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Weronika Wojtak is a Senior Researcher at the CCG/ZGDV Institute, working in the field of human–robot interaction with a focus on cognitive and adaptive systems for natural collaboration. Her research centers on developing computational models—particularly Dynamic Neural Field (DNF) architectures—that enable robots to interpret human behavior, anticipate actions, and coordinate effectively in time-sensitive, real-world environments. She holds a PhD in Applied Mathematics (2021) from the Universidade do Minho, a Master’s degree in Computer Science (2013), and a Bachelor’s degree in Biomedical Engineering (2012), both from Uniwersytet Zielonogórski (Poland). Her work integrates robotics, machine learning, and multimodal perception to advance intuitive, resilient, and human-centered robotic systems.
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Identification

Personal identification

Full name
Weronika Wojtak

Citation names

  • Wojtak, Weronika

Author identifiers

Ciência ID
1516-682B-D9DF
ORCID iD
0000-0001-9515-2397

Email addresses

  • weronika.wojtak@ccg.pt (Professional)

Knowledge fields

  • Engineering and Technology - Electrotechnical Engineering, Electronics and Informatics - Robotics and Automatic Control
  • Exact Sciences - Mathematics - Applied Mathematics
  • Exact Sciences - Computer and Information Sciences - Computer Sciences

Languages

Language Speaking Reading Writing Listening Peer-review
Polish (Mother tongue)
English Advanced (C1) Proficiency (C2) Proficiency (C2) Proficiency (C2) Proficiency (C2)
Education
Degree Classification
2021/09/28
Concluded
 Matemática Aplicada (associação) (Doutoramento)
Major in Sem especialidade
Universidade do Minho, Portugal
"A novel dynamic field model supporting a continuum of bump amplitudes: analysis and applications" (THESIS/DISSERTATION)
2012/03/12 - 2013/07/12
Concluded
 Master's degree in Computer Science (Magister (2nd cycle))
Uniwersytet Zielonogórski, Poland
"Computer system to support breast cancer diagnosis based on microscope images of the Fine Needle Biopsy" (THESIS/DISSERTATION)
 5/5
2008/10/01 - 2012/03/07
Concluded
 Bachelor's degree in Biomedical Engineering (Bachelor (1st cycle))
Uniwersytet Zielonogórski, Poland
"Automatic nuclei detection on cytological images using the firefly optimization algorithm" (THESIS/DISSERTATION)
 5/5
Affiliation

Science

Category
Host institution		 Employer
2023/07/01 - Current Researcher (Research) Centro de Computação Gráfica, Portugal
Centro de Computação Gráfica, Portugal
2020/12/02 - 2023/06/30 Postdoc (Research) Universidade do Minho - Campus de Azurém, Portugal
2016/09/01 - 2020/12/01 Researcher (Research) Universidade do Minho - Campus de Azurém, Portugal
Universidade do Minho - Campus de Azurém, Portugal
2013/10/01 - 2016/08/31 Researcher (Research) Universidade do Minho - Campus de Azurém, Portugal
Projects

Grant

Designation Funders
2024/12/01 - 2025/11/30 TIME4HRI - Learning TIME constrained sequences for natural Human-Robot Interaction
101070596
Principal investigator
Centro de Computação Gráfica, Portugal
Concluded
2019/01 - 2019/12 Centro de Investigação ALGORITMI
154637UID
UID/CEC/00319/2019
Universidade do Minho, Portugal

Universidade do Minho Centro ALGORITMI, Portugal
 Fundação para a Ciência e a Tecnologia
Concluded
Outputs

