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
Thematic Line: Information and Data Sciences
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
  • Instituto Superior Técnico, 01-01-2011,
  • Instituto Superior Técnico, 01-01-2006,
  • Machine Learning
  • Algorithmics
  • Bioinformatics
As Supervisor
  • 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, 2020
  • 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, 2020
  • M. Anacleto, S. Vinga, A. M. Carvalho, MSAX: Multivariate symbolic aggregate approximation for time series classification, Chapter in, Computational Intelligence methods for Bioinformatics and Biostatistics, Cazzaniga P., Besozzi D., Merelli I., Manzoni L., Springer, Cham, 2020
  • A. M. Carvalho, S. Vinga, Sparse Consensus Classification for Discovering Novel Biomarkers in Rheumatoid Arthritis, Chapter in, Machine Learning, Optimization, and Data Science, Giuseppe NicosiaVarun OjhaEmanuele La MalfaGiorgio JansenVincenzo SciaccaPanos PardalosGiovanni GiuffridaRenato Umeton, Springer, Cham, 2020
  • 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. 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
  • M. Lemus, J. Beirão, N. Paunkovic, A. M. Carvalho, P. Mateus, Information-Theoretical Criteria for Characterizing the Earliness of Time-Series Data, Entropy, Vol. 22, No. 1, pp. 49 - 49, January, 2020 | BibTex
  • K. Rama, H. Canhão, A. M. Carvalho, S. Vinga, AliClu - Temporal sequence alignment for clustering longitudinal clinical data, BMC Medical Informatics and Decision Making, Vol. 19, No. 1, pp. 1 - 11, December, 2019 | BibTex
  • 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 Transactions 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 projects2

Acronym Name Funding Agency Start date Ending date
LAY(RF)^2 Ready-to-Fabricate RF and mmWave Integrated Circuit Layouts IT 01-02-2020 31-01-2022
PREDICT Personalized therapy for RhEumatic DIseases via machine learning methods FCT 01-01-2019 31-12-2021

Closed Projects3

Acronym Name Funding Agency Start date Ending date
CancerSys Multiscale modeling for personalized therapy of bone metastasis FCT 01-04-2014 01-10-2015
NEUROCLINOMICS2 Unravelling Prognostic Markers in NEUROdegenerative diseases through CLINical and OMICS data integration FCT 01-07-2016 31-03-2020
PERSEIDS Personalizing cancer therapy through integrated modeling and decision FCT 17-06-2016 16-12-2019
  • 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 Transactions 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);