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Identification

Personal identification

Full name
Petia Georgieva

Citation names

  • Georgieva, Petia
  • P. Georgieva
  • Georgieva, Pétia

Author identifiers

Ciência ID
6D1E-22DA-1F69
ORCID iD
0000-0002-6424-6590
Google Scholar ID
https://scholar.google.co.uk/citations?user=aeA48X8AAAAJ&hl=en
Researcher Id
https://publons.com/researcher/1711121/petia-georgieva/
Scopus Author Id
6701326860

Knowledge fields

  • Engineering and Technology - Electrotechnical Engineering, Electronics and Informatics - Automation and Control Systems
  • Exact Sciences - Computer and Information Sciences - Information Science

Languages

Language Speaking Reading Writing Listening Peer-review
Bulgarian (Mother tongue)
English Proficiency (C2) Proficiency (C2) Proficiency (C2) Proficiency (C2) Proficiency (C2)
Portuguese Proficiency (C2) Proficiency (C2) Proficiency (C2) Proficiency (C2) Proficiency (C2)
Russian Upper intermediate (B2) Advanced (C1) Advanced (C1) Advanced (C1) Advanced (C1)
German Intermediate (B1) Advanced (C1) Intermediate (B1) Intermediate (B1) Intermediate (B1)
Education
Degree Classification
2003
Concluded
 Engenharia Electrotécnica e de Computadores (Doutoramento)
Major in Sem especialidade
Universidade do Porto Faculdade de Engenharia, Portugal
"Synthesis of Linear-sqare Self-adjusting Regulator" (THESIS/DISSERTATION)
1997
Concluded
 Ph.D. in Systems and Control Engineering (Doctor of Philosophy)
Tehnicheski universitet Sofija, Bulgaria
1987/07/05
Concluded
 M.Sc. in Systems and Control Engineering, (Master)
Tehnicheski universitet Sofija, Bulgaria
Affiliation

Science

2003 - Current Researcher (Research)
Universidade de Aveiro Instituto de Engenharia Eletrónica e Informática de Aveiro, Portugal

Teaching in Higher Education

2020/10/15 - Current Associate Professor (University Teacher)
Universidade de Aveiro, Portugal
2003/09/01 - 2020/09/30 Assistant Professor (University Teacher)
Universidade de Aveiro, Portugal
Projects

Grant

Designation Funders
2005 - 2007/12 HERON - A Framework for Portuguese Articulatory Synthesis Research
Provided by PTCRIS: 57680
 Fundação para a Ciência e a Tecnologia

Contract

Designation Funders
2020 - 2023/06/30 Augmanity Projeto Mobilizador nº 46103
Augmanity Projeto Mobilizador nº 46103
Invited Scientist Fellow
2020 - 2022/12/31 SEEBug: Develoment of a sensor for the fast and efficient detection of pathogenic bacteria in Bivalves
SEEBug
Invited Scientist Fellow
Universidade de Aveiro, Portugal
2020 - 2021/12/31 SENSECOR - Sistema imunosSENSorial integrado para o rastreio rápido e Eficiente do CORonavírus SARS-CoV-2
POCI-01-02B7-FEDER-049256
Researcher
Universidade de Aveiro, Portugal
 Fundação para a Ciência e a Tecnologia
2020 - 2021/03/31 PT2020 Project ROTATOR-AV Awareness of optical network performance
PT2020 Project ROTATOR-AV
Invited Scientist Fellow
2020 - 2021 FreeComm-B5G : Ultra-high-capacity free-space optical communications for beyond 5G
UID/EEA/50008/2019
Invited Scientist Fellow
Outputs

