Bio

I am a Research Scientist at Deezer, a global music streaming service, in Paris, France. Since October 2018, I am simultaneously pursuing a Ph.D. in Machine Learning at École Polytechnique, under the supervision of Romain Hennequin and Michalis Vazirgiannis.

My research interests span the broad areas of Deep Learning, Graph Mining and Recommender Systems. In my recent publications, I mainly focused on improving Representation Learning on Graphs, with various applications to Music Information Retrieval and Music Recommendation.

Prior to my Ph.D., I worked as a Data Scientist at Deezer for two years, conducting product-oriented projects to improve UX, conversion and churn. Even before, I also handled exciting challenges in Canada and in China. Feel free to visit my LinkedIn profile for more details about my experience.

I graduated in 2016 from École Normale Supérieure Paris-Saclay, completing a Master's degree in Mathematics, Computer Vision and Machine Learning (MVA), and from ENSAE Paris, completing a Master of Engineering in Data Science, both with first class honours.

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News

• July 2021: We got two papers accepted at RecSys. See you (hopefully) in Amsterdam!
• May 2021: Our paper tackling user cold start on Deezer has been accepted at KDD!
• April 2021: Our work on FastGAE has been published in Neural Networks (impact factor: 8.05).
• Sept. 2020: Our work on music genre perception has been accepted at EMNLP!
• July 2020: I recently got papers accepted at ECML-PKDD, at ISMIR and at RecSys!

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Publications

See me also on Google Scholar and ORCID.org.

2021

• Cold Start Similar Artists Ranking with Gravity-Inspired Graph Autoencoders
  G. Salha-Galvan, R. Hennequin, B. Chapus, V.A. Tran, M. Vazirgiannis
  15th ACM Conference on Recommender Systems (RecSys 2021)
  [PDF] [Code] [Data]

• Hierarchical Latent Relation Modeling for Collaborative Metric Learning
  V.A. Tran, G. Salha-Galvan, R. Hennequin, M. Moussallam
  15th ACM Conference on Recommender Systems (RecSys 2021)
  [PDF] [Code]

• A Semi-Personalized System for User Cold Start Recommendation on Music Streaming Apps
  L. Briand, G. Salha-Galvan, W. Bendada, M. Morlon, V.A. Tran
  27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021)
  [PDF] [Code] [Data]

• Modéliser la Perception des Genres Musicaux à travers Différentes Cultures à partir de Ressources Linguistiques
  E.V. Epure, G. Salha-Galvan, M.Moussallam, R. Hennequin
  28ème Conférence sur le Traitement Automatique des Langues Naturelles (TALN 2021)
  (Summary paper presenting our EMNLP 2020 work)
  [PDF] [Code]

2020

Note: I published under the name G. Salha until 2020.

• FastGAE: Scalable Graph Autoencoders with Stochastic Subgraph Decoding
  G. Salha, R. Hennequin, J.B. Remy, M. Moussallam, M. Vazirgiannis
  Neural Networks 142, 1-19, Elsevier (impact factor: 8.05)
  [PDF] [Code]

• Modeling the Music Genre Perception across Language-Bound Cultures
  E.V. Epure, G. Salha, M. Moussallam, R. Hennequin
  2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)
  [PDF] [Code] [Data] [Video]

• Carousel Personalization in Music Streaming Apps with Contextual Bandits
  W. Bendada, G. Salha, T. Bontempelli
  14th ACM Conference on Recommender Systems (RecSys 2020)
  [PDF] [Code] [Data] [Video] Best short paper candidate

• Simple and Effective Graph Autoencoders with One-Hop Linear Models
  G. Salha, R. Hennequin, M. Vazirgiannis
  2020 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2020)
  [PDF] [Code] [Video]

• Multilingual Music Genre Embeddings for Effective Cross-Lingual Music Item Annotation
  E.V. Epure, G. Salha, R. Hennequin
  21st International Society for Music Information Retrieval Conference (ISMIR 2020)
  [PDF] [Code] [Data]

• Muzeeglot : Annotation Multilingue et Multi-Sources d’Entités Musicales à partir de Représentations de Genres Musicaux
  E.V. Epure, G. Salha, F. Voituret, M. Baranes, R. Hennequin
  27ème Conférence sur le Traitement Automatique des Langues Naturelles (TALN 2020)
  [PDF (in French)] [Slides (in English)] [Code]

2019

• Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks
  G. Salha, R. Hennequin, M. Vazirgiannis
  Workshop on Graph Representation Learning
  33rd Conference on Neural Information Processing Systems (NeurIPS 2019)
  [PDF] [Code]

• Gravity-Inspired Graph Autoencoders for Directed Link Prediction
  G. Salha, S. Limnios, R. Hennequin, V.A. Tran, M. Vazirgiannis
  28th ACM International Conference on Information and Knowledge Management (CIKM 2019)
  [PDF] [Code]

• A Degeneracy Framework for Scalable Graph Autoencoders
  G. Salha, R. Hennequin, V.A. Tran, M. Vazirgiannis
  28th International Joint Conference on Artificial Intelligence (IJCAI 2019)
  [PDF] [Code]

2018

• Adaptive Submodular Influence Maximization with Myopic Feedback
  G. Salha, N. Tziortziotis, M. Vazirgiannis
  2018 IEEE/ACM Int. Conf. on Adv. in Social Networks Analysis and Mining (ASONAM 2018)
  [PDF]