| 2019 | SIGIR | Learning Embeddings for Product Size Recommendations. | Kallirroi Dogani, Matteo Tomassetti, Sal Vargas, Benjamin Paul Chamberlain, Sofie De Cnudde |
| 2018 | KDD | Product Characterisation towards Personalisation: Learning Attributes from Unstructured Data to Recommend Fashion Products. | ngelo Cardoso, Fabio Daolio, Sal Vargas |
| 2017 | WSDM | Building recommender systems for scholarly information. | Maya Hristakeva, Daniel Kershaw, Marco Rossetti, Petr Knoth, Benjamin Pettit, Sal Vargas, Kris Jack |
| 2017 | WSDM | Effectively identifying users' research interests for scholarly reference management and discovery. | Marco Rossetti, Sal Vargas, Davide Magatti, Benjamin Pettit, Daniel Kershaw, Maya Hristakeva, Kris Jack |
| 2016 | RecSys | Mendeley: Recommendations for Researchers. | Sal Vargas, Maya Hristakeva, Kris Jack |
| 2016 | WSDM | Term-by-Term Query Auto-Completion for Mobile Search. | Sal Vargas, Roi Blanco, Peter Mika |
| 2015 | RecSys | Analysing Compression Techniques for In-Memory Collaborative Filtering. | Sal Vargas, Craig Macdonald, Iadh Ounis |
| 2014 | RecSys | Coverage, redundancy and size-awareness in genre diversity for recommender systems. | Sal Vargas, Linas Baltrunas, Alexandros Karatzoglou, Pablo Castells |
| 2014 | SIGIR | Novelty and diversity enhancement and evaluation in recommender systems and information retrieval. | Sal Vargas |