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In 2021, Carla Silva was granted a doctorate in computer science by the Faculty of Sciences at the University of Porto (FCUP). After, in brief - postdoctoral fellow at the Research Center for Systems and Technologies (SYSTEC) and the Institute of Systems and Robotics (ISR-Porto) and principal researcher at the Institute of Science and Innovation in Mechanical and Industrial Engineering (INEGI). She has participated in projects both in industry (e.g., Fabamaq, Bosch) and research institutions, namely as a scientific programmer, data scientist, and researcher. In the past, she did Erasmus at the Leiden Institute of Advanced Computer Science (LIACS), Leiden University, The Netherlands. She also has academic experience as a research fellow at the Centre for Research in Advanced Computing Systems (CRACS INESC TEC), Portugal; Centre for Health Technology and Services Research (CINTESIS), Department of Community Medicine Information and Decision in Health, Portugal; Instituto de Telecomunicaçoes (IT), Portugal; Department of Computer Science, Faculty of Sciences, Porto University (DCC-FCUP); Department of Industrial Engineering and Management (DEGI), Faculty of Engineering of the University of Porto (FEUP). Her research interests include many aspects of computer science, e.g., artificial intelligence, data science, and machine learning, and the development of algorithms for multiple applications through a data-driven strategy to derive knowledge from data.
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Identificação

Identificação pessoal

Nome completo
Carla Maria Alves Pereira da Silva

Nomes de citação

  • Silva, C
  • Carla Silva
  • Silva, Carla
  • C Silva

Identificadores de autor

Ciência ID
5D1C-C504-DE39
ORCID iD
0000-0002-4941-1009
AuthenticusID
R-00G-YNK
Google Scholar ID
qzLi-IwAAAAJ&hl
Researcher Id
A-3382-2012
Scopus Author Id
56263913400

Domínios de atuação

  • Ciências Exatas - Ciências da Computação e da Informação

Idiomas

Idioma Conversação Leitura Escrita Compreensão Peer-review
Português (Idioma materno)
Inglês Utilizador proficiente (C2) Utilizador proficiente (C2) Utilizador proficiente (C2) Utilizador proficiente (C2) Utilizador proficiente (C2)
Formação
Grau Classificação
2017/06/05 - 2021/11/25
Concluído
 Ciência de Computadores (Doutoramento)
Universidade do Porto Faculdade de Ciências, Portugal
"Quantum Machine Intelligence: Mapping AI Applications" (TESE/DISSERTAÇÃO)
 Aprovado
2007
Concluído
 Ciências de Engenharia - Perfil de Engenharia Geográfica (Licenciatura)
Universidade do Porto Faculdade de Ciências, Portugal
Projetos

Bolsa

Designação Financiadores
2020/03/01 - 2021/08 Safe Cities - Inovação para Construir Cidades Seguras
POCI-01-0247-FEDER-041435 (Safe Cities)
Bolseiro de Investigação
Concluído
2019/01 - 2019/08 S2MovingCity: Sensing and Serving a Moving City
CMUP-ERI/TIC/0010/2014
Bolseiro de Investigação
Concluído
2017/11/15 - 2018/12 SmartCityMules - Mobile Data Collection and Dissemination Through Vehicular Delay Tolerant Networks
PTDC/EEI-TEL/2008/2014
Bolseiro de Investigação
Concluído
2016/08/01 - 2017/03 NanoSTIMA - Macro-to-Nano Human Sensing Technologies
NORTE-01-0145-FEDER-000016
Bolseiro de Investigação
Concluído
2014/06/01 - 2015/12 INCENTIVO PESt (CRACS)
1009/BI_B1C/ 14
Bolseiro de Investigação
Concluído

Outro

Designação Financiadores
2022/08/18 - 2022/11/30 Desenvolvimento e Implementação de Algoritmos para Processamento de Dados provenientes de Sistemas de Produção e de Automação
RH CT CEECInst 22/2022 – LAETA LA/P/0079/2020
Investigador
Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia, Portugal
Produções

