Creating and sharing knowledge for telecommunications
... Alexandra Sofia Martins de Carvalho

Researcher

Alexandra Carvalho

Academic position: Assistant Professor
Joining date: 12-10-2011
Roles in IT: Researcher
Scientific Area: Networks and Multimedia
Group: Pattern and Image Analysis – Lx

Email: Send Email
Address: IT – Lisboa
Instituto Superior Técnico - Torre Norte - Piso 10
Av. Rovisco Pais, 1
1049 - 001 Lisboa
Tel: +351 21 841 84 54
Fax: +351 21 841 84 72

Personal page


Scientific Achievements

  • PhD, Instituto Superior Técnico, 01-01-2011
  • MSc, Instituto Superior Técnico, 01-01-2004
  • Licenciatura, Instituto Superior Técnico, 01-01-1998
  • Machine Learning
  • Algorithmics
  • Bioinformatics
  • Instituto Superior Técnico, 01-01-2011,
  • Instituto Superior Técnico, 01-01-2006,
Supervision of theses
  • Mining electronic medical records for early classification of rheumatoid arthritis, MSc Student, Guilherme Reis de Moura, 05-2019
  • Profiling rheumatoid arthritis disease progression through data mining techniques, MSc Student, José Pedro de Almeida Gabriel Vieira Borges, 05-2019
  • Precision medicine with electronic medical records, MSc Student, Manuel Pereira da Conceição Monteiro Anacleto, 05-2019
  • Genetic programming for survival prediction, MSc Student, Miguel Ângelo Palma Pereira, 05-2019
  • Feature selection for high longitudinal data using elastic net, MSc Student, Xia Anbang, 05-2019
  • Outlier detection for multivariate time series, MSc Student, Jorge Luís Fuzeta Serras, 11-2018
  • Unveiling Interpretable Behaviour in Two-Way High-Dimensional Clinical Data, MSc Student, Luís Bernardo de Brito Mendes Rei, 11-2018
  • Network-based Regularisation for Survival Analysis, MSc Student, Pedro Jorge Estrela Martinho, 11-2018
  • Probabilistic Modelling of Single-cell Transcriptomics, MSc Student, Pedro Miguel Falé Ferreira, 11-2018
  • Model-based Learning in Multivariate Time Series, MSc Student, Samuel David Pelaio Arcadinho, 11-2018
  • Unravelling breast and prostate common gene signatures by Bayesian network learning, MSc Student, João Araújo Delgado Vila de Brito, 07-2018
  • Temporal sequence alignment and agglomerative clustering for the analysis of medical longitudinal data, MSc Student, Kishan Rameshchandra Rama, 06-2018
  • Profiling the Amyotrophic Lateral Sclerosis disease progression through data mining techniques, MSc Student, Orlando Bastos Vaz, 06-2018
  • Multivariate Correlations for Early Classification, MSc Student, João Pedro Carriço Beirão, 05-2018
  • Genetic programming for time series forecasting, MSc Student, Frederico Borges Costa Coelho Nunes, 04-2018
  • Modelling cancer progression through joint models for longitudinal and time-to-event data, MSc Student, Hugo Daniel Paes Loureiro Santos Ambrósio, 12-2017
  • Advances in Probabilistic Graphical Models, MSc Student, Margarida Nunes de Almeida Rodrigues de Sousa, 12-2017
  • Feature analysis to predict treatment outcome in rheumatoid arthritis, MSc Student, Cátia Sofia Tadeu Botas, 11-2017
  • Model Selection for Clustering of Pharmacokinetic Responses with the Minimum Description Length, MSc Student, Rui Pedro Pimentel de Almeida Guerra, 11-2017
  • Biclustering-based imputation in longitudinal data, MSc Student, Inês Nolasco, 05-2015
  • Analysis of Electronic Medical Records of Rheumatoid Arthritis Patients on Biological Therapies, MSc Student, João Pedro Bento Machado Marques de Freitas, 05-2015
  • Outlier Detection in Survival Analysis, MSc Student, João Pinto, 05-2015
  • Prognostic prediction in patients with Amyotrophic Lateral Sclerosis using graphical models, MSc Student, José Jorge dos Reis, 11-2014
  • Learning from short multivariate time series, MSc Student, José Maria Líbano Monteiro, 11-2014
  • Learning from imbalanced data, MSc Student, Cecília Nunes, 12-2012
  • M. Sousa, A. M. Carvalho, Learning consistent tree-augmented dynamic Bayesian networks, Chapter in, The 4th International Conference on Machine Learning, Optimization and Data Science, Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida, Renato Umeton, Vincenzo Sciacca, Springer, Cham, 2018
  • J. Brito, M. Lopes, A. M. Carvalho, S. Vinga, Unravelling breast and prostate common gene signatures by Bayesian network learning, Chapter in, Computational Intelligence methods for Bioinformatics and Biostatistics, Springer, Cham, 2018
  • P. Ferreira, A. M. Carvalho, S. Vinga, Variational inference in probabilistic single-cell RNA-seq models, Chapter in, Computational Intelligence methods for Bioinformatics and Biostatistics, Springer, Cham, 2018
  • J. D. Pinto, A. M. Carvalho, S. Vinga, Outlier Detection in Cox Proportional Hazards Models Based on the Concordance c-Index, Chapter in, Machine Learning, Optimization, and Big Data - Revised Selected Papers, pages 252-256, Springer International Publishing, Cham, 2015
  • C. Nunes, D. Silva, M. Guerreiro, A. de Mendonça, A. M. Carvalho, S. Madeira, Class imbalance in the prediction of dementia from neuropsychological data, Chapter in, Portuguese Conference on Artificial Intelligence, volume 8154 of Lecture Notes in Computer Science, pages 138-151, Luis Miguel Correia, Luís Paulo Reis and José Manuel Cascalho, Springer, Angra do Heroísmo, Açores, 2014
