| Knowledge-based hybrid modelling of a batch crystallisation when accounting for nucleation, growth and agglomeration phenomena P Georgieva, MJ Meireles, SF De Azevedo Chemical Engineering Science 58 (16), 3699-3713, 2003 | 118 | 2003 |
| On-line monitoring of a sugar crystallization process A Simoglou, P Georgieva, EB Martin, AJ Morris, SF De Azevedo Computers & Chemical Engineering 29 (6), 1411-1422, 2005 | 81 | 2005 |
| Software engineering with computational intelligence TM Khoshgoftaar Springer Science & Business Media, 2012 | 71* | 2012 |
| Adaptive recurrent neural network control of biological wastewater treatment IS Baruch, P Georgieva, J Barrera‐Cortes, SF de Azevedo International Journal of Intelligent Systems 20 (2), 173-193, 2005 | 62 | 2005 |
| Learning to decode human emotions with Echo State Networks L Bozhkov, P Koprinkova-Hristova, P Georgieva Neural Networks 78, 112-119, 2016 | 60 | 2016 |
| Semi-supervised hybrid modeling of atmospheric pollution in urban centers I Bougoudis, K Demertzis, L Iliadis, VD Anezakis, A Papaleonidas Engineering Applications of Neural Networks: 17th International Conference …, 2016 | 54* | 2016 |
| Comparison of consumer purchase intention between interactive and augmented reality shopping platforms through statistical analyses J Stoyanova, PQ Brito, P Georgieva, M Milanova 2015 International Symposium on Innovations in Intelligent SysTems and …, 2015 | 53 | 2015 |
| Neural network-based control strategies applied to a fed-batch crystallization process P Georgieva, SF De Azevedo International Journal of Chemical and Molecular Engineering 1 (12), 145-154, 2007 | 51 | 2007 |
| ECG-based Emotion Recognition: Overview of Methods and Applications D Nikolova, P Petkova, A Manolova, P Georgieva ANNA'18; Advances in Neural Networks and Applications 2018, 1-5, 2018 | 50 | 2018 |
| Reservoir computing for emotion valence discrimination from EEG signals L Bozhkov, P Koprinkova-Hristova, P Georgieva Neurocomputing 231, 28-40, 2017 | 48 | 2017 |
| SSA of biomedical signals: A linear invariant systems approach N Figueiredo, P Georgieva, EW Lang, IM Santos, AR Teixeira, AM Tomé Statistics and its Interface 3 (3), 345-355, 2010 | 44 | 2010 |
| Robust control design of an activated sludge process PG Georgieva, S Feyo de Azevedo International Journal of Robust and Nonlinear Control: IFAC‐Affiliated …, 1999 | 44 | 1999 |
| EEG-based subject independent affective computing models L Bozhkov, P Georgieva, I Santos, A Pereira, C Silva Procedia Computer Science 53, 375-382, 2015 | 42 | 2015 |
| Nonlinear MPC for fed-batch multiple stages sugar crystallization LAP Suárez, P Georgieva, SF De Azevedo Chemical Engineering Research and Design 89 (6), 753-767, 2011 | 37 | 2011 |
| Computational intelligence techniques as tools for bioprocess modelling, optimization, supervision and control MC Nicoletti, LC Jain, RC Giordano Computational Intelligence Techniques for Bioprocess Modelling, Supervision …, 2009 | 37 | 2009 |
| Human umbilical cord blood plasma as an alternative to animal sera for mesenchymal stromal cells in vitro expansion – A multicomponent metabolomic analysis AR Caseiro, G Ivanova, SS Pedrosa, MV Branquinho, P Georgieva, ... PloS one 13 (10), e0203936, 2018 | 35 | 2018 |
| Adaptive?-tracking control of activated sludge processes P Georgieva, A Ilchmann International Journal of Control 74 (12), 1247-1259, 2001 | 32 | 2001 |
| A beamformer-particle filter framework for localization of correlated EEG sources P Georgieva, N Bouaynaya, F Silva, L Mihaylova, LC Jain IEEE Journal of Biomedical and Health Informatics 20 (3), 880-892, 2015 | 30 | 2015 |
| Dynamical model of brushite precipitation C Oliveira, P Georgieva, F Rocha, A Ferreira, SF de Azevedo Journal of crystal growth 305 (1), 201-210, 2007 | 29 | 2007 |
| Overview of deep learning architectures for EEG-based brain imaging L Bozhkov, P Georgieva 2018 International joint conference on neural networks (IJCNN), 1-7, 2018 | 28 | 2018 |
Sebastião Feyo de AzevedoEmeritus Professor of Chemical EngineeringVerified email at fe.up.pt
