineering at UC San Diego, where I was a member of the Artificial Intelligence group. I was also affiliated with the Information Theory and Applications Center (ITA) and the Qualcomm Institute. Between Oct. 2015 - Sept. 2016, I was a postdoctoral researcher in the Data Science and Mining (DaSciM) group of the Computer Science Laboratory (LIX) at École Polytechnique in Paris, France, from where I also received my Ph.D. degree (Sept. 2015), working under the supervision of Prof. Michalis Vazirgiannis. I obtained both my Diploma and my M.Sc. degree from the Computer Engineering and Informatics Department of the University of Patras, Greece in 2009 and 2011 respectively. There, I was fortunate to work with Prof. Vasileios Megalooikonomou.

During the summer of 2014, I was a research intern at the Palo Alto Research Center (PARC) in Palo Alto, CA. I was also the recipient of the 2012 Google Europe Doctoral Fellowship in Graph Mining and the 2015 Thesis Prize by Ecole Polytechnique.

News

Teaching

DSBA: M.Sc. in Data Sciences and Business Analytics, CentraleSupélec and ESSEC Business School
AI: M.Sc. in Artificial Intelligence, CentraleSupélec


Current courses:

Previous courses:

Publications

Preprints

  • A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems
    Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Liò, Yoshua Bengio, and Michael Bronstein.
    Preprint, 2023.
    [arXiv: PDF]

2024

  • Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction
    Jhon A. Castro-Correa, Jhony H. Giraldo, Mohsen Badiey, and Fragkiskos D. Malliaros.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024.
    [arXiv: PDF, Code: LINK]
  • Estimation of a Causal Directed Acyclic Graph Process using Non-Gaussianity
    Aref Einizade, Jhony H. Giraldo, Fragkiskos D. Malliaros, and Sepideh Hajipour Sardouie.
    Digital Signal Processing, Elsevier, 2024.
    [Journal version: LINK]

  • 2023

    • Maximizing Influence with Graph Neural Networks
      George Panagopoulos, Nikolaos Tziortziotis, Fragkiskos D. Malliaros, and Michalis Vazirgiannis.
      IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Morocco, 2023.
      [arXiv: PDF]
    • On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks
      Jhony H. Giraldo, Konstantinos Skianis, Thierry Bouwmans, and Fragkiskos D. Malliaros.
      ACM International Conference on Information and Knowledge Management (CIKM), Atlanta, Georgia, 2023.
      [Paper: PDF, Code: LINK]
    • FAENet: Frame Averaging Equivariant GNN for Materials Modeling
      Alexandre Duval, Victor Schmidt, Alex Hernandez Garcia, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, and David Rolnick.
      International Conference on Machine Learning (ICML), Hawaii, 2023.
      [Paper: PDF, Code: LINK]
    • Time-varying Signals Recovery via Graph Neural Networks
      Jhon A. Castro-Correa, Jhony H Giraldo, Anindya Mondal, Mohsen Badiey, Thierry Bouwmans, and Fragkiskos D. Malliaros.
      IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Rhodes Island, Greece, 2023.
      [Paper: PDF]
    • Higher-order Sparse Convolutions in Graph Neural Networks
      Jhony H Giraldo, Sajid Javed, Arif Mahmood, Fragkiskos D. Malliaros, and Thierry Bouwmans.
      IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Rhodes Island, Greece, 2023.
      [Paper: PDF]