  • A. M. Carvalho, A. L. Oliveira, M.-F. Sagot Sagot, Efficient learning of Bayesian network classifiers: An extension to the TAN classifier, Chapter in, Australian Joint Conference on Artificial Intelligence, volume 4830 of Lecture Notes in Artificial Intelligence, pages 16-25, M. A. Orgun and J. Thornton, Springer, Gold Coast, Australia, 2007
  • N. Pisanti, A. M. Carvalho, L. Marsan, M.-F. Sagot Sagot, RISOTTO: Fast extraction of motifs with mismatches, Chapter in, Latin American Theoretical Informatics Symposium, volume 3887 of Lecture Notes in Computer Science, pages 757-768, J. R. Correa, A. Hevia and M. Kiwi, Springer, Valdivia, Chile, 2006
  • A. M. Carvalho, A. L. Oliveira, M.-F. Sagot Sagot, A highly scalable algorithm for the extraction of cis-regulatory regions, Chapter in, Asia Pacific Bioinformatics Conference, volume 1 of Advances in Bioinformatics and Computational Biology, pages 273-282, Yi-Ping Phoebe Chen and Limsoon Wong, Singapore, 2005
  • A. M. Carvalho, A. L. Oliveira, M.-F. Sagot Sagot, Efficient extraction of structured motifs using box-links, Chapter in, Symposium on String Processing and Information Retrieval, volume 3246 of Lecture Notes in Computer Science, pages 267-268, A. Apostolico and M. Melucci, Springer, Padova, Italy, 2004
  • H. Loureiro, E. Carrasquinha, I. Alho, A. Ferreira, L. Costa, A. M. Carvalho, S. Vinga, Modelling cancer outcomes of bone metastatic patients: combining survival data with N-Telopeptide of type I collagen (NTX) dynamics through joint models, BMC Medical Informatics and Decision Making, Vol. 19, No. 13, pp. 1 - 12, January, 2019 | BibTex
  • R. Guerra, A. M. Carvalho, P. Mateus, Model Selection for Clustering of Pharmacokinetic Responses, Computer Methods and Programs in Biomedicine, Vol. 162, No. 2018, pp. 11 - 18, August, 2018 | BibTex
  • M. Sousa, A. M. Carvalho, Polynomial-Time Algorithm for Learning Optimal BFS-Consistent Dynamic Bayesian Networks, Entropy, Vol. 20, No. 4, pp. 274 - 274, April, 2018 | BibTex
  • E. Tomás, S. Vinga, A. M. Carvalho, Unsupervised learning of pharmacokinetic responses, Computational Statistics, Vol. 32, No. 2, pp. 409 - 428, June, 2017 | BibTex
  • A. M. Carvalho, P. Adão, P. Mateus, Hybrid learning of Bayesian multinets for binary classification, Pattern Recognition, Vol. 47, No. 10, pp. 3438 - 3450, April, 2014 | BibTex
  • A. M. Carvalho, P. Adão, P. Mateus, Efficient Approximation of the Conditional Relative Entropy with Applications to Discriminative Learning of Bayesian Network Classifiers, Entropy, Vol. 15, No. 7, pp. 2716 - 2735, July, 2013 | BibTex
  • S. Vinga, A. M. Carvalho, A. P. Francisco, L. M. S. Russo, J. S. Almeida, Pattern matching through Chaos Game Representation: bridging numerical and discrete data structures for biological sequence analysis, Algorithms for Molecular Biology, Vol. 7, No. 10, pp. 1 - 12, May, 2012 | BibTex
  • A. M. Carvalho, T. Roos, A. L. Oliveira, P. Myllymäki, Discriminative learning of Bayesian networks via factorized conditional log-likelihood, Journal of Machine Learning Research, Vol. 12, No. Jul, pp. 2181 - 2210, July, 2011 | BibTex
  • A. M. Carvalho, A. L. Oliveira, GRISOTTO: A greedy approach to improve combinatorial algorithms for motif discovery with prior knowledge, Algorithms for Molecular Biology, Vol. 6, No. 13, pp. 0 - 0, April, 2011 | BibTex
  • P. T. Monteiro, N. D. Mendes, M. C. Teixeira, S. Orey, S. Tenreiro, N. Mira, A. P. Francisco, A. M. Carvalho, A. B. Lourenço, I. Sá-Correia, YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in Saccharomyces cerevisiae, Nucleic Acids Research, Vol. 36, No. Database-Issue, pp. 132 - 136, October, 2008 | BibTex
  • A. M. Carvalho, A. L. Oliveira, M.-F. Sagot Sagot, An Efficient Algorithm for the Identification of Structured Motifs in DNA Promoter Sequences, IEEE/ACM Trans. on Computational Biology and Bioinformatics, Vol. 3, No. 2, pp. 126 - 140, April, 2006 | BibTex
  • J. L. Monteiro, S. Vinga, A. M. Carvalho, Polynomial-time algorithm for learning optimal tree-augmented dynamic Bayesian networks, Conference on Uncertainty in Artificial Intelligence, Amsterdam, Netherlands, Vol. 31, pp. 622 - 631, July, 2015 | BibTex
  • J. D. Pinto, A. M. Carvalho, S. Vinga, Outlier detection in survival analysis based on the concordance c-index, BIOINFORMATICS, Lisbon, Portugal, Vol. 6, pp. 75 - 82, January, 2015 | BibTex
  • A.V.C. Carreiro, S. Pinto, A. M. Carvalho, M. C. Carvalho, S. Madeira, Predicting non-invasive ventilation in ALS patients using time windows, ACM SIGKDD Workshop on Healthcare Informatics HI-KDD, New York, United States, Vol. 20, pp. 1 - 8, August, 2014 | BibTex
  • A. M. Carvalho, A. L. Oliveira, Learning Bayesian networks consistent with the optimal branching, International Conf. on Machine Learning and Applications - ICMLA, Ohio, United States, Vol., pp. 369 - 374, December, 2007 | BibTex
  • A. M. Carvalho, A. L. Oliveira, M.-F. Sagot Sagot, A parallel algorithm for the extraction of structured motifs, ACM Symp. on Appl. Computing, Nicosia, Cyprus, Vol., pp. 147 - 153, March, 2004 | BibTex