Publications

Book chapter
  1. Dias, Pedro; Ferreira, Flora; Guimarães, Pedro M. F.; Wojtak, Weronika; Erlhagen, Wolfram; Monteiro, Sérgio; Sousa, Emanuel; Bicho, Estela. "A Machine Learning Approach for Points of Interest Extraction and Event Classification". In IFIP Advances in Information and Communication Technology, 69-82. Springer Nature Switzerland, 2024.
    10.1007/978-3-031-63223-5_6
  2. Paulo Barbosa; Flora Ferreira; Carlos Fernandes; Wolfram Erlhagen; Pedro Guimarães; Weronika Wojtak; Sérgio Monteiro; Estela Bicho. "Endowing Intelligent Vehicles with the Ability to Learn User’s Habits and Preferences with Machine Learning Methods". 157-169. Springer International Publishing, 2022.
    10.1007/978-3-031-21753-1_16
  3. Weronika Wojtak; Flora Ferreira; Pedro Guimarães; Paulo Barbosa; Sérgio Monteiro; Wolfram Erlhagen; Estela Bicho. "Towards Endowing Intelligent Cars with the Ability to Learn the Routines of Multiple Drivers: A Dynamic Neural Field Model". 337-349. Springer International Publishing, 2021.
    10.1007/978-3-030-86973-1_24
  4. Flora Ferreira; Weronika Wojtak; Carlos Fernandes; Pedro Guimarães; Sérgio Monteiro; Estela Bicho; Wolfram Erlhagen. "Dynamic Identification of Stop Locations from GPS Trajectories Based on Their Temporal and Spatial Characteristics". 347-359. Springer International Publishing, 2021.
    10.1007/978-3-030-86380-7_28
  5. Pawel Filipczuk; Weronika Wojtak; Andrzej Obuchowicz. "Automatic Nuclei Detection on Cytological Images Using the Firefly Optimization Algorithm". 85-92. Springer Berlin Heidelberg, 2012.
    10.1007/978-3-642-31196-3_9
Conference paper
  1. Wojtak, Weronika; Ferreira, Flora José Rocha; Bicho, Estela; Erlhagen, Wolfram. "Neural field model for measuring and reproducing time intervals". 2019.
    10.1007/978-3-030-30487-4_26
  2. Wojtak, Weronika; Ferreira, Flora José Rocha; Bicho, Estela; Erlhagen, Wolfram. "Numerical analysis of the shape of bump solutions in a neuronal model of working memory". 2019.
    10.1063/1.5114243
  3. Ferreira, Flora; Wojtak, Weronika; Erlhagen, Wolfram; Vicente, Paulo; Ankit, Patel R.; Bicho, Estela. "A dynamic neural model for endowing intelligent cars with the ability to learn driver routines: where to go, when to arrive and how long to stay there?". Paper presented in Towards Cognitive Vehicles Workshop – IROS 2019, 2019.
    10.6084/m9.figshare.13655636.v1
  4. Wojtak, Weronika; Ferreira, Flora José Rocha; Louro, Luís; Bicho, Estela; Erlhagen, Wolfram. "Towards temporal cognition for robots: a neurodynamics approach". 2017.
    10.1109/DEVLRN.2017.8329836
  5. Wojtak, Weronika; Coombes, Stephen; Bicho, Estela; Erlhagen, Wolfram. "Combining spatial and parametric working memory in a dynamic neural field model". 2016.
    10.1007/978-3-319-44778-0_48
  6. Wojtak, Weronika; Ferreira, Flora José Rocha; Erlhagen, Wolfram; Bicho, Estela. "Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach". 2015.
    10.1109/IJCNN.2015.7280717
Journal article
  1. Guimarães, Pedro M. F.; Ferreira, Flora; Wojtak, Weronika; Barbosa, Paulo J. S.; Monteiro, Sérgio; Bicho, Estela; Erlhagen, Wolfram. "A Dynamic Neural Field Approach for Intelligent Cockpits: Online Learning and Prediction of Traveling Routines". IEEE Transactions on Intelligent Transportation Systems 25 12 (2024): 20240-20255. https://doi.org/10.1109/tits.2024.3463389.
    10.1109/tits.2024.3463389
  2. Wojtak, Weronika; Coombes, Stephen; Avitabile, Daniele; Bicho, Estela; Erlhagen, Wolfram. "Robust working memory in a two-dimensional continuous attractor network". (2023): https://hdl.handle.net/1822/85745.
    10.1007/s11571-023-09979-3
  3. Wojtak, Weronika; Ferreira, Flora José Rocha; Louro, Luís; Bicho, Estela; Erlhagen, Wolfram. "Adaptive timing in a dynamic field architecture for natural human–robot interactions". (2023): https://hdl.handle.net/1822/85747.
    10.1016/j.cogsys.2023.101148
  4. Weronika Wojtak; Stephen Coombes; Daniele Avitabile; Estela Bicho; Wolfram Erlhagen. "A dynamic neural field model of continuous input integration". Biological Cybernetics 115 5 (2021): 451-471. http://dx.doi.org/10.1007/s00422-021-00893-7.
    10.1007/s00422-021-00893-7
  5. Ferreira, Flora José Rocha; Wojtak, Weronika; Sousa, Emanuel; Louro, Luis; Bicho, Estela; Erlhagen, Wolfram. "Rapid learning of complex sequences with time constraints: A dynamic neural field model". (2020): http://hdl.handle.net/1822/69418.
    10.1109/TCDS.2020.2991789
  6. Wojtak, Weronika; Ferreira, Flora José Rocha; Vicente, Paulo Sérgio Cunha; Louro, Luís; Bicho, Estela; Erlhagen, Wolfram. "A neural integrator model for planning and value-based decision making of a robotics assistant". (2020): http://hdl.handle.net/1822/69412.
    10.1007/s00521-020-05224-8
  7. Wojtak, Weronika; Silva, Cristiana J.; Torres, Delfim F. M.. "Uniform asymptotic stability of a fractional tuberculosis model". (2018): http://hdl.handle.net/10773/24522.
    10.1051/mmnp/2018015

Other

Other output
  1. Solving neural field equations using physics informed neural networks. This article presents an approach for solving neural field equations (NFEs) using Physics Informed Neural Networks (PINNs). NFEs are integro-differential equations describing the spatio-temporal dynamics of neuronal populations in the cortex. The traditional numerical methods for NFEs require significant computational effort due to the discretization of the spatial convolution. The proposed approa. 2023. Wojtak, Weronika; Bicho, Estela; Erlhagen, Wolfram. https://hdl.handle.net/1822/90178.
Distinctions

Award

2019 3rd Prize – International Collegiate Competition for Brain-Inspired Computing (Tsinghua University)
2019 Best Poster Award at 'Towards Cognitive Vehicles Workshop' (TCV2019) at IROS 2019