    • 2022

      • BraneMF: Integration of Biological Networks for Functional Analysis of Proteins
        Surabhi Jagtap, Abdulkadir Çelikkanat, Aurélie Pirayre, Frederique Bidard, Laurent Duval, and Fragkiskos D. Malliaros.
        Bioinformatics, Oxford University Press, 2022.
        [Journal Version: LINK, Paper: PDF, Code: LINK]
      • BRANEnet: Embedding Multilayer Networks for Omics Data Integration
        Surabhi Jagtap, Aurélie Pirayre, Frederique Bidard, Laurent Duval, and Fragkiskos D. Malliaros.
        BMC Bioinformatics, 2022.
        [Journal Version: PDF, Code: LINK], Code and data: LINK]
      • NodeSig: Binary Node Embeddings via Random Walk Diffusion
        Abdulkadir Çelikkanat, Apostolos N. Papadopoulos, and Fragkiskos D. Malliaros.
        IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Istanbul, Turkey, 2022.
        [Paper: PDF, Code: LINK]
      • Higher-order Clustering and Pooling for Graph Neural Networks
        Alexandre Duval and Fragkiskos D. Malliaros.
        ACM International Conference on Information and Knowledge Management (CIKM), Atlanta, Georgia, 2022.
        ICML Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG:ML), Baltimore, Maryland, 2022.
        [Paper: PDF, Code: LINK]
      • Multiple Similarity Drug-Target Interaction Prediction with Random Walks and Matrix Factorization
        Bin Liu, Dimitrios Papadopoulos, Fragkiskos D. Malliaros, Grigorios Tsoumakas, and Apostolos N. Papadopoulos.
        Briefings in Bioinformatics, Oxford University Press, 2022.
        [Journal Version: PDF, arXiv: PDF, Code: LINK]
      • Multiple Kernel Representation Learning on Networks
        Abdulkadir Çelikkanat, Yanning Shen, and Fragkiskos D. Malliaros.
        IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
        [Journal Version: PDF, arXiv: PDF, Code: LINK]
      • Multivariate Lipschitz Analysis of the Stability of Neural Networks
        Kavya Gupta, Fateh Kaakai, Beatrice Pesquet-Popescu, Jean-Christophe Pesquet, and Fragkiskos D. Malliaros.
        Frontiers in Signal Processing (Front. Sig. Proc.), 2022.
        [Journal Version: LINK]

      2021

      • BRANET: Graph-based Integration of Multi-omics Data with Biological a priori for Regulatory Network Inference
        Surabhi Jagtap, Aurélie Pirayre, Frederique Bidard, Laurent Duval, and Fragkiskos D. Malliaros.
        International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB), Online, 2021.
        [Paper: PDF, Code: LINK]
      • Influence Learning and Maximization (Tutorial)
        George Panagopoulos and Fragkiskos D. Malliaros.
        IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Online, 2021.
        [Tutorial Website: LINK]
      • GraphSVX: Shapley Value Explanations for Graph Neural Networks
        Alexandre Duval and Fragkiskos D. Malliaros.
        European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Online, 2021.
        [Paper: PDF, arXiv (full version): PDF, Code: LINK]
      • Multiomics Data Integration for Gene Regulatory Network Inference with Exponential Family Embeddings
        Surabhi Jagtap, Abdulkadir Çelikkanat, Aurélie Pirayre, Frederique Bidard, Laurent Duval, and Fragkiskos D. Malliaros.
        European Signal Processing Conference (EUSIPCO), Dublin, Ireland, 2021.
        [Paper: PDF, Code: LINK]
      • An Adversarial Attacker for Neural Networks in Regression Problems
        Kavya Gupta, Beatrice Pesquet-Popescu, Fateh Kaakai, Jean-Christophe Pesquet, and Fragkiskos D. Malliaros.
        IJCAI AI Safety Workshop (AISafety), Online, 2021.
        [Paper: PDF]
        Shortlisted for the Best Paper Award.
      • Topic-Aware Latent Models for Representation Learning on Networks
        Abdulkadir Çelikkanat and Fragkiskos D. Malliaros.
        Pattern Recognition Letters (Pattern Recognit. Lett.), Elsevier, 2021.
        [HAL repository: LINK, Journal Version: LINK]
      • Influence Learning and Maximization (Tutorial)
        George Panagopoulos and Fragkiskos D. Malliaros.
        International Conference on Web Engineering (ICWE), Online, 2021.
        [Paper: PDF, Tutorial Website: LINK]