Publications

Book
  1. Pires, M.; Georgieva, P.. An Intelligent Tool for Detection of Phishing Messages. 2020.
    10.1007/978-3-030-17065-3_12
  2. Georgieva, P.; Suárez, L.A.P.; de Azevedo, S.F.. Time accounting artificial neural networks for biochemical process models. 2017.
    10.1007/978-3-319-41438-6_4
  3. Bozhkov, L.; Georgieva, P.. Brain neural data analysis with feature space defined by descriptive statistics. 2015.
    10.1007/978-3-319-19390-8_47
  4. Figueiredo, N.; Silva, F.; Georgieva, P.; Milanova, M.; Mendi, E.. Towards an adaptive brain-computer interface – An error potential approach. 2015.
    10.1007/978-3-319-14899-1_12
  5. Georgieva, P.; Silva, F.; Milanova, M.; Kasabov, N.. EEG signal processing for brain-computer interfaces. 2014.
    10.1007/978-3-642-30574-0_46
  6. Georgieva, P.; de Azevedo, S.F.. Error tolerant predictive control based on recurrent neural models. 2014.
    10.1007/978-3-662-43370-6_2
  7. Bozhkov, L.; Georgieva, P.; Trifonov, R.. Brain Neural Data Analysis Using Machine Learning Feature Selection and Classification Methods. 2014.
    10.1007/978-3-319-11071-4_12
  8. Georgieva, P.; Nuntal, N.; De La Torre, F.. Robust principal component analysis for improving cognitive brain states discrimination from fMRI. 2013.
    10.1007/978-3-642-38628-2_19
  9. Georgieva, P.; Mihaylova, L.; Silva, F.; Milanova, M.; Figueiredo, N.; Jain, L.C.. A sequential Monte Carlo approach for brain source localization. 2013.
    10.1007/978-3-642-28696-4-5
  10. Mihaylova, L.; Georgieva, P.; Jain, L.C.. Introduction to intelligent signal processing and data mining. 2013.
    10.1007/978-3-642-28696-4-1
  11. Georgieva, P.; De La Torre, F.. Robust principal component analysis for brain imaging. 2013.
    10.1007/978-3-642-40728-4_36
  12. Petia Georgieva; Lyudmila Mihaylova; Lakhmi C Jain. Advances in Intelligent Signal Processing and Data Mining. Springer Berlin Heidelberg. 2013.
    10.1007/978-3-642-28696-4
  13. Georgieva, P.; Bouaynaya, N.; Mihaylova, L.; Silva, F.. Bayesian approach for reconstruction of moving brain dipoles. 2013.
    10.1007/978-3-642-39094-4_64
  14. Georgieva, P.. Plant and Equipment: Instrumentation and Process Control: Process Control. 2011.
    10.1016/b978-0-12-374407-4.00413-1
  15. Oliveira, R.; Georgieva, P.; Feyo de Azevedo, S.. Plant and Equipment: Instrumentation and Process Control: Instrumentation. 2011.
    10.1016/b978-0-12-374407-4.00412-x
  16. Georgieva, P.; Suárez, L.A.P.; De Azevedo, S.F.. Time accounting artificial neural networks for biochemical process models. 2010.
    10.1007/978-3-642-13428-9_8
  17. Ferreira, A.; Almeida, C.; Georgieva, P.; Tomé, A.; Silva, F.. Advances in EEG-based biometry. 2010.
    10.1007/978-3-642-13775-4_29
  18. Georgieva, P.; de Azevedo, S.F.. Novel computational methods for modeling and control in chemical and biochemical process systems. 2009.
    10.1007/978-3-642-01888-6_4
  19. Oliveira, C.; Georgieva, P.; Rocha, F.; Ferreira, A.; De Azevedo, S.F.. Modelling of dicalcium phosphate dihydrate precipitation from solution. 2005.
    10.1016/s0263-8762(07)73209-4
  20. Simoglou, A.; Georgieva, P.; Martin, E.B.; Morris, A.J.; Feyo de Azevedo, S.. On-line multivariate statistical monitoring of a fed-batch sugar crystallisation process. 2004.
    10.1016/s1570-7946(04)80202-5
Book chapter
  1. Desislava Nikolova; Petia Mihaylova; Agata Manolova; Petia Georgieva. "ECG-Based Human Emotion Recognition Across Multiple Subjects". 2019.
    10.1007/978-3-030-23976-3_3
  2. André Brandão; Pedro Pires; Petia Georgieva. "Reinforcement Learning and Neuroevolution in Flappy Bird Game". 225-236. Springer International Publishing, 2019.
