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Marjory Da Costa Abreu

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Professor Marjory Da Costa Abreu PhD, MPhil, BSc, SFHEA

Associate Professor in Ethical Artificial Intelligence and Transforming Lives Fellow

Summary

Dr Márjory is an Associate Professor in Ethical Artificial Intelligence and a Transforming Lives Fellow at Ï㽶ÊÓƵ.

Her work centres on breaking down barriers in the ethical use of AI in different application areas, and on ensuring that Digital Literacy follows the advancement of technology. Her research crosses the application areas of health and public health data, forensics/surveillance, museum sector with a decolonial view, digital law, higher education, hate speech/fake news, policy regarding AI/Digital usages and biometrics.

She works creating new light AI-based algorithms, not using off-the-shelf profit-driven big-tech-owned solutions.

Being a woman of colour in STEM, she is a feminist, anti-racist and huge supporter and promoter of women in science.

 
Marjory Da Costa Abreu

About

Marjory is passionate about computing and artificial intelligence.

Her main area of research is applied , more specifically, data-mining and machine learning applied to user data analysis and biometrics (face analysis, emotion prediction, keystroke, mouse and touch dynamics, fingerprint, handwritten text, signature and voice/speech). Some of my ongoing projects are: ; transparency in user behaviour in commercial game playing; signal processing (speech analysis) applied to medical diagnosis and neurological diseases therapy; forensics-based keystroke dynamics analysis applied to accountability concerns in social networks; mining judges’ sentences for analysing fairness; mining hard real-time network environments and investigating machine learning-based decision engines for network intrusion detection systems; and designing cheaper technological solutions for biometrics applications in different scenarios.

She has won the Newton Ï㽶ÊÓƵ Collaboration Programme Award and has strong collaborations with the University of Kent (UK) and the University of York (UK) and she has been working in several different projects.

She worked as a Reader in Artificial Intelligence at UFRN until 2019.

Teaching

School of Computing and Digital Technologies

College of Business, Technology and Engineering

I have been teaching in higher education subjects that are related with programming, machine learning, research methods and artificial intelligence.

Subject Area

Games and Artificial Intelligence

Courses 

MSc Artificial Intelligence

I have been teaching in higher education subjects that are related with programming, machine learning, research methods and artificial intelligence.
Currently, I am responsible for the Artificial Intelligence Seminar Series module.

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Some of my ongoing projects are: medieval document analysis (); transparency in user behaviour in commercial game playing; signal processing (speech analysis) applied to medical diagnosis and neurological diseases therapy; forensics-based keystroke dynamics analysis applied to accountability concerns in social networks; mining judges’ sentences for analysing fairness; mining hard real-time network environments and investigating machine learning-based decision engines for network intrusion detection systems; and designing cheaper technological solutions for biometrics applications in different scenarios.

Relevant Projects

  • Exploring Applied Artificial Intelligence.
  • Visualisation and dynamic analysis of medieval writing processes in the context of neurological diseases and disorders.
  • DeepEyes: Visual Computing and Machine Intelligence Solutions for Computer Forensics and Electronic Surveillance.
  • Identity management using biometric data (UFRN / Propesq - PVB9148-2013).
  • Aging and biometric processing (UFRN / Propesq - PVB9756-2013).
  • Collection and analysis of a new multibiometric database based on behavioral metrics of the hand (CNPq Universal 14/2013 - 472717 / 2013-8).
  • Multi-source biometric processing.
  • Establishing the Parameters of Soft Biometrics Integration in an Agent-Based Identification Framework.
  • Investigating of Measures of Communication Effectiveness.
  • Perspectives on identity, identity protection and biometrics among young people.
  • SimOrg - Simulation of Organizations (PDPG-TI / CNPq 552431 / 2002-8) .
  • Brazilian Genome Project: RL group.

Publications

Journal articles

Marques, J.G., Carvalho, B.M.D., Guedes, L.A., & Da Costa Abreu, M. (2025). . Frontiers in Artificial Intelligence, 8.

Nascimento, F.R.S., Cavalcanti, G.D.C., & Costa-Abreu, M.D. (2025). . Neural Computing and Applications, 37 (5), 3887-3905.

Marques, J.G., Carvalho, B.M.D., Guedes, L.A., & Da Costa-Abreu, M. (2024). . International Journal of Environmental Ï㽶ÊÓƵ and Public Health, 21 (9).

