Since February 2020 I am on leave from UPC and full time at Amalfi Analytics. The UPC email address will continue working. I will not be able to take any interns or PhD students in the foreseeable future.
I work at the Department of Computer Science of Universitat Politècnica de Catalunya - BarcelonaTech (UPC). I belong to the LARCA research group.
My research is on Machine Learning and Data Mining, both in their algorithmic aspects and their applications. I am particularly interested in the applications of Data Science to Social Good.
I am co-founder of Amalfi Analytics. We create data analytic platforms for the management of complex healthcare systems.
News:
- March 6th, 2020: Rafael Mena-Yedra defended his PhD thesis, on using Machine Learning for traffic prediction. an industrial doctorate on traffic prediction and management at Aimsun, co-supervised with Jordi Casas.
- Feb 5th, 2020: I start an academic leave to go full time in Amalfi Analytics. Quite a change after 30+ years in UPC!
- Jan 20: Our data streams book has a Chinese translation!
- October 19: Paper Probabilistic model for robust traffic state identification in urban networks with Rafael Mena and Jordi Casas, presented at 2019 IEEE Intelligent Transportation Systems Conference (ITSC).
- June 19: Paper Interpretable Patient Trajectories from Temporally Annotated Health Records with Martí Zamora, presented at 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)
- Sept 1st, 2019: Check the program of the 4th Workshop on Data Science for Social Good (SoGood 2019).
- Feb 14th, 2019: Matteo Ruffini defends his Ph.D. thesis "Learning Latent Variable Models: Efficient Algorithms and Applications". A honor to have been his supervisor.
- Feb 2019: Amalfi Analytics is one of the 20 Catalan startups to receive a 75Keuro ACCIO Startup Capital grant
- Jan 2019: My student Martí Zamora gets an industrial doctorate grant to carry out his PhD at Amalfi Analytics. Topic: analysis of temporally annotated healthcare records.
- November 2018: Pipeline design to identify key features and classify the chemotherapy response on lung cancer patients using large-scale genetic data. María Gabriela Valdés, Iván Galván-Femenía, Vicent Ribas Ripoll, Xavier Duran, Jun Yokota, Ricard Gavaldà, Xavier Rafael-Palou and Rafael de Cid. BMC Systems Biology 2018 12 (Suppl 5):97.
- October 2018: You can now access the online html version of the data streams book, and add comments / questions / remarks / requests on a paragraph basis.. Authors will check periodically and reply. By the way, the book site contains course slides, exercises, lab work, etc. You are welcome to distribute!
- September 2018: Co-organizer of the 3rd Workshop on Data Science for Social Good associated to ECML PKDD 2018, in Dublin. Unfortunately I could not attend.
- August 2018: Generating Synthetic but Plausible Healthcare Record Datasets. Laura Aviñó, Matteo Ruffini, Ricard Gavaldà. Presented at the Workshop on Machine Learning for Medicine and Healthcare (MLMH 2018), held within KDD 2018. An application of Matteo's work on clustering via tensor decomposition to generating synthetic datasets.