      2020

      • Multi-task Learning for Influence Estimation and Maximization
        George Panagopoulos, Fragkiskos D. Malliaros, and Michalis Vazirgiannis.
        IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020.
        [Journal Version: PDF, arXiv: PDF, Code: LINK]
      • Boosting Tricks for Word Mover’s Distance
        Konstantinos Skianis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis, and Michalis Vazirgiannis.
        International Conference on Artificial Neural Networks (ICANN), Bratislava, Slovakia, 2020.
        [Paper: PDF]
      • Exponential Family Graph Embeddings
        Abdulkadir Çelikkanat and Fragkiskos D. Malliaros.
        AAAI Conference on Artificial Intelligence (AAAI), New York City, New York, 2020.
        [arXiv: PDF, Code: LINK]
      • Influence Maximization using Influence and Susceptibility Embeddings
        George Panagopoulos, Michalis Vazirgiannis, and Fragkiskos D. Malliaros.
        AAAI International Conference on Web and Social Media (ICWSM), Atlanta, Georgia, 2020.
        [Paper: PDF, Code: LINK]
        Best Paper Honorable Mention Award.
      • The Core Decomposition of Networks: Theory, Algorithms and Applications
        Fragkiskos D. Malliaros, Christos Giatsidis, Apostolos N. Papadopoulos, and Michalis Vazirgiannis.
        International Journal on Very Large Data Bases (The VLDB Journal), 2020.
        [Journal Version: LINK, HAL Repository: PDF]

      2019

      • Dynamic Monitoring of Software Use with Recurrent Neural Networks
        Chloé Adam, Antoine Aliotti, Fragkiskos D. Malliaros, and Paul-Henry Cournède.
        Data & Knowledge Engineering (DKE), Elsevier, 2019.
        [Journal Version: LINK]
      • Learning Node Embeddings with Exponential Family Distributions
        Abdulkadir Çelikkanat and Fragkiskos D. Malliaros.
        NeurIPS Graph Representation Learning Workshop (NeurIPS-GRL), Vancouver, Canada, 2019.
        [Paper: PDF]
      • Kernel Node Embeddings
        Abdulkadir Çelikkanat and Fragkiskos D. Malliaros.
        7th IEEE Global Conference on Signal and Information Processing (GlobalSIP), Ottawa, Canada, November 2019.
        [Paper: PDF, Code: LINK]
      • Perturb and Combine to Identify Influential Spreaders in Real-World Networks
        Antoine J.-P. Tixier, Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, Jesse Read, and Michalis Vazirgiannis.
        IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Vancouver, Canada, August 2019.
        [arXiv: PDF]
      • Semi-Supervised Learning and Graph Neural Networks for Fake News Detection
        Adrien Benamira, Benjamin Devillers, Etienne Lesot, Ayush K. Rai, Manal Saadi, and Fragkiskos D. Malliaros.
        IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Vancouver, Canada, August 2019.
        Also presented at the International Conference on Computational Social Science (IC2S2), Amsterdam, The Netherlands, July 2019.
        [Full paper: PDF, Code: LINK]