(2024). . Public Policy.

Russo, C., Wyld, L., Da Costa Aubreu, M., Bury, C.S., Heaton, C., Cole, L.M., & Francese, S. (2023). . Scientific Reports, 13 (1).

Marques, J.G., Guedes, L.A., & Da Costa Abreu, M. (2022). . International Journal of Environmental Ï㽶ÊÓƵ and Public Health, 20 (1).

Nascimento, F., Cavalcanti, G., & Da Costa Abreu, M. (2022). . Expert Systems with Applications, 201.

Dos Santos Nascimento, F.R., Smith, S., & Da Costa Abreu, M. (2022). . Digital Studies/le champ numérique, 12 (1).

De Lima, T.A., & Da Costa Abreu, M. (2022). . IET Biometrics.

de Lima, T.A., & Da Costa Abreu, M. (2022). . IET Biometrics.

Da Costa Abreu, M., & Silva, B. (2020). . Revista de Direitos Fundamentais e Tributação, 1 (3), 1-16.

Goncalves de A. S. Marques, J.C., Lima Do Nascimento, T.M., Vasiljevic, B., Alves dos Santos Santana, L.E., & Da Costa Abreu, M. (2020). . Journal of the Brazilian Computer Society, 26 (1), 8.

da Silva, R.S., Da Costa Abreu, M., & Smith, S. (2020). . Evolutionary Intelligence.

Aguiar de Lima, T., & da Costa-Abreu, M. (2019). . Computer Speech & Language, 101055.

Silva, J., Kreutz, M., Pereira, M., & Da Costa Abreu, M. (2019). . Journal of Supercomputing, 1-19.

Da Costa Abreu, M., & Bezerra, G.S. (2019). . Pattern Analysis and Applications, 22 (2), 683-701.

Da Costa Abreu, M.C., & Fairhurst, M. (2011). Enhancing Identity Prediction Using a Novel Approach to Combining Hard- and Soft-Biometric Information. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 41 (5), 599-607.

Da Costa Abreu, M.C., & Fairhurst, M. (2009). Analyzing the Benefits of a Novel Multiagent Approach in a Multimodal Biometrics Identification Task. IEEE Systems Journal, 3 (4), 410-417.

Fairhurst, M.C., & Abreu, M.C.C. (2009). Balancing performance factors in multisource biometric processing platforms. IET Signal Processing, 3 (4), 342-351.

Canuto, A.M.P., Campos, A.M.C., Bezerra, V.M.S., & Abreu, M.C.D.C. (2007). Investigating the use of a multi-agent system for knowledge discovery in databases. International Journal of Hybrid Intelligent Systems, 4 (1), 27-38.

Canuto, A.M.P., Abreu, M.C.C., de Melo Oliveira, L., Xavier, J.C., & Santos, A.D.M. (2007). Investigating the influence of the choice of the ensemble members in accuracy and diversity of selection-based and fusion-based methods for ensembles. Pattern Recognition Letters, 28 (4), 472-486.

Canuto, A.M.P., Fagundes, D., Abreu, M.C.C., & Junior, J.C.X. (2006). Using weighted dynamic classifier selection methods in ensembles with different levels of diversity. International Journal of Hybrid Intelligent Systems, 3 (3), 147-158.

Canuto, A.M., Santos, A.M., Abreu, M.C., Bezerra, V.M., Souza, F.M., & Gomes Junior, M.F. (2004). Investigating the Use of an Agent-Based Multi-classifier System for Classification Tasks. .

Conference papers

Dubinko, N., Bayerl, P.S., Da Costa Abreu, M., & Gibson, H. (2024). Analysing Emotional and Topical Patterns in Conspiracy Theory Narratives: a Discourse Comparative Study on the 2023 Hawaii Wildfires. 2024 14th International Conference on Pattern Recognition Systems (ICPRS), 1-7.

Da Costa Abreu, M., Lycaena Débora, J., Jane, W., Kalinka, B., & Ricardo, M. (2024). Wellness impact of PGR students during COVID-19: A comparative analysis between SHU and USP. In UKCGE Annual Conference 2024, UCL East, Stratford, London, 4 July 2024 - 5 July 2024.

Aguiar, T., & Da Costa Abreu, M. (2023). . 2023 IEEE 13th International Conference on Pattern Recognition Systems (ICPRS).

