Bio

I am a French researcher specializing in Graph-Based Machine Learning and Recommender Systems, with a Ph.D. from École Polytechnique and over seven years of experience in the music tech industry.

Until recently, I was a Research Scientist and Coordinator on Music Recommendation at Deezer. From 2018 to 2024, I conducted research on Machine/Deep Learning, Graph Representation Learning, Information Retrieval, and Recommender Systems as part of the Research team in France. Previously, from 2016 to 2018, I worked as a Data Scientist in the company, collaborating with cross-functional teams to enhance the user experience.

My research has resulted in over 30 scientific publications in peer-reviewed journals and international conferences, earning best paper awards or honorable mentions at RecSys 2020, 2021, and 2024, as well as at ECIR 2024. Several of these publications describe algorithms now powering Deezer's recommender systems, helping millions of users worldwide discover new music daily.

I completed my Ph.D. from 2018 to 2022 alongside my work at Deezer, through a scientific partnership with École Polytechnique. I was supervised by Romain Hennequin and Michalis Vazirgiannis. Prior to that, I graduated in 2016 from ENS Paris-Saclay with an M.Sc. in Machine Learning (MVA), and from ENSAE Paris with an M.Eng. in Data Science, both with first-class honours.

I am now embarking on the next chapter of my career and look forward to sharing more soon!

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News

• March 2025: We will co-organize a RecSys 2025 workshop on LLMs. Stay tuned!
• February 2025: We will present our study on vMF sampling of GloVe vectors at FPI@ICLR 2025!
• January 2025: Our paper on weight sharing in VGAE has been accepted at WWW 2025!
• October 2024: We are thrilled to be among the “Best Full Paper” candidates at RecSys 2024!
• August 2024: We will present three papers on music recommendation at RecSys 2024.
• July 2024: I was fortunate to be invited by VinAI to discuss graph ML in Hanoi.

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Publications

See me also on Google Scholar and ORCID.org.

2025

• EARL: The 2nd Workshop on Evaluating and Applying Recommender Systems with Large Language Models
  I. Li, R. Dong, G. Salha-Galvan, A. Lawlor, D. Liu, L. Li
  19th ACM Conference on Recommender Systems (RecSys 2025)
  [PDF (soon)] [Website (soon)]

• von Mises-Fisher Sampling of GloVe Vectors
  W. Bendada, G. Salha-Galvan, R. Hennequin, T. Bontempelli, T. Bouabça, T. Cazenave
  Workshop on Frontiers in Probabilistic Inference: Sampling Meets Learning
  13th International Conference on Learning Representations (ICLR 2025)
  [PDF] [Code]

• To Share or Not to Share: Investigating Weight Sharing in Variational Graph Autoencoders
  G. Salha-Galvan, J. Xu
  2025 ACM Web Conference (WWW 2025)
  [PDF] [Code] [Data]

2024

Note: publications from 2023 and 2024 reflect my Research Coordinator role at Deezer, where I was responsible for supervising projects. I am often listed as the second or last author in these articles.

• Transformers Meet ACT-R: Repeat-Aware and Sequential Listening Session Recommendation
  V.A. Tran, G. Salha-Galvan, B. Sguerra, R. Hennequin
  18th ACM Conference on Recommender Systems (RecSys 2024)
  [PDF] [Code] [Data] Best full paper candidate

• Do Recommender Systems Promote Local Music? A Reproducibility Study Using Music Streaming Data
  K. Matrosova, L. Marey, G. Salha-Galvan, T. Louail, O. Bodini, M. Moussallam
  18th ACM Conference on Recommender Systems (RecSys 2024)
  [PDF] [Code] [Data]

• Let’s Get It Started (Again!): Fostering the Discoverability of New Releases on Deezer
  L. Briand, T. Bontempelli, W. Bendada, M. Morlon, F. Rigaud, B. Chapus, G. Salha-Galvan
  Workshop on Music Recommender Systems
  18th ACM Conference on Recommender Systems (RecSys 2024)
  (Workshop presentation showcasing our ECIR 2024 work)
  [PDF] [Slides]

• vMF-exp: von Mises-Fisher Exploration of Large Action Sets with Hyperspherical Embeddings
  W. Bendada, G. Salha-Galvan, R. Hennequin, T. Bontempelli, T. Bouabça, T. Cazenave
  Workshop on Aligning Reinforcement Learning Experimentalists and Theorists
  41st International Conference on Machine Learning (ICML 2024)
  [PDF] [Code]

• Let’s Get It Started: Fostering the Discoverability of New Releases on Deezer
  L. Briand, T. Bontempelli, W. Bendada, M. Morlon, F. Rigaud, B. Chapus, G. Salha-Galvan
  46th European Conference on Information Retrieval (ECIR 2024)
  [PDF] [Slides] Best industry track paper award

2023

• Track Mix Generation on Music Streaming Services using Transformers
  W. Bendada, T. Bontempelli, M. Morlon, B. Chapus, T. Cador, T. Bouabça, G. Salha-Galvan
  17th ACM Conference on Recommender Systems (RecSys 2023)
  [PDF] [Blog Post]

• On the Consistency of Average Embeddings for Item Recommendation
  W. Bendada, G. Salha-Galvan, T. Bouabça, T. Cazenave
  17th ACM Conference on Recommender Systems (RecSys 2023)
  [PDF] [Code] [Poster]

• Attention Mixtures for Time-Aware Sequential Recommendation
  V.A. Tran, G. Salha-Galvan, B. Sguerra, R. Hennequin
  46th Int. ACM SIGIR Conf. on Research and Development in Information Retrieval (SIGIR 2023)
  [PDF] [Code]

• A Scalable Framework for Automatic Playlist Continuation on Music Streaming Services
  W. Bendada, G. Salha-Galvan, T. Bouabça, T. Cazenave
  46th Int. ACM SIGIR Conf. on Research and Development in Information Retrieval (SIGIR 2023)
  [PDF] [Code]

2022

• New Frontiers in Graph Autoencoders: Joint Community Detection and Link Prediction
  G. Salha-Galvan, J.F. Lutzeyer, G. Dasoulas, R. Hennequin, M. Vazirgiannis
  Workshop on New Frontiers in Graph Learning
  36th Conference on Neural Information Processing Systems (NeurIPS 2022)
  [PDF] [Code]

• Flow Moods: Recommending Music by Moods on Deezer
  T. Bontempelli, B. Chapus, F. Rigaud, M. Morlon, M. Lorant, G. Salha-Galvan
  16th ACM Conference on Recommender Systems (RecSys 2022)
  [PDF] [Blog Post] [Poster] [Video]

• Contributions to Representation Learning with Graph Autoencoders and Applications to Music Recommendation
  G. Salha-Galvan
  Ph.D. thesis, École Polytechnique, Institut Polytechnique de Paris
  [PDF] [Slides from the defense]

2021

• Modularity-Aware Graph Autoencoders for Joint Community Detection and Link Prediction
  G. Salha-Galvan, J.F. Lutzeyer, G. Dasoulas, R. Hennequin, M. Vazirgiannis
  Neural Networks 153, 474-495, Elsevier (2021 impact factor: 9.657)
  [PDF] [Code]

• 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] [Video] Best student paper honorable mention

• 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] [Video]

• 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] [Blog Post] [Code] [Data] [Video]

• 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 (2020 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 honorable mention

• 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]

• 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]