    10.1007/978-3-030-31332-6_20
  3. Diogo Daniel Ferreira; Luís Leira; Petya Mihaylova; Petia Georgieva. "Breaking Text-Based CAPTCHA with Sparse Convolutional Neural Networks". 2019.
    10.1007/978-3-030-31321-0_35
  4. José Domingues; Bernardo Lopes; Petya Mihaylova; Petia Georgieva. "Incremental Learning for Football Match Outcomes Prediction". 2019.
    10.1007/978-3-030-31321-0_19
Conference paper
  1. Georgieva, P.. "Deep learning in brain computer interfaces". 2019.
    10.1145/3351556.3351594
  2. Jesus, R.; Antunes, M.; Georgieva, P.; Gomes, D.; Aguiar, R.L.. "Stream generation: Markov chains vs GANs". 2019.
    10.5220/0007766501770184
  3. Bozhkov, L.; Georgieva, P.. "Overview of Deep Learning Architectures for EEG-based Brain Imaging". 2018.
    10.1109/IJCNN.2018.8489561
  4. Carneiro, D.; Silva, F.; Georgieva, P.. "The role of early anticipations for human-robot ball catching". 2018.
    10.1109/ICARSC.2018.8374153
  5. Dinkova, P.; Georgieva, P.; Manolova, A.; Milanova, M.. "Face recognition based on subject dependent Hidden Markov Models". 2017.
    10.1109/BlackSeaCom.2016.7901570
  6. Georgieva, K.; Georgieva, O.; Georgieva, P.; Ribeiro, M.J.; Paiva, J.S.. "Regression approach for automatic detection of attention lapses". 2016.
    10.1109/IS.2016.7737447
  7. Mladenov, V.M.; Georgieva, P.; Spasov, G.; Petrova, G.. "Preface". 2015.
  8. Stoyanova, J.; Brito, P.Q.; Georgieva, P.; Milanova, M.. "Comparison of consumer purchase intention between interactive and augmented reality shopping platforms through statistical analyses". 2015.
    10.1109/inista.2015.7276727
  9. Koprinkova-Hristova, P.; Bozhkov, L.; Georgieva, P.. "Echo state networks for feature selection in affective computing". 2015.
    10.1007/978-3-319-18944-4_11
  10. Bozhkov, L.; Georgieva, P.; Santos, I.; Pereira, A.; Silva, C.. "EEG-based subject independent affective computing models". 2015.
    10.1016/j.procs.2015.07.314
  11. Duarte, D.P.; Prats, S.; Keizer, J.J.; Georgieva, P.; Nogueira, R.; Bilro, L.. "Novel approach for simultaneous sediment classification and concentration determination of water turbidity". 2015.
    10.1117/12.2194578
  12. Ebinger, B.; Bouaynaya, N.; Georgieva, P.; Mihaylova, L.; Ebinger, B; Bouaynaya, N; Georgieva, P; et al. "EEG dynamic source localization using Marginalized Particle Filtering". 2015.
    10.1109/bibm.2015.7359727
  13. Bozhkov, L; Georgieva, P; Trifonov, R. "Brain Neural Data Analysis Using Machine Learning Feature Selection and Classification Methods". 2014.
  14. Lachezar Bozhkov; Petia Georgieva. "Classification Models of Emotional Biosignals Evoked While Viewing Affective Pictures". 2014.
    10.5220/0005104206010606
  15. Georgieva, P.; Silva, F.; Bouaynaya, N.; Mihaylova, L.. "Bayesian tracking and multi-core beamforming for estimation of correlated brain sources". 2014.
    10.1049/cp.2014.0522
  16. Georgieva, P.; Silva, F.; Mihaylova, L.; Bouaynaya, N.. "Statistical approach for reconstruction of dynamic brain dipoles based on EEG data". 2014.
    10.1109/IJCNN.2014.6889663
  17. Suarez, L.A.P.; Georgieva, P.; De Azevedo, S.F.. "Error tolerant MPC versus PI control - A crystallization case study". 2014.
  18. Georgieva, O.; Milanov, S.; Georgieva, P.. "Cluster analysis for EEG biosignal discrimination". 2013.
    10.1109/INISTA.2013.6577646
  19. Georgieva, P.; Silva, F.; Figueiredo, N.. "Brain machine interface IEETA case study". 2012.
    10.1109/IS.2012.6335164
  20. Georgieva, P.; Mihaylova, L.; Bouaynaya, N.; Jain, L.. "Particle filters and beamforming for EEG source estimation". 2012.
    10.1109/IJCNN.2012.6252516
  21. Georgieva, P.; Feyo De Azevedo, S.. "Neural networks for model predictive control". 2011.