Silva, B.S.F., & Da Costa Abreu, M. (2022). . In 12th International Conference on Pattern Recognition Systems (ICPRS 2022). IEEE:

Ajao, O., Garg, A., & Da Costa Abreu, M. (2022). . In 12th International Conference on Pattern Recognition Systems (ICPRS 2022). IEEE:

Rannow Budke, J., & Da Costa Abreu, M. (2021). . In 11th International Conference on Pattern Recognition Systems, Curico, Chile, 17 March 2021 - 19 March 2021 (pp. 121-126). IET:

Nascimento, T.M.L.D., Oliveira, A.V.M.D., Santana, L.E.A.D.S., & Da Costa Abreu, M. (2021). . In 11th International Conference on Pattern Recognition Systems, Curico, Chile, 17 March 2021 - 19 March 2021 (pp. 115-120). IET:

Rocha de Azevedo Santos, L., Silla Jr., C., & Da Costa Abreu, M. (2021). . In 11th International Conference on Pattern Recognition Systems, Curico, Chile, 17 March 2021 - 19 March 2021 (pp. 1-6). IET:

Lima do Nascimento, T.M., Alves dos Santos Santana, L.E., & Da Costa Abreu, M. (2021). . In e Eduardo Souto, M.A.H. (Ed.) The 21th Brazilian Symposium on Information and Computer Systems Security (SBSeg 2021), Virtual, 4 October 2021 - 7 October 2021 (pp. 397-402). SBSeg:

de Lima, T.A., & da Costa-Abreu, M. (2021). Investigating the use of multiple languages for crisp and fuzzy speaker identification. IET Conference Publications, 2021 (2021), 19-24.

Araujo De Souza, G., & Da Costa Abreu, M. (2020). . In IEEE World Congress on Computational Intelligence (IEEE WCCI), Glasgow, UK, 19 July 2020 - 24 July 2020. IEEE:

Cavalcante Bandeira, D.R., De Paula Canuto, A.M., Da Costa Abreu, M., Fairhurst, M., Li, C., & Nascimento, D.S.C. (2019). . Proceedings - 2019 Brazilian Conference on Intelligent Systems, BRACIS 2019, 126-131.

Da Costa Abreu, M., & Bruno, S. (2019). . In XIX Brazilian Symposium on Information and Computational Systems Security, São Paulo, Brazil, 2 September 2019 - 5 September 2019 (pp. 1-7). Brazilian Computer Society (SBC):

Lima do Nascimento, T.M., Monteiro de Oliveira, A.V., Da Costa Abreu, M., & Oliveira, L. (2019). . In 19th Brazilian Symposium on Information and Computer System Security (SBSeg 2019), São Paulo, Brazil, 2 September 2019 - 5 September 2019 (pp. 1-4). Brazilian Computer Society (SBC):

Da Costa Abreu, M., & Goncalve, J.C. (2019). . In 19th Brazilian Symposium on Information and Computer System Security (SBSeg 2019), São Paulo, Brazil, 2 September 2019 - 5 September 2019 (pp. 1-6). Brazilian Computer Society (SBC):

Da Costa Abreu, M., & Pereira, M. (2019). . In 39th Brazilian Computer Society Congress (CSBC 2019), Belem, Brazil, 14 July 2019 - 18 July 2019 (pp. 99-103). Brazilian Computer Society (SBC):

Da Costa Abreu, M., & Silveira Silva, R. (2018). . In 18th Brazilian Symposium on Information and Computational Systems Security (SBSeg 2018), Natal, Brazil, 22 October 2018 - 25 October 2018 (pp. 181-184). Brazilian Computer Society (SBC):

Da Silva, V.R., & Da Costa Abreu, M. (2018). . Proceedings of the International Joint Conference on Neural Networks, 2018-J (2018-J).

Da Silva, V.R., De AraújoSilva, J.C.G., & Da Costa Abreu, M. (2018). . IET Seminar Digest, 2016 (2016).

Bittencourt, V.G., Da Costa Abreu, M., Souto, M.C.P.D., Costa, J.A.F., & Canuto, A.M.P. (2016). . Anais do 7. Congresso Brasileiro de Redes Neurais.

Da Silva Beserra, I., Camara, L., & Da Costa Abreu, M. (2016). . IET Seminar Digest, 2016 (2016).

