Profesorado e Investigación
Directorio
Rodriguez Serrano, Jose A.
Profesor Asociado Sénior, Departamento de Operaciones, Innovación y Data Sciences en Esade
Profesor contratado doctor URL
Director acadèmic MSc in Business Analytics, Master Business Analytics
Formación académica
- Ciencias de la Computación. Universitat Autònoma de Barcelona
- Licenciado en Física. Universitat de Barcelona
Áreas de interés
- ODS 9: Industria, innovación e infraestructura
Publicaciones destacadas
- Rodriguez-Serrano, J. A. (2024). Prototype-based learning for real estate valuation: a machine learning model that explains prices. Annals of Operations Research. DOI: https://doi.org/10.1007/s10479-024-06273-1.
- Akoglu, L., Chawla, N., Domingo-Ferrer, J., Kurshan, E., Kumar, S., Naware, V., Rodriguez-Serrano, J. A., Chaturvedi, I., Nagrecha, S., Das, M. & Faruquie, T. (2024). Machine Learning in Finance. KDD 2024 - Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 6703). Association for Computing Machinery. DOI: https://doi.org/10.1145/3637528.3671488.
- Bueno, A., Rodriguez-Serrano, J. A., Torrens, M., Agell, N., Nguyen, J. T. V. & Agell, N. (2024, May). Poster: Using Deep Attention Multiple Instance Learning To Improve Malpractices Detection In The Health Sector [Paper presentation]. https://convin.gr/assets/files/misc/IALM2024_Abstract%CE%92ook.pdf
- Rodriguez-Serrano, J. A. (E-pub ahead of print). (2024). Prototype-based models for real estate valuation: a machine learning model that explains prices. Annals of Operations Research. DOI: https://doi.org/10.2139/ssrn.4695079.
- Brando, A., Gimeno, J., Rodriguez-Serrano, J. A. & Vitrià, J. (2022). Deep Non-Crossing Quantiles through the Partial Derivative. Proceedings of Machine Learning Research, 151, pp. 7902-7914.
- Kumar, S., Akoglu, L., Chawla, N., Rodriguez-Serrano, J. A., Faruquie, T. & Nagrecha, S. (2021). Machine Learning in Finance. KDD 2021 - Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 4139-4140). Association for Computing Machinery. DOI: https://doi.org/10.1145/3447548.3469456.
- Brando, A., TORRES-LATORRE, C., Rodriguez-Serrano, J. A. & Vitrià, J. (2020). Building Uncertainty Models on Top of Black-Box Predictive APIs. IEEE Access, 8, pp. 121344-121356. DOI: https://doi.org/10.1109/ACCESS.2020.3006711.
- Brando, A., Rodriguez-Serrano, J. A., Ciprian, M., Maestre, R. & Vitrià, J. (2019). Uncertainty modelling in deep networks. In Brefeld, U., Marascu, A. & Pinelli, F., Curry, E., Macnamee, B., Hurley, N., Daly, E. (Eds.), Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Proceedings (pp. 325-340). Springer Verlag. DOI: https://doi.org/10.1007/978-3-030-10997-4_20.
- Brando, A., Rodriguez-Serrano, J. A., Vitrià, J. & Rubio, A. (2019). Modelling heterogeneous distributions with an uncountable mixture of asymmetric laplacians. Advances in Neural Information Processing Systems, 32.
- Tariq, U., Rodriguez-Serrano, J. A. & Perronnin, F. (2017). Unsupervised fisher vector adaptation for re-identification. Advances in Computer Vision and Pattern Recognition (9783319583464th ed., pp. 213-225). Springer London. DOI: https://doi.org/10.1007/978-3-319-58347-1_11.
- Dai, Z., Larlus, D. & Rodriguez-Serrano, J. A. (2016). Data-Driven Detection of Prominent Objects. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, pp. 1969-1982. DOI: https://doi.org/10.1109/TPAMI.2015.2509988.
- Gordo, A., Perronnin, F. & Rodriguez-Serrano, J. A. (2015). Label embedding: A frugal baseline for text recognition. DOI: https://doi.org/10.1007/s11263-014-0793-6.
- Chidlovskii, B., Csurka, G. & Rodriguez-Serrano, J. A. (2014). Vehicle type classification from laser scans with global alignment kernels. 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 (pp. 2840-2845). Institute of Electrical and Electronics Engineers Inc.. DOI: https://doi.org/10.1109/ITSC.2014.6958145.
