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Joana Peres (http://orcid.org/0000-0001-5165-2488) has a degree in Mathematics (1991), a branch of Scientific Specialization in Applied Mathematics from the Faculty of Sciences of the University of Porto (FCUP), has a Master's degree in Electrical and Computer Engineering (1996), Industrial Informatics branch of Faculty of Engineering of University of Porto (FEUP); and a PhD in Chemical Engineering (2005) from the University of Porto in the area of Hybrid Modular Networks applied to chemical and biological processes. Nowadays, she is an assistant professor at the Chemical Engineering Department of FEUP and a member of the Process Engineering, Environment, Biotechnology and Energy Laboratory (LEPABE). She has taught mathematics, statistics, and programming for almost twenty years. Her main research interests are multi-variable statistical models and hybrid models that combine phenomenological knowledge with statistical models applied to chemical and biological processes.
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Identificação

Identificação pessoal

Nome completo
Joana Peres

Nomes de citação

  • Peres, J.

Identificadores de autor

Ciência ID
AA14-1695-765E
ORCID iD
0000-0001-5165-2488
AuthenticusID
R-000-BTE
Scopus Author Id
35820227900

Idiomas

Idioma Conversação Leitura Escrita Compreensão Peer-review
Inglês Utilizador independente (B1) Utilizador independente (B1) Utilizador independente (B1) Utilizador independente (B1)
Projetos

Projeto

Designação Financiadores
2021/01/01 - 2025/12/31 ALICE - Laboratório Associado em Engenharia Química
LA/P/0045/2020
10.54499/LA/P/0045/2020
Investigador
Universidade do Porto Laboratorio de Engenharia de Processos Ambiente Biotecnologia e Energia, Portugal

Universidade do Porto Faculdade de Engenharia, Portugal

Universidade do Porto Centro de Estudos de Fenómenos de Transporte, Portugal

Universidade do Porto Laboratório de Processos de Separação e Reacção Laboratório de Catálise e Materiais, Portugal

Instituto Politécnico de Leiria, Portugal
Fundação para a Ciência e a Tecnologia
Em curso
2020/01/01 - 2023/12/31 Laboratório de Engenharia de Processos, Ambiente, Biotecnologia e Energia
UIDB/00511/2020
10.54499/UIDB/00511/2020
UIDP/00511/2020
10.54499/UIDP/00511/2020
Investigador
Universidade do Porto Laboratorio de Engenharia de Processos Ambiente Biotecnologia e Energia, Portugal

Universidade do Porto Faculdade de Engenharia, Portugal
Fundação para a Ciência e a Tecnologia
Concluído
2016/10/01 - 2020/12/31 Harvesting and storage of solar energy
SAICTPAC/0046/2015
Universidade de Coimbra, Portugal

Universidade Nova de Lisboa Associação para a Inovação e Desenvolvimento da FCT, Portugal

Universidade do Porto Faculdade de Engenharia, Portugal
Fundação para a Ciência e a Tecnologia
Concluído
2010/05 - 2013/10 SAFEPINE - assessment of contamination of forests by emerging pollutants
grant.Provided by PTCRIS: 102597
PTDC/AGR-CFL/102597/2008
Universidade do Porto Laboratorio de Engenharia de Processos Ambiente Biotecnologia e Energia, Portugal

Universidade do Porto Faculdade de Engenharia, Portugal
The Foundation for Science and Technology

Fundação para a Ciência e a Tecnologia
Concluído
2011/01/01 - 2012/12/31 Projecto Estratégico - UI 511 - 2011-2012
PEst-C/EQB/UI0511/2011
Universidade do Porto Laboratorio de Engenharia de Processos Ambiente Biotecnologia e Energia, Portugal

Universidade do Porto Faculdade de Engenharia, Portugal
Fundação para a Ciência e a Tecnologia
Concluído
2005/06/01 - 2007/12/31 Automação Avançada de Processos Biológicos Baseada em Sistemas Híbridos do Tipo Caixa Cinzenta
POCI/BIO/56571/2004
Instituto de Biologia Experimental e Tecnológica, Portugal