      2018

      • TNE: A Latent Model for Representation Learning on Networks
        Abdulkadir Çelikkanat and Fragkiskos D. Malliaros.
        NeurIPS Relational Representation Learning Workshop (NeurIPS-R2L), Montréal, Canada, 2018.
        [Paper: PDF, Poster: PDF, Code: LINK]
      • BiasedWalk: Biased Sampling for Representation Learning on Graphs
        Duong Nguyen and Fragkiskos D. Malliaros.
        IEEE International Conference on Big Data Workshops (Big Data), Seattle, WA, 2018.
        [Paper: PDF, HAL: PDF]
      • MATI: An Efficient Algorithm for Influence Maximization in Social Networks
        Maria-Evgenia G. Rossi, Bowen Shi, Nikolaos Tziortziotis, Fragkiskos D. Malliaros, Christos Giatsidis, and Michalis Vazirgiannis.
        PLOS One, 2018.
        [Journal version: LINK]
      • DiffuGreedy: An Influence Maximization Algorithm based on Diffusion Cascades
        George Panagopoulos, Fragkiskos D. Malliaros, and Michalis Vazirgiannis.
        International Conference on Complex Networks and Their Applications (Complex Networks), Cambridge, UK, 2018.
        [Paper: PDF, Journal version: LINK, Code: LINK]
      • k-Degree Anonymity on Directed Networks
        Jordi Casas-Roma, Julián Salas, Fragkiskos D. Malliaros, and Michalis Vazirgiannis.
        Knowledge and Information Systems (KAIS), Springer, 2018.
        [Paper: PDF, Journal version: LINK, Code: LINK]
      • GraphRep: Boosting Text Mining, NLP and Information Retrieval with Graphs (Tutorial)
        Michalis Vazirgiannis, Fragkiskos D. Malliaros, and Giannis Nikolentzos.
        ACM International Conference on Information and Knowledge Management (CIKM), Turin, Italy, 2018.
        [Paper: PDF, Tutorial Website: LINK]
      • Fusing Document, Collection and Label Graph-based Representations with Word Embeddings for Text Classification
        Konstantinos Skianis, Fragkiskos D. Malliaros, and Michalis Vazirgiannis.
        NAACL-HLT Workshop on Graph-Based Natural Language Processing (TextGraphs), New Orleans, Louisiana, June 2018.
        [Paper: PDF, Code: LINK]
        Best Paper Award.
      • Reconstructing Uncertain Graphs Based on Low-Rank Factorizations
        Ke Sun, Fragkiskos D. Malliaros, Frank Nielsen, and Michalis Vazirgiannis.
        From Physics to Information Sciences and Geometry (Entropy) , Barcelona, May 2018.
      • Graph-based Text Representations: Boosting Text Mining, NLP and Information Retrieval with Graphs (Tutorial)
        Fragkiskos D. Malliaros, Polykarpos Meladianos, and Michalis Vazirgiannis.
        The Web Conference (WWW), Lyon, France, 2018.
        [Tutorial Website: LINK]

      2017

      • MATI: An Efficient Algorithm for Influence Maximization in Social Networks
        Maria-Evgenia G. Rossi, Bowen Shi, Nikolaos Tziortziotis, Fragkiskos D. Malliaros, Christos Giatsidis, and Michalis Vazirgiannis.
        International Conference on Complex Networks and Their Applications (Complex Networks), Lyon, France, December 2017.
        [Paper: PDF]
      • NetGloVe: Learning Node Representations for Community Detection
        Kumaran Gunasekaran, Jeyavaishnavi Muralikumar, Sudarshan Srinivasa Ramanujam, Balasubramaniam Srinivasan, and Fragkiskos D. Malliaros.
        International Conference on Complex Networks and Their Applications (Complex Networks), Lyon, France, December 2017.
        [Paper: PDF]
      • Core Decomposition of Uncertain Graphs Using Representative Instances
        Damien Seux, Fragkiskos D. Malliaros, Apostolos Papadopoulos, and Michalis Vazirgiannis.
        International Conference on Complex Networks and Their Applications (Complex Networks), Lyon, France, December 2017.
        [Paper: PDF]
      • Core Decomposition of Networks: Concepts, Algorithms and Applications (Tutorial)
        Fragkiskos D. Malliaros, Apostolos N. Papadopoulos and Michalis Vazirgiannis.
        European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), Skopje, September 2017.
        [Tutorial Website: LINK]
      • Graph-based Text Representations: Boosting Text Mining, NLP and Information Retrieval with Graphs (Tutorial)
        Fragkiskos D. Malliaros and Michalis Vazirgiannis.
        Conference on Empirical Methods in Natural Language Processing (EMNLP), Copenhagen, Denmark, September 2017.
        [Tutorial Website: LINK]
      • Sensitivity of Community Structure to Network Uncertainty
        Marc Mitri, Fragkiskos D. Malliaros, and Michalis Vazirgiannis.
        SIAM International Conference on Data Mining (SDM), Houston, Texas, April 2017.
        [Paper: PDF, Slides: PDF, Project Website: LINK]
        Received the SIAM/NSF Early Career Travel Award.