    10.1109/IJCNN.2011.6033208
  22. Tomé, A.M.; Teixeira, A.R.; Figueiredo, N.; Georgieva, P.; Santos, I.M.; Lang, E.. "Clustering evoked potential signals using subspace methods". 2010.
    10.1109/IEMBS.2010.5627971
  23. Ferreira, A.; Almeida, C.; Georgieva, P.; Tomé, A.. "Person identification using VEP signals and SVM classifiers". 2010.
    10.1109/IJCNN.2010.5596616
  24. Suárez, L.A.P.; Georgieva, P.; De Azevedo, S.F.. "Intelligent predictive control - Application to scheduled crystallization processes". 2009.
    10.1109/icais.2009.34
  25. Suárez, L.A.P.; Georgieva, P.; De Azevedo, S.F.. "Computationally efficient process control with neural networkbased predictive models". 2009.
    10.1109/IJCNN.2009.5178663
  26. Georgieva, P.; De Azevedo, S.F.. "Neural network - Based estimation of reaction rates with partly unknown states and completely known kinetics coefficients". 2008.
    10.1109/is.2008.4670443
  27. Stadlthanner, K.; Lutter, D.; Theis, F.J.; Lang, E.W.; Tomé, A.M.; Georgieva, P.; Puntonet, C.G.. "Sparse nonnegative matrix factorization with genetic algorithms for microarray analysis". 2007.
    10.1109/IJCNN.2007.4370971
  28. Georgieva, P.; Oliveira, C.; Rocha, F.; Feyo De Azevedo, S.. "Process modeling strategy combining analytical and data based techniques - I. NN identification of reaction rates with known kinetics coefficients". 2007.
    10.1109/ijcnn.2007.4371185
  29. Georgieva, P; de Azevedo, SF. "Application of Feed Forward Neural Networks in Modeling and Control of a Fed-Batch Crystallization Process". 2006.
  30. Galvanauskas, V.; Georgieva, P.; Feyo De Azevedo, S.. "Dynamic optimisation of industrial sugar crystallization process based on a hybrid (mechanistic+ANN) model". 2006.
  31. Simoglou, A.; Georgieva, P.; Martin, E.B.; Morris, A.J.; De Azevedo, S.F.. "A time varying state space approach for sugar crystallization process modelling and monitoring". 2005.
  32. Baruch, I.S.; Georgieva, P.; Hernandes P., L.A.; Nenkova, B.. "An adaptive integral plus states neural control of aerobic continuous stirred tank reactor". 2004.
  33. Roumenin, C.; Georgieva, P.; Ivanov, A.. "Anomalous angle dependence of the output signal of bipolar magnetic sensors". 1998.
    10.1109/ASDAM.1998.730227
Journal article
  1. Santos, Fábio Miguel Tomaz dos. "Deep learning for multi-class skin lesion diagnosis". (2020): http://hdl.handle.net/10773/29604.
  2. Lachezar Bozhkov; Petia Georgieva. "Deep learning models for brain machine interfaces". Annals of Mathematics and Artificial Intelligence (2019): https://doi.org/10.1007/s10472-019-09668-0.
    10.1007/s10472-019-09668-0
  3. Vitor Pereira; Filipe Tavares; Petya Mihaylova; Valeri Mladenov; Petia Georgieva. "Factor Analysis for Finding Invariant Neural Descriptors of Human Emotions". Complexity (2018): https://doi.org/10.1155/2018/6740846.
    10.1155/2018/6740846
  4. A. C. Maurício; T. Pereira; P. Teixeira; R. Magalhães; J. D. Santos; P. P. Barbosa; M. V. Branquinho; et al. "Human umbilical cord blood plasma as an alternative to animal sera for mesenchymal stromal cells in vitro expansion - A multicomponent metabolomic analysis". Plos One (2018): https://publons.com/publon/15924906/.
    10.1371/JOURNAL.PONE.0203936
  5. Bozhkov, L.; Koprinkova-Hristova, P.; Georgieva, P.. "Reservoir computing for emotion valence discrimination from EEG signals". Neurocomputing 231 (2017): 28-40. http://www.scopus.com/inward/record.url?eid=2-s2.0-85006062107&partnerID=MN8TOARS.
    10.1016/j.neucom.2016.03.108
  6. Bozhkov, L.; Koprinkova-Hristova, P.; Georgieva, P.. "Learning to decode human emotions with Echo State Networks". Neural Networks 78 (2016): 112-119. http://www.scopus.com/inward/record.url?eid=2-s2.0-84966400967&partnerID=MN8TOARS.