- Ferryman, J., Hogg, D., Sochman, J., Behera, A., Rodriguez-Serrano, J. A., Worgan, S., Li, L., Leung, V., Evans, M., Cornic, P., Herbin, S., Schlenger, S. & Dose, M. (2013). Robust abandoned object detection integrating wide area visual surveillance and social context. Pattern Recognition Letters, 34 (7), pp. 789-798. DOI: https://doi.org/10.1016/j.patrec.2013.01.018.
- Rodriguez-Serrano, J. A. & Perronnin, F. (2013, January). Label embedding for text recognition [Paper presentation]. 2013 24th British Machine Vision Conference, BMVC 2013, Bristol. http://www.scopus.com/inward/record.url?scp=84898493831&partnerID=8YFLogxK
- Mo, X., Monga, V., Bala, R., Rodriguez-Serrano, J. A., Fan, Z. & Burry, A. (2013). Practical methods for sparsity based video anomaly detection. 2013 16th International IEEE Conference on Intelligent Transportation Systems (pp. 955-960). DOI: https://doi.org/10.1109/ITSC.2013.6728355.
- Sandhawalia, H., Rodriguez-Serrano, J. A., Poirier, H. & Csurka, G. (2013). Vehicle type classification from laser scanner profiles. 2013 16th International IEEE Conference on Intelligent Transportation Systems (pp. 517-522). DOI: https://doi.org/10.1109/ITSC.2013.6728283.
- Perronnin, F. & Rodriguez-Serrano, J. A. (2012). A model-based sequence similarity with application to handwritten word spotting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34, pp. 2108-2120. DOI: https://doi.org/10.1109/TPAMI.2012.25.
- Rodriguez-Serrano, J. A. & Singh, S. (2012). Trajectory clustering in CCTV traffic videos using probability product kernels with hidden Markov models. Pattern Analysis and Applications, 15 (4), pp. 415-426. DOI: https://doi.org/10.1007/s10044-012-0269-7.
- Rodriguez-Serrano, J. A. & Perronnin, F. (2012). Synthesizing queries for handwritten word image retrieval. Pattern Recognition, 45 (9), pp. 3270-3276. DOI: https://doi.org/10.1016/j.patcog.2012.02.015.
- Gordoa, A., Perronnin, F., Rodriguez-Serrano, J. A. & Valveny, E. (2012, June). Leveraging category-level labels for instance-level image retrieval [Paper presentation]. 2012 IEEE Conference on Computer Vision and Pattern Recognition, Providence.
- Rodriguez-Serrano, J. A. (2012). Handwritten word-spotting using hidden Markov models and universal vocabularies. Pattern Recognition, 42 (9), pp. 2106. DOI: https://doi.org/10.1016/j.patcog.2009.02.005.
- Bala, R., Zhao, Y., Burry, A., Kozitsky, V., Fillion, C., Saunders, C. & Rodriguez-Serrano, J. A. (2012). Image simulation for automatic license plate recognition. Proceedings of SPIE-IS and T Electronic Imaging - Visual Information Processing and Communication III (83050Z). DOI: https://doi.org/10.1117/12.912453.
- Rodriguez-Serrano, J. A., Sandhawalia, H., Bala, R., Perronnin, F. & Saunders, C. (2012). Data-driven vehicle identification by image matching. Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings (PART 2 ed., pp. 536-545). Springer Verlag. DOI: https://doi.org/10.1007/978-3-642-33868-7_53.
- Rodriguez-Serrano, J. A., Perronnin, F., Sánchez, G. & Lladós, J. (2010). Unsupervised writer adaptation of whole-word HMMs with application to word-spotting. Pattern Recognition Letters, 31 (8), pp. 742-749. DOI: https://doi.org/10.1016/j.patrec.2010.01.007.
- Rodriguez-Serrano, J. A., Perronnin, F., Lladós, J. & Sánchez, G. (2009). A similarity measure between vector sequences with application to handwritten word image retrieval. 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009 (pp. 1722-1729). IEEE Computer Society. DOI: https://doi.org/10.1109/CVPRW.2009.5206783.
- Rodriguez-Serrano, J. A. & Perronnin, F. (2009). Handwritten word-image retrieval with synthesized typed queries. ICDAR2009 - 10th International Conference on Document Analysis and Recognition (pp. 351-355). DOI: https://doi.org/10.1109/ICDAR.2009.201.
- Perronnin, F. & Rodriguez-Serrano, J. A. (2009). Fisher kernels for handwritten word-spotting. ICDAR2009 - 10th International Conference on Document Analysis and Recognition (pp. 106-110). DOI: https://doi.org/10.1109/ICDAR.2009.16.
Datos de contacto
Tel: +34 932 806 162
Ext. 5503
Fax: +34 932 048 105
Ext. 5503
Fax: +34 932 048 105