Universidade do Porto Faculdade de Engenharia, Portugal
Fundação para a Ciência e a Tecnologia
Concluído
Produções

Publicações

Artigo em conferência
  1. Oliveira, R.; Peres, J.; Feyo de Azevedo, S.. "Hybrid modelling of fermentation processes using artificial neural networks: A study on identification and stability". 2004.
  2. Peres, J.; Oliveira, R.; Feyo de Azevedo, S.. "Hybrid modelling of fermentation processes: A study on the use of modular neural networks for modelling cells reaction kinetics". 2004.
Artigo em revista
  1. Pedro A. S. Sousa; Joana Neto; Joana V. Barbosa; Joana Peres; Ana Magro; Graça Barros; José M. Sousa; et al. "Novel Approach for a Controlled Delivery of Essential Oils during Long-Term Maize Storage: Clove Bud and Pennyroyal Oils Efficacy to Control Sitophilus zeamais, Reducing Grain Damage and Post-Harvest Losses". Insects (2023): https://doi.org/10.3390/insects14040366.
    10.3390/insects14040366
  2. Rui Churro; Fernando Mendes; Paulo Araújo; Filipa Ribeiro; Joana Peres; Luís M. Madeira. "Statistical modelling of the amination reaction of cyclohexanol to produce cyclohexylamine over a commercial Ni-based catalyst". Chemical Engineering Research and Design (2021): https://doi.org/10.1016/j.cherd.2021.03.029.
    10.1016/j.cherd.2021.03.029
  3. Andreia S. Azevedo; Gislaine P. Gerola; João Baptista; Carina Almeida; Joana Peres; Filipe J. Mergulhão; Nuno F. Azevedo. "Increased Intraspecies Diversity in Escherichia coli Biofilms Promotes Cellular Growth at the Expense of Matrix Production". Antibiotics 9 11 (2020): 818-818. https://doi.org/10.3390/antibiotics9110818.
    10.3390/antibiotics9110818
  4. Sousa, Sérgio F.; Peres, Joana; Coelho, Manuel; Vieira, Tatiana F.. "Analyzing PEGylation through Molecular Dynamics Simulations". ChemistrySelect 3 29 (2018): 8415-8427. http://dx.doi.org/10.1002/slct.201800855.
    Publicado • 10.1002/slct.201800855
  5. De Azevedo, C.R.; Peres, J.; Von Stosch, M.. "An efficient method for the numerical integration of measured variable dependent ordinary differential equations". Engineering Applications of Artificial Intelligence 38 (2015): 24-33. http://www.scopus.com/inward/record.url?eid=2-s2.0-84916620113&partnerID=MN8TOARS.
    10.1016/j.engappai.2014.10.014
  6. von Stosch, M.; Oliveira, R.; Peres, J.; Feyo de Azevedo, S.. "Hybrid semi-parametric modeling in process systems engineering: Past, present and future". Computers and Chemical Engineering 60 (2013): 86-101. http://www.scopus.com/inward/record.url?eid=2-s2.0-84884346400&partnerID=MN8TOARS.
    10.1016/j.compchemeng.2013.08.008
  7. Von Stosch, M.; Oliveria, R.; Peres, J.; De Azevedo, S.F.. "Hybrid modeling framework for process analytical technology: Application to Bordetella pertussis cultures". Biotechnology Progress 28 1 (2012): 284-291. http://www.scopus.com/inward/record.url?eid=2-s2.0-84856575287&partnerID=MN8TOARS.
    10.1002/btpr.706
  8. Barreiros, L.; Peres, J.; Azevedo, N.F.; Manaia, C.M.; Nunes, O.C.. "Environmental factors influencing molinate biodegradation by a two-member mixed culture in rice paddy field floodwater". International Biodeterioration and Biodegradation 72 (2012): 52-58. http://www.scopus.com/inward/record.url?eid=2-s2.0-84861973594&partnerID=MN8TOARS.