    10.1016/j.neunet.2015.07.005
  7. Georgieva, P.; Bouaynaya, N.; Silva, F.; Mihaylova, L.; Jain, L.C.. "A Beamformer-Particle Filter Framework for Localization of Correlated EEG Sources". IEEE Journal of Biomedical and Health Informatics 20 3 (2016): 880-892. http://www.scopus.com/inward/record.url?eid=2-s2.0-84969913442&partnerID=MN8TOARS.
    10.1109/jbhi.2015.2413752
  8. Milanova, Mariofanna; Manolova, Agata; Dinkova, Petya; Georgieva, Petia. "Face Recognition Based on Subject Dependent Hidden Markov Models". IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom) (2016): https://publons.com/publon/14571346/.
    10.1109/BLACKSEACOM.2016.7901570
  9. Roumiana Ilieva; Petia Georgieva; Stanislava Petrova. "BRAIN DATA ANALYSIS AND MANAGEMENT". GISAP:MSP 7 (2015): http://dx.doi.org/10.18007/gisap:msp.v0i7.1071.
    10.18007/gisap:msp.v0i7.1071
  10. Georgieva, O.; Milanov, S.; Georgieva, P.; Santos, I.M.; Pereira, A.T.; Silva, C.F.. "Learning to decode human emotions from event-related potentials". Neural Computing and Applications 26 3 (2015): 573-580. http://www.scopus.com/inward/record.url?eid=2-s2.0-84925289990&partnerID=MN8TOARS.
    10.1007/s00521-014-1653-6
  11. Neves, José; Machado, José; Gomes, Guida; Sousa, Sérgio; Tereso, Daniela; Coelho, Ana; Caldeira, A. Teresa; et al. "An Evaluation of Parchments’ Degradation - A Hybrid Approach". Parchment stands for a multifaceted material made from animal skin, which has been used for centuries as a writing support or as bookbinding. Due to the historic value of objects made of parchment, understanding their degradation and their condition is of utmost importance to archives, libraries and museums, i.e., the assessment of parchment degradation is mandatory, although it is hard to do with (2015): http://www.scs-europe.net/dlib/2015/2015-0492.htm.
  12. Georgieva, O.; Milanov, S.; Georgieva, P.. "Unsupervised EEG biosignal discrimination". International Journal of Reasoning-based Intelligent Systems 6 3-4 (2014): 118-125. http://www.scopus.com/inward/record.url?eid=2-s2.0-84918536579&partnerID=MN8TOARS.
    10.1504/ijris.2014.066249
  13. Petia Georgieva; Filipe Silva; Nuno Figueiredo. "IEETA brain computer interface technologies". International Journal of Computational Intelligence Studies 2 3/4 (2013): 314-314. http://dx.doi.org/10.1504/ijcistudies.2013.057645.
    10.1504/ijcistudies.2013.057645
  14. Alexiev, Kiril; Koprinkova-Hristova, Petia. "Echo State Networks in Dynamic Data Clustering". Lecture Notes in Computer Science (2013): https://publons.com/publon/3487082/.
    10.1007/978-3-642-40728-4_43
  15. Georgi Jelev; Valentin Atanassov; Denitsa Borisova; Kiril Alexiev; Petia Koprinkova-Hristova. "Recurrent neural networks for automatic clustering of multispectral satellite images". Image and Signal Processing for Remote Sensing Xix (2013): https://publons.com/publon/3487086/.
    10.1117/12.2029191
  16. Georgieva, Petia; Azevedo, Sebastião Feyo de. "Application of artificial neural networks in modeling and optimization of batch crystallization processes". This paper is focused on issues of dynamic process modeling and model-based optimization of batch and fed-batch industrial crystallization processes applying the concept of artificial neural networks as computational tools. The objective is to drive the process to its optimal state of profit maximization and cost minimization. The simulation results demonstrate that t (2013): http://revistas.ua.pt/index.php/revdeti/article/view/1870.
