Data and Systems Intelligence

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Description:

The research line on Data and Systems Intelligence strives to devise innovative solutions for applying artificial intelligence when analyzing and reasoning about large‐scale data problems and complex systems. The DSI research line intersects areas of recent high visibility and impact, namely Machine Learning and Data Mining, but also the general fields of Artificial Intelligence, Information Systems and Logic in Computer Science, and aims at advancing research and knowledge in the recent flagship application domains of Data Science and Web Science.

Targeted areas:

Data Science
Web Science
Data Mining
Machine Learning
Artificial Intelligence
Logic in Computer Science

Leader:

João Marques Silva

Research Line Members:

Name	Category
Alexey Ignatiev	Integrated Researcher
Alysson Bessani	Integrated Researcher
André Souto	Integrated Researcher
António Morgado	Integrated Researcher
Cátia Pesquita	Integrated Researcher
Fernando Ramos	Integrated Researcher
Francisco Couto	Integrated Researcher
Ibéria Medeiros	Integrated Researcher
João Marques Silva	Integrated Researcher
Pedro Ferreira	Integrated Researcher
Sara Madeira	Integrated Researcher
Tiago Guerreiro	Integrated Researcher
Telma Pereira	PhD Student
Filipe Pereira	MSc Student
Madalena Pavão	MSc Student
Nuno Dionísio	MSc Student
Sofia Pires	MSc Student

Software and Tools

Software and Tools:

Title	Short descritption
AgreementMakerLight	An automated and efficient ontology matching system derived from AgreementMaker that has been in development since the beginning of 2013
CESSM	An online tool for the automated evaluation of GO-based semantic similarity measures

Publications

2017

Journal Article

Sousa, J., Bessani A., & Vukolić M. (2017). A Byzantine Fault-Tolerant Ordering Service for the Hyperledger Fabric Blockchain Platform. arXiv preprint arXiv:1709.06921.

Lobo, M., Lamurias A., & Couto F. M. (2017). Identifying Human Phenotype Terms by Combining Machine Learning and Validation Rules. BioMed Research International. 2017,

Asif, M., Martiniano H. F., Rasga C., Marques A. R., Santos J. X., Couto F. M., et al. (2017). An integrative system biology approach to delineate complex genotype-phenotype associations in Autism Spectrum Disorder. 2nd BioSys Retreat 2017, 6-7 October, 2017.

Campos, L., & Couto F. (2017). MRA-Proof of Concept of a Multilingual Report Annotator Web Application. arXiv preprint arXiv:1704.01748.

Ignatiev, A., Morgado A., & Marques-Silva J. (2017). On Tackling the Limits of Resolution in SAT Solving. arXiv preprint arXiv:1705.01477.

Gaspar, D., Trindade C., Usié A., Meireles B., Barbosa P., Fortes A. M., et al. (2017). Expression Profiling in Pinus pinaster in Response to Infection with the Pine Wood Nematode Bursaphelenchus xylophilus. Forests. 8, 279.

Vlachou, C., Krawec W., Mateus P., Paunkovic N., & Souto A. (2017). Quantum key distribution with quantum walks. arXiv preprint arXiv:1710.07979.

Conference Paper

Ferreira, F. L., Cardoso S., Silva D., Guerreiro M., de Mendonça A., & Madeira S. C. (2017). Improving Prognostic Prediction from Mild Cognitive Impairment to Alzheimer’s Disease Using Genetic Algorithms. International Conference on Practical Applications of Computational Biology & Bioinformatics. 180–188.

Costa, P. A. R. S., Ramos F., & Correia M. (2017). Chrysaor: Fine-Grained, Fault-Tolerant Cloud-of-Clouds MapReduce. Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. 421–430.

Rodrigues, A., Santos A., Montague K., & Guerreiro T. (2017). Improving Smartphone Accessibility with Personalizable Static Overlays. Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility. 37–41.

LASIGE

Data and Systems Intelligence

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Research Line Members:

Software and Tools:

Journal Article

Conference Paper

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Data and Systems Intelligence

Line Tabs

Research Line Members:

Software and Tools:

Journal Article

Conference Paper

Pages

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