Publicações

Artigo em conferência
  1. Silva, C; Rodrigues, A; Jorge, A; Dutra, I. "Sensor data modeling with Bayesian networks". 2022.
    10.1109/iaict55358.2022.9887461
  2. Nejad, EB; Silva, C; Rodrigues, A; Jorge, A; Dutra, I. "AutoSW: A new automated sliding window-based change point detection method for sensor data". 2022.
    10.1109/iaict55358.2022.9887400
  3. Silva, C; da Silva, MF; Rodrigues, A; Silva, J; Costa, VS; Jorge, A; Dutra, I. "Predictive Maintenance for Sensor Enhancement in Industry 4.0". 2021.
    10.1007/978-981-16-1685-3_33
  4. Silva, C; d'Orey, PM; Aguiar, A. "Visual Analysis of Multivariate Urban Traffic Data Resorting to Local Principal Curves". 2019.
    10.2312/mlvis.20191159
  5. Silva, C; d'Orey, PM; Aguiar, A. "Interpreting Traffic Congestion Using Fundamental Diagrams and Probabilistic Graphical Modeling". 2018.
    10.1109/icdmw.2018.00090
  6. Rodrigues, A.; Silva, C.; Borges, P.; Silva, S.; Dutra, I.. "Performance evaluation of statistical functions". 2016.
    10.1109/SmartCity.2015.159
  7. Silva, C.; Pereira, W.; Knotek, J.; Campos, P.. "Evolutionary dynamics of the spatial prisoner's dilemma with single and multi-behaviors: A multi-agent application". 2011.
    10.1007/978-3-642-14788-3_49
Artigo em revista
  1. Azevedo, V; Silva, C; Dutra, I. "Quantum transfer learning for breast cancer detection". QUANTUM MACHINE INTELLIGENCE (2022):
    10.1007/s42484-022-00062-4
  2. Silva, C; Aguiar, A; Lima, PMV; Dutra, I. "Mapping a logical representation of TSP to quantum annealing". QUANTUM INFORMATION PROCESSING (2021):
    10.1007/s11128-021-03321-8
  3. Fernandes, D; Silva, C; Dutra, I. "Erratum: Using Grover's search quantum algorithm to solve Boolean satisfiability problems, part 2". ACM Crossroads (2020):
    10.1145/3368085
  4. Silva, C; Aguiar, A; Lima, PMV; Dutra, I. "Mapping graph coloring to quantum annealing". QUANTUM MACHINE INTELLIGENCE (2020):
    10.1007/s42484-020-00028-4
  5. Fernandes, D; Silva, C; Dutra, I. "Using Grover's search quantum algorithm to solve Boolean satisfiability problems, part 2". ACM Crossroads (2019):
    10.1145/3386233
  6. Rodrigues, Andre; Silva, Carla; Borges, PauloViniciusKoerich; Silva, Sergio; Dutra, Ines. "Optimising the calculation of statistical functions". IJBDI (2017):
  7. Silva, C. "What is Quantum AI?". ITNOW (2017):
    10.1093/itnow/bwx119
Poster em conferência
  1. Silva, Carla. "Exploring extrapolation for molecular dissociation profiles". Trabalho apresentado em MLQ2021: Machine Learning for Quantum, 2021.
  2. Silva, Carla. "Towards an Applied Quantum Machine Learning in Intelligent Transportation Systems". Trabalho apresentado em CIÊNCIA'19 - Encontro com a Ciência e Tecnologia em Portugal, Centro de Congressos de Lisboa, 2019., 2019.
  3. Silva, Carla; Dutra, Inês; Dahlem, MS. "Simulating Markov transition probabilities in a quantum environment". Trabalho apresentado em 3rd International Conference for Young Quantum Information Scientists 3-6 October 2017, Max Planck Institute for the Science of Light, Friedrich-Alexander Universitat Erlangen-Nurnberg, 2017, 2017.
  4. Silva, Carla; Lobo, Mariana; Pedro P Rodrigues. "Exploring multimorbidity using Bayesian models with time-based abstractions". Trabalho apresentado em Informatics for Health 2017: Advancing both science and practice, 2017.
Resumo em conferência
  1. Silva, C; Aguiar, A; Dutra, I. "Quantum Binary Classification (Student Abstract)". Trabalho apresentado em The Thirty-Fifth AAAI Conference on Artificial Intelligence, February 2-9, 2021, held virtually, 2021.
    Publicado

Outros

Outra produção
  1. Driven tabu search: a quantum inherent optimisation. 2018. Silva, C; Dutra, I; Dahlem, MS.
Atividades

Apresentação oral de trabalho

Título da apresentação Nome do evento
Anfitrião (Local do evento)
2022/07/29 Sensor data modeling with Bayesian networks The IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology
(Bali (held online), Indonésia)
2021/04/08 Predictive Maintenance for Sensor Enhancement in Industry 4.0 Recent Challenges in Intelligent Information and Database Systems - 13th Asian Conference, ACIIDS 2021, Phuket, Thailand, April 7-10, 2021
(Phuket (held online), Tailândia)
2019/06/07 Urban Traffic Visualization UT Austin Portugal Applied Visualization Workshop 7-8 June
(Braga, Portugal)
2019/06/03 Visual Analysis of Multivariate Urban Traffic Data Resorting to Local Principal Curves 2nd Workshop on Machine Learning Methods in Visualisation for Big Data, Mlvis@eurovis 2019, Porto, Portugal, June 3, 2019, 3 June 2019, Sponsors EUROGRAPHICS Association
(Porto, Portugal)
2018/08/20 Driven Tabu Search: A Quantum Inherent Optimisation 1st Workshop on Quantum Machine Learning of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2018, London, UK, August 19-23, 2018
(Londres, Reino Unido)

Organização de evento

Nome do evento
Tipo de evento (Tipo de participação) 		Instituição / Organização
2020 - 2020 SMBQ 2020 - Summer School on Machine Learning and Big Data with Quantum Computing (2020/09/07 - 2020/09/08) Universidade do Porto Faculdade de Ciências, Portugal

Entrevista (jornal / revista)

Descrição da atividade Jornal / Forum
2019/09/27 (DIZ) Connect. Interview in the scope of former INESC TEC employees describing professional trajectories. BIP - INESC TEC Magazine

Revisão ad hoc de artigos em revista

Nome da revista (ISSN) Editora
2023 - 2023 The Journal of Supercomputing Springer
2022 - 2023 Quantum Machine Intelligence Springer Nature
2019 - 2020 IEEE Internet of Things Journal IEEE - Institute of Electrical and Electronics Engineers Inc
Distinções

Prémio

2022 Medal (doctorates) in the computer science category.
Universidade do Porto Faculdade de Ciências, Portugal