  17. Paz Suárez, L.A.; Georgieva, P.; Feyo de Azevedo, S.. "Nonlinear MPC for fed-batch multiple stages sugar crystallization". Chemical Engineering Research and Design 89 6 (2011): 753-767. http://www.scopus.com/inward/record.url?eid=2-s2.0-79956293971&partnerID=MN8TOARS.
    10.1016/j.cherd.2010.10.010
  18. Tomé, A.M.; Teixeira, A.R.; Figueiredo, N.; Georgieva, P.; Santos, I.M.; Lang, E.. "Clustering evoked potential signals using subspace methods.". Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference (2010): 3986-3989. http://www.scopus.com/inward/record.url?eid=2-s2.0-84903875543&partnerID=MN8TOARS.
  19. Tome, AM; Teixeira, AR; Figueiredo, N; Santos, IM; Georgieva, P; Lang, EW. "SSA of biomedical signals: A linear invariant systems approach". STATISTICS AND ITS INTERFACE (2010): https://www.authenticus.pt/P-003-CZ0.
  20. Oliveira, C.; Georgieva, P.; Rocha, F.; Feyo De Azevedo, S.. "Artificial neural networks for modeling in reaction process systems". Neural Computing and Applications 18 1 (2009): 15-24. http://www.scopus.com/inward/record.url?eid=2-s2.0-58549113550&partnerID=MN8TOARS.
    10.1007/s00521-008-0200-8
  21. Oliveira, C.; Georgieva, P.; Rocha, F.; Ferreira, A.; Feyo de Azevedo, S.. "Dynamical model of brushite precipitation". Journal of Crystal Growth 305 1 (2007): 201-210. http://www.scopus.com/inward/record.url?eid=2-s2.0-34249875384&partnerID=MN8TOARS.
    10.1016/j.jcrysgro.2007.04.016
  22. Simoglou, A.; Georgieva, P.; Martin, E.B.; Morris, A.J.; Feyo De Azevedo, S.. "On-line monitoring of a sugar crystallization process". Computers and Chemical Engineering 29 6 SPEC. IS (2005): 1411-1422. http://www.scopus.com/inward/record.url?eid=2-s2.0-18244371404&partnerID=MN8TOARS.
    10.1016/j.compchemeng.2005.02.013
  23. Baruch, I.S.; Georgieva, P.; Barrera-Cortes, J.; De Azevedo, S.F.. "Adaptive recurrent neural network control of biological wastewater treatment". International Journal of Intelligent Systems 20 2 (2005): 173-193. http://www.scopus.com/inward/record.url?eid=2-s2.0-13844296578&partnerID=MN8TOARS.
    10.1002/int.20061
  24. Georgieva, P.; Meireles, M.J.; Feyo de Azevedo, S.. "Knowledge-based hybrid modelling of a batch crystallisation when accounting for nucleation, growth and agglomeration phenomena". Chemical Engineering Science 58 16 (2003): 3699-3713. http://www.scopus.com/inward/record.url?eid=2-s2.0-0042827953&partnerID=MN8TOARS.
    10.1016/S0009-2509(03)00260-4
  25. Trayana Patarinska; Petya Koprinkova; Silvia Popova. "Neural network based biomass and growth rate estimation aimed to control of a chemostat microbial cultivation". Applied Artificial Intelligence (2003): https://publons.com/publon/3487068/.
    10.1080/713827143
  26. Faculdade de Engenharia. "Modeling of sugar crystallization through knowledge integration". (2003): https://repositorio-aberto.up.pt/handle/10216/98899.
    10.1002/elsc.200390019
  27. Georgieva, P.; Feyo De Azevedo, S.. "A neural network based approach for measurement dynamics compensation". Applied Artificial Intelligence 16 6 (2002): 423-442. http://www.scopus.com/inward/record.url?eid=2-s2.0-0036646944&partnerID=MN8TOARS.
    10.1080/08839510290030291
  28. Georgieva, P.; Ilchmann, A.. "Adaptive ¿-tracking control of activated sludge processes". International Journal of Control 74 12 (2001): 1247-1259. http://www.scopus.com/inward/record.url?eid=2-s2.0-0035883107&partnerID=MN8TOARS.
    10.1080/00207170110065910
  29. Georgieva, P.; Ilchmann, A.; Weirig, M.-F.. "Modelling and adaptive control of aerobic continuous stirred tank reactors". European Journal of Control 7 5 (2001): 476-491. http://www.scopus.com/inward/record.url?eid=2-s2.0-29944447574&partnerID=MN8TOARS.
    10.3166/ejc.7.476-491