Currently running projects3

Acronym Name Funding Agency Start date Ending date
NEUROCLINOMICS2 Unravelling Prognostic Markers in NEUROdegenerative diseases through CLINical and OMICS data integration FCT 01-07-2016 01-06-2019
PERSEIDS Personalizing cancer therapy through integrated modeling and decision FCT 17-06-2016 16-12-2019
PREDICT Personalized therapy for RhEumatic DIseases via machine learning methods FCT 01-01-2019 31-12-2021

Closed Projects1

Acronym Name Funding Agency Start date Ending date
CancerSys Multiscale modeling for personalized therapy of bone metastasis FCT 01-04-2014 01-10-2015
  • S. Vinga, A. M. Carvalho, A. P. Francisco, L. M. S. Russo, J. S. Almeida, Highly accessed article, for the paper, Pattern matching through Chaos Game Representation: Bridging numerical and discrete data structures for biological sequence analysis, by BioMed Central, 01-01-2012
  • A. M. Carvalho, A. L. Oliveira, Highly accessed article, for the paper GRISOTTO: A greedy approach to improve combinatorial algorithms for motif discovery with prior knowledge, by BioMed Central, 01-11-2011
  • N. D. Mendes, M. C. Teixeira, S. Orey, S. Tenreiro, N. Mira, H. Pais, A. P. Francisco, A. M. Carvalho, A. B. Lourenço, Sartorius award, Inovation in Microbiology/Biotecnology, for the work that lead to the article YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in Saccharomyces cerevisiae, at Micro-Biotec 2007, 01-01-2007
  • A. M. Carvalho, Diploma Thesis award, PRODEP program 5/5.2/207/011/PRODEP/98, 01-02-1998
  • Machine Learning, Optimization, and Data Science LOD, Technical Programme Committee, 2018
  • Portuguese Conf. on Artificial Intelligence - EPIA, Technical Programme Committee, 2013
  • European Conf. on Machine Learning - ECML, Technical Programme Committee, 2012
  • Bioinformatics
    2012, 1 review(s);
  • Machine Learning
    2012, 1 review(s);
  • Journal of Machine Learning Research
    2012, 1 review(s);
  • Formal Aspects of Computing
    2013, 1 review(s);
  • IEEE Trans. on Knowledge and Data Engineering
    2013, 1 review(s);
  • European Conf. on Machine Learning - ECML
    2012, 1 review(s);
  • Portuguese Conf. on Artificial Intelligence - EPIA
    2013, 1 review(s);