Erbilek, M., Fairhurst, M., & Da Costa Abreu, M. (2013). . 5th International Conference on Imaging for Crime Detection and Prevention, ICDP 2013.

Fairhurst, M., & Da Costa Abreu, M. (2012). . 4th International Conference on Imaging for Crime Detection and Prevention 2011 (ICDP 2011).

Abreu, M., & Fairhurst, M. (2011). Combining Multiagent Negotiation and an Interacting Verification Process to Enhance Biometric-Based Identification. In Lecture Notes in Computer Science, (pp. 95-105). Springer Berlin Heidelberg:

Fairhurst, M.C., & Abreu, M.C.D.C. (2009). An Investigation of Predictive Profiling from Handwritten Signature Data. 2009 10th International Conference on Document Analysis and Recognition, 1305-1309.

Abreu, M., & Fairhurst, M. (2009). Improving forgery detection in off-line forensic signature processing. 3rd International Conference on Imaging for Crime Detection and Prevention (ICDP 2009), P6.

Abreu, M., & Fairhurst, M. (2009). Improving Identity Prediction in Signature-based Unimodal Systems Using Soft Biometrics. In Lecture Notes in Computer Science, (pp. 348-356). Springer Berlin Heidelberg:

Abreu, M., & Fairhurst, M. (2008). Analyzing the impact of non-biometric information on multiclassifier processing for signature recognition applications. 2008 IEEE Second International Conference on Biometrics: Theory, Applications and Systems, 1-6.

Abreu, M., & Fairhurst, M. (2008). An Empirical Comparison of Individual Machine Learning Techniques in Signature and Fingerprint Classification. In Lecture Notes in Computer Science, (pp. 130-139). Springer Berlin Heidelberg:

Canuto, A.M.P., Santana, L.E.A., Abreu, M.C.C., & Xavier, J.C. (2008). . Neurocomputing, 71 (16-18), 3319-3325.

Canuto, A.M.P., & Abreu, M.C.C. (2007). Using Fuzzy, Neural and Fuzzy-Neural Combination Methods in Ensembles with Different Levels of Diversity. In Lecture Notes in Computer Science, (pp. 349-359). Springer Berlin Heidelberg:

Da Costa Abreu, M., & Canuto, A.M.P. (2007). . Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007).

Abreu, M.C.C., & Canuto, A.M.P. (2007). An Experimental Study on the Importance of the Choice of the Ensemble Members in Fuzzy Combination Methods. Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007).

Abreu, M.C.C., & Canuto, A.M.P. (2007). Evaluating the Influence of the Choice of the Ensemble Members in Some Fuzzy Combination Methods. 2007 International Joint Conference on Neural Networks, 448-453.

Santana, L.E.O., Canuto, A.M.P., & Abreu, M.C.C. (2006). . IEEE International Conference on Neural Networks - Conference Proceedings, 2951-2958.

Abreu, M.C.D.C., & Canuto, A.M.P. (2006). . IEEE International Conference on Neural Networks - Conference Proceedings, 2959-2966.

O Santana, L., P Canuto, A., & C Abreu, M. (2006). A Neuro-Fuzzy-Based Agent System with Data Distribution among the Agents for Classification Tasks. 2006 Ninth Brazilian Symposium on Neural Networks (SBRN'06), 27.

Abreu, M.C.C., Canuto, A.M.P., & Santana, L.E.A.S. (2005). A comparative analysis of negotiation methods for a multi-neural agent system. Fifth International Conference on Hybrid Intelligent Systems (HIS'05), 6 pp..

Canuto, A.M.P., Oliveira, L.M., Xavier, J.C., Santos, A.M., & Abreu, M.C.C. (2005). Performance and diversity evaluation in hybrid and non-hybrid structures of ensembles. Fifth International Conference on Hybrid Intelligent Systems (HIS'05), 6 pp..

Bittencourt, V.G., Abreut, M.C.C., de Souto, M.C.P., & de P. Canuto, A.M. An empirical comparison of individual machine learning techniques and ensemble approaches in protein structural class prediction. Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005, 2, 527-531.

Book chapters

(2017). Age predictive biometrics: predicting age from iris characteristics. In Iris and Periocular Biometric Recognition. (pp. 213-234). Institution of Engineering and Technology:

Other activities

External Examiner
Journal Associate Editor
UKRI reviewer

Postgraduate supervision

I have had more than 20 research-based supervisions completed.

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