      2016

      • SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks
        Konstantinos Skianis, Maria Evgenia G. Rossi, Fragkiskos D. Malliaros, and Michalis Vazirgiannis.
        IEEE International Conference on Data Mining (ICDM), Barcelona, Spain, December 2016.
        (Demo paper)
      • Core Decomposition of Networks: Concepts, Algorithms and Applications (Tutorial)
        Fragkiskos D. Malliaros, Apostolos N. Papadopoulos and Michalis Vazirgiannis.
        IEEE International Conference on Data Mining (ICDM), Barcelona, Spain, December 2016.
        (Acceptance Rate: 4/17)
        [Tutorial Website: LINK]
      • A Graph Degeneracy-based Approach to Keyword Extraction
        Antoine J.-P. Tixier, Fragkiskos D. Malliaros, and Michalis Vazirgiannis.
        Conference on Empirical Methods in Natural Language Processing (EMNLP), Austin, Texas, November 2016.
        [Paper: PDF]
      • A k-core Decomposition Framework for Graph Clustering
        Christos Giatsidis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis, Charanpal Dhanjal, Emmanouil Kiagias, Dimitrios M. Thilikos, and Michalis Vazirgiannis.
        Preprint, 2016.
        [arXiv: PDF]
      • Locating Influential Nodes in Complex Networks
        Fragkiskos D. Malliaros, Maria-Evgenia G. Rossi and Michalis Vazirgiannis.
        Scientific Reports, Nature Publishing Group, 2016.
        (Impact Factor: 5.228)
        [Journal Version: LINK]
        Editor's choice: complex networks.
      • Core Decomposition in Graphs: Concepts, Algorithms and Applications (Tutorial)
        Fragkiskos D. Malliaros, Apostolos N. Papadopoulos and Michalis Vazirgiannis.
        International Conference on Extending Database Technology (EDBT), Bordeaux, France, March 2016.
        [Paper: PDF, Slides: PDF]

      2015

      • Vulnerability Assessment in Social Networks under Cascade-based Node Departures
        Fragkiskos D. Malliaros and Michalis Vazirgiannis.
        EPL (Europhysics Letters), 110(6): 68006, IOP Science, 2015.
        (Impact Factor: 1.963)
        [Journal Version: LINK]
      • Graph-Based Term Weighting for Text Categorization
        Fragkiskos D. Malliaros and Konstantinos Skianis.
        Social Media and Risk Workshop (SoMeRis), IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Paris, France, August 2015.
        [Paper: PDF, Slides: PDF]
      • Core Decomposition: Algorithms and Applications (Tutorial)
        Fragkiskos D. Malliaros, Michalis Vazirgiannis and Apostolos N. Papadopoulos.
        IEEE/ACM Intern. Conf. on Advances in Social Networks Analysis and Mining (ASONAM), Paris, France, August 2015.
        [Tutorial Website: LINK]
      • Disengagement Social Contagion: Assessing Network Vulnerability under Node Departures
        Fragkiskos D. Malliaros and Michalis Vazirgiannis.
        International Conference on Computational Social Science (ICCSS), Helsinki, Finland, June 2015.
        [Paper: PDF]
      • Spread it Good, Spread it Fast: Identification of Influential Nodes in Social Networks
        Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, and Michalis Vazirgiannis.
        International World Wide Web Conference (WWW), Florence, Italy, May 2015.
        [Paper: PDF, Poster: PDF ]