    10.1016/j.ibiod.2012.05.003
  9. Von Stosch, M.; Oliveira, R.; Peres, J.; Feyo De Azevedo, S.. "A general hybrid semi-parametric process control framework". Journal of Process Control 22 7 (2012): 1171-1181. http://www.scopus.com/inward/record.url?eid=2-s2.0-84864311580&partnerID=MN8TOARS.
    10.1016/j.jprocont.2012.05.004
  10. Von Stosch, M.; Oliveira, R.; Peres, J.; Feyo De Azevedo, S.. "A novel identification method for hybrid (N)PLS dynamical systems with application to bioprocesses". Expert Systems with Applications 38 9 (2011): 10862-10874. http://www.scopus.com/inward/record.url?eid=2-s2.0-79955579227&partnerID=MN8TOARS.
    10.1016/j.eswa.2011.02.117
  11. von Stosch, M.; Peres, J.; de Azevedo, S.F.; Oliveira, R.. "Modelling biochemical networks with intrinsic time delays: A hybrid semi-parametric approach". BMC Systems Biology 4 (2010): http://www.scopus.com/inward/record.url?eid=2-s2.0-77956872192&partnerID=MN8TOARS.
    10.1186/1752-0509-4-131
  12. Peres, J.; Oliveira, R.; de Azevedo, S.F.. "Bioprocess hybrid parametric/nonparametric modelling based on the concept of mixture of experts". Biochemical Engineering Journal 39 1 (2008): 190-206. http://www.scopus.com/inward/record.url?eid=2-s2.0-43049156236&partnerID=MN8TOARS.
    10.1016/j.bej.2007.09.003
  13. Peres, J.; Freitas, F.; Reis, M.; Feyo de Azevedo, S.; Oliveira, R.. "Hybrid modular mechanistic/ANN modelling of a wastewater phosphorus removal process". Computer Aided Chemical Engineering 21 C (2006): 1717-1722. http://www.scopus.com/inward/record.url?eid=2-s2.0-77956759117&partnerID=MN8TOARS.
    10.1016/S1570-7946(06)80295-6
  14. Peres, J.; Oliveira, R.; Serafim, L.S.; Lemos, P.; Reis, M.A.; Feyo de Azevedo, S.. "Hybrid Modelling of a PHA Production Process Using Modular Neural Networks". Computer Aided Chemical Engineering 18 C (2004): 733-738. http://www.scopus.com/inward/record.url?eid=2-s2.0-77955639355&partnerID=MN8TOARS.
    10.1016/S1570-7946(04)80188-3
  15. Peres, J.; Oliveira, R.; Feyo de Azevedo, S.. "Modelling cells reaction kinetics with artificial neural networks: A comparison of three network architectures". Computer Aided Chemical Engineering 14 C (2003): 839-844. http://www.scopus.com/inward/record.url?eid=2-s2.0-77956737455&partnerID=MN8TOARS.
    10.1016/S1570-7946(03)80221-3
  16. Peres, J.; Oliveira, R.; Feyo De Azevedo, S.. "Knowledge based modular networks for process modelling and control". Computers and Chemical Engineering 25 4-6 (2001): 783-791. http://www.scopus.com/inward/record.url?eid=2-s2.0-0035340794&partnerID=MN8TOARS.
    10.1016/S0098-1354(01)00665-2
  17. Peres, J.; Oliveira, R.; Feyo de Azevedo, S.. "Knowledge based modular networks for process modelling and control". Computer Aided Chemical Engineering 8 C (2000): 247-252. http://www.scopus.com/inward/record.url?eid=2-s2.0-77956807481&partnerID=MN8TOARS.
    10.1016/S1570-7946(00)80043-7
Livro
  1. Martins, F.G.; Gonçalves, D.J.D.; Peres, J.. Artificial neural networks in environmental sciences and chemical engineering. 2011.
Poster em conferência
  1. Vieira, T.F.; Sousa, Sérgio F.; Peres, J.; Coelho, M.. "PEGylation of Temozolomide (TMZ): A Molecular Dynamics study". Trabalho apresentado em WATOC 2017 (Munich, Germany), 2017.