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Fernández-Macías, E., Gomez E., Hernández-Orallo J., Loe B. - S., Martens B., Martínez-Plumed F., et al. (2018).  A multidisciplinary task-based perspective for evaluating the impact of AI autonomy and generality on the future of work. Workshop on architectures and evaluation for generality, autonomy and progress in AI, IJCAI-ECAI 2018, AAMAS 2018 AND ICML 2018.
Gomez, E., Blaauw M., Bonada J., Chandna P., & Cuesta H. (2018).  Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners. Keynote speech, 2018 Joint Workshop on Machine Learning for Music. The Federated Artificial Intelligence Meeting (FAIM), a joint workshop program of ICML, IJCAI/ECAI, and AAMAS.
Cuesta, H., Gómez E., Martorell A., & Loáiciga F. (2018).  Analysis of Intonation in Unison Choir Singing. 15th International Conference on Music Perception and Cognition (ICMPC).
Slizovskaia, O., Gómez E., & Haro G. G. (2017).  Correspondence between audio and visual deep models for musical instrument detection in video recordings. 18th International Society for Music Information Retrieval Conference (ISMIR2017, LBD).
Chandna, P., Miron M., Janer J., & Gómez E. (2017).  Monoaural Audio Source Separation Using Deep Convolutional Neural Networks. 13th International Conference on Latent Variable Analysis and Signal Separation (LVA ICA2017).