      2014

      • Estimating Robustness in Large Social Graphs
        Fragkiskos D. Malliaros, Vasileios Megalooikonomou, and Christos Faloutsos.
        Knowledge and Information Systems (KAIS), Springer, 2014.
        (Impact Factor: 1.702)
        [Paper: PDF, Journal Version: LINK]
      • CoreCluster: A Degeneracy Based Graph Clustering Framework
        Christos Giatsidis, Fragkiskos D. Malliaros, Dimitrios M. Thilikos and Michalis Vazirgiannis.
        AAAI Conference on Artificial Intelligence (AAAI), Quebec City, Canada, July 2014.
        (Acceptance Rate: 28%)
        [Paper: PDF, Poster: PDF]

      2013

      • To Stay or Not to Stay: Modeling Engagement Dynamics in Social Graphs
        Fragkiskos D. Malliaros and Michalis Vazirgiannis.
        ACM International Conference on Information and Knowledge Management (CIKM), San Francisco, October 2013.
        (Full Paper, Acceptance Rate: 16.9%)
        [Paper: PDF, Slides: PDF]
      • Clustering and Community Detection in Directed Networks: A Survey
        Fragkiskos D. Malliaros and Michalis Vazirgiannis.
        Physics Reports, 533(4): 95-142, Elsevier, 2013.
        (Impact Factor: 22.929)
        [Journal Version: LINK, arXiv Preprint: PDF]
      • Multiresolution Similarity Search in Time Series Data: An Application to EEG Signals
        Amalia Charisi, Fragkiskos D. Malliaros, Evangelia Zacharaki, and Vasileios Megalooikonomou.
        ACM International Conf. on Pervasive Technologies Related to Assistive Environments (PETRA), Rhodes, Greece, May 2013.
        [Paper: PDF]
      • Graph Mining Tools for Community Detection and Evaluation in Social Networks and the Web (Tutorial)
        Christos Giatsidis, Fragkiskos D. Malliaros, and Michalis Vazirgiannis.
        International World Wide Web Conference (WWW), Rio de Janeiro, Brazil, May 2013.
        [Tutorial Slides: PDF]
      • Advanced Graph Mining for Community Evaluation in Social Networks and the Web (Tutorial)
        Christos Giatsidis, Fragkiskos D. Malliaros, and Michalis Vazirgiannis.
        ACM International Conference on Web Search and Data Mining (WSDM), Rome, Italy, February 2013.
        [Paper: PDF, Tutorial Website: LINK]

      2011 - 2012

      • Fast Robustness Estimation in Large Social Graphs: Communities and Anomaly Detection
        Fragkiskos D. Malliaros, Vasileios Megalooikonomou, and Christos Faloutsos.
        SIAM International Conference on Data Mining (SDM), Anaheim, California, April 2012.
        (Acceptance Rate: 27%)
        [Paper: PDF, Poster: PDF]
      • Expansion Properties of Large Social Graphs
        Fragkiskos D. Malliaros and Vasileios Megalooikonomou.
        DASFAA International Workshop on Social Networks and Social Media Mining on the Web (SNSMW), Hong Kong, April 2011.
        [Paper: PDF, Slides: PDF]

Collaborators

I have been very privileged to collaborate with the following great people, listed in chronological order of collaboration.

Vasileios Megalooikonomou (U of Patras), Christos Faloutsos (CMU), Michalis Vazirgiannis (École Polytechnique), Christos Giatsidis (École Polytechnique), Amalia Charisi (U of Patras), Evangelia I. Zacharaki (U of Patras), Dimitrios M. Thilikos (U of Montpellie, CNRS and U of Athens), Maria-Evgenia Rossi (École Polytechnique), Konstantinos Skianis (École Polytechnique), Jordi Casas-Roma (U Oberta de Catalunya and U Autònoma de Barcelona), Apostolos N. Papadopoulos (Aristotle U of Thessaloniki), Charanpal Dhanjal (Télécom ParisTech and Forebyte Ltd. London), Nikolaos Tziortziotis (École Polytechnique), Emmanouil Kiagias (Oracle, UK), Antoine J.-P. Tixier (École Polytechnique)


Misc

Contact

Address
Bâtiment Bouygues, CVN, Room 217
CentraleSupélec, 8 rue Joliot-Curie
91190 Gif-sur-Yvette, France