  30. Mareels, I; Georgieva, P; Ilchmann, A; Weirig, M. "Discussion on: “Modeling and Adaptive Control of Aerobic Continuous Stirred Tank Reactors” by P. Georgieva, A. Ilchmann and M.-F. Weirig". European Journal of Control (2001):
    10.3166/ejc.7.492-493
  31. Georgieva, P.G.; Ignatova, M.N.. "Implementation of robust control theory to a continuous stirred tank bioreactor". Bioprocess Engineering 22 6 (2000): 563-568. http://www.scopus.com/inward/record.url?eid=2-s2.0-2442593226&partnerID=MN8TOARS.
  32. Ignatova, M.; Lubenova, V.; Georgieva, P.. "MIMO adaptive linearizing control of fed-batch amino acids simultaneous production". Bioprocess Engineering 22 1 (2000): 79-84. http://www.scopus.com/inward/record.url?eid=2-s2.0-0033951345&partnerID=MN8TOARS.
  33. Georgieva, P.G.; Feyo De Azevedo, S.. "Robust control design of an activated sludge process". International Journal of Robust and Nonlinear Control 9 13 (1999): 949-967. http://www.scopus.com/inward/record.url?eid=2-s2.0-6744224437&partnerID=MN8TOARS.
    10.1002/(SICI)1099-1239(199911)9:13<949::AID-RNC445>3.0.CO;2-G
  34. Georgieva, P.G.; Ignatova, M.N.. "LFT models of continuous biotechnological processes". Bioprocess Engineering 20 2 (1999): 179-183. http://www.scopus.com/inward/record.url?eid=2-s2.0-0033063952&partnerID=MN8TOARS.
    10.1007/s004490050578
  35. Petia Georgieva. "ROBUST STABILITY IN MULTIVARIABLE FEEDBACK-SYSTEMS USING DOMINANCE CONCEPT AND APPROXIMATE MODEL". 93, INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS: SYSTEMS ENGINEERING IN THE SERVICE OF HUMANS, VOL 3 (1993): https://publons.com/publon/15926468/.
Thesis / Dissertation
  1. Marques, João António Palavra. "A self-surveillance system for change detection of pigmented skin lesions". Master, 2019. http://hdl.handle.net/10773/29597.
  2. Maia, Fábio. "A study of transfer learning for skin lesion classification". Master, 2019. http://hdl.handle.net/10773/29408.
  3. Sousa, Diogo Macedo de. "Decision support service for Bewegen bike-sharing systems". Master, 2019. http://hdl.handle.net/10773/29670.
  4. Carneiro, Diogo José Vaz. "Generalization and anticipation skills for robot ball catching using supervised learning". Master, 2017. http://hdl.handle.net/10773/23856.
  5. Pires, Marcos da Silva Neto Abranches. "Development of intelligent tool for phising email detection". Master, 2017. http://hdl.handle.net/10773/25890.
  6. Costa, Rui Jorge Duarte. "Face detection and recognision". Master, 2016. http://hdl.handle.net/10773/21683.
  7. Paz Suárez, Luis Alberto. "Estratégias avançadas de modelização e controlo para processos industriais não lineares e descontínuos : aplicação em cristalizadores industriais de açucar". PhD, 2010. http://hdl.handle.net/10216/58885.
  8. Gaspar, Pedro André dos Santos. "Laboratório virtual de sistemas de controlo: realidade virtual". Master, 2010. http://hdl.handle.net/10773/3562.
  9. Maia, Pedro Emanuel Moreira. "Detecção de actividade cerebral com imagens de ressonância magnética". Master, 2010. http://hdl.handle.net/10773/7434.
  10. Prada, Bruno Miguel Lopes. "Interface cérebro-computador não invasiva baseada em OpenVibe". Master, 2010. http://hdl.handle.net/10773/7524.
  11. Ferreira, António José Claro. "Sistema de identificação pessoal baseado em sinais de EEG". Master, 2009. http://hdl.handle.net/10773/2114.
  12. Ferraz, João Miguel Ribeiro Paiva. "Laboratório virtual de sistemas de controlo". Master, 2009. http://hdl.handle.net/10773/2108.
  13. Ribeiro, Vítor Manuel Costa. "Controlo de sistemas dinâmicos com redes neuronais artificiais". Master, 2008. http://hdl.handle.net/10773/2007.
  14. Salgado, Norberto Emanuel Godinho. "Ajuste de controladores por optimização não linear multiobjectivo". Master, 2008. http://hdl.handle.net/10773/1959.

