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Vitor holds a Research position at the University of Porto. His CV includes: - Book lead author on deep learning for time series (published in May 2024) - Published 34 research papers: 15 journal papers (10 Q1) and 18 conference papers (3 CORE Rank A, 13 Rank B, 1 Rank A*) - Highly-cited research with +1250 citations, h-index of 15 and i10-index of 19 - Best paper award in ECML/PKDD’17 (CORE Rