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FC6 - Departamento de Ciência de Computadores FC5 - Edifício Central FC4 - Departamento de Biologia FC3 - Departamento de Física e Astronomia e Departamento GAOT FC2 - Departamento de Química e Bioquímica FC1 - Departamento de Matemática

Carla Silva

Fotografia de Carla Maria Alves Pereira da Silva
Name: Carla Maria Alves Pereira da Silva
Abbreviation: CMAPS
Status: Non active
R-00G-YNK
5D1C-C504-DE39
A-3382-2012
56263913400
Institutional Email: carlasilva@fe.up.pt

Duties

End Date: 31-08-2021
Bond: Bolsa -> Bolsa de investigação
Department: Department of Computer Science

Personal Presentation

Dr. Carla Silva graduated (2007) from the Faculty of Sciences, Porto University, Portugal. She received the PhD degree (2021) in Computer Science from the Faculty of Sciences, Porto University, Portugal. She was a postdoc fellow at SYSTEC - Research Center For Systems and Technologies and Institute of Systems and Robotic (ISR-Porto) in 2022. In the past, she has participated in projects both in industry and research institutions. She worked in the companies Fabamaq and Bosch as math software developer, data scientist and researcher. She did Erasmus at Leiden Institute of Advanced Computer Science (LIACS), Leiden University, The Netherlands. She has academic experience as a research fellow at CRACS INESC TEC - Center for Research in Advanced Computing Systems, Portugal; CINTESIS - Center for Health Technology and Services Research, Department of Community Medicine Information and Decision in Health, Portugal; Instituto de Telecomunicações (IT), Portugal; Department of Computer Science, Faculty of Sciences, Porto University, Portugal. Her research interests include many aspects of computer science, namely, artificial intelligence, data science and machine learning, and the development of algorithms for multiple applications. Her applied research focuses on data mining, data visualisation, quantum computation and quantum information, simulation and modelling, spatial and spatial-temporal statistics, Bayesian statistics, as well as, urban computing and dynamical systems through a data-driven strategy to derive knowledge.
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