Other

Other output
  1. Petia Georgieva. 2016. Advances in Intelligent Signal Processing and Data Mining: Theory and Applications. http://doi.org/10.17632/K37H8H7ZKS.2.
    10.17632/K37H8H7ZKS.2
  2. Georgieva, Petia. 2016. EEG-based subject independent affective computing models.
    10.17632/JVB9NSBWT9.2
  3. Georgieva, Petia. 2015. ECMS 2015 Proceedings edited by: Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova. http://dx.doi.org/10.7148/2015.
    10.7148/2015
  4. Sánchez Dediós, Luis; Georgieva, Petia; Feyo de Azevedo, Sebastião. 2013. SISO versus MIMO model based predictive control structures: a fed-batch crystallizer case study. This work is focused on a comparative study of four structures of linear model predictive control (LMPC) for a fed batch crystallization process. Two single input single output (SISO) and two multiple input multiple output (MIMO) control schemes are analysed with respect to the final process quality achieved. The linear models required in the controller structures are extracted applying two identi. http://revistas.ua.pt/index.php/revdeti/article/view/2111.
  5. Capela, Nelson Filipe; Georgieva, Petia. 2013. Aplicação de técnicas de aprendizagem automática para classificação de emoções humanas com sinais de EEG. Este artigo apresenta um estudo referente a várias técnicas de Aprendizagem Automática (MachineLearning) e a sua aplicação para discriminar dois tipos de emoções humanas - valência emocional positiva e negativa, baseado em dados de eletroencefalografia (EEG).Numa primeira fase foi efetuada uma abordagemintrodutória das técnicas m. http://revistas.ua.pt/index.php/revdeti/article/view/2183.
  6. Luis Alberto Paz Suarez; Petia Georgieva; Sebastiao Feyo de Azevedo. 2011. Model Predictive Control Strategies for Batch Sugar Crystallization Process. http://dx.doi.org/10.5772/16853.
    10.5772/16853
Activities

Supervision

Thesis Title
Role 		Degree Subject (Type)
Institution / Organization
2013 - Current Enhancing the usability, computational efficiency and reability of EEG - based brand machine interfaces.
Supervisor
 Informática (PhD)
Universidade de Aveiro, Portugal
2018 - 2018 Desenvolvimento de Ferramenta Inteligente para Deteção de Phishing
Supervisor
 Engenharia de Computadores e Telemática (Master)
Universidade de Aveiro, Portugal
2016 - 2016 Deteção e Reconhecimento Facial
Supervisor
 Engenharia Eletrónica e Telecomunicações (Master)
Universidade de Aveiro, Portugal
Distinctions

Award

2020 BEST PAPER award: A. Brandão, P. Georgieva (2020). Log Files Analysis for Network Intrusion Detection. 10th IEEE Int Conf on Intelligent Systems, 28-30 August, 2020, Varna, Bulgaria
2016 Best paper award - 8 IEEE Int Conf on Intelligent Systems. Paper: K. Georgieva, P. Georgieva, O. Georgieva, M.J. Ribeiro, J.S. Paiva (2016), Regression Approach for Automatic Detection of Attention Lapses.
2012 Best paper award – 6th IEEE Int Conf on Intelligent Systems. Paper: P Georgieva, F. Silva, N. Figueiredo (2012). Brain Machine Interface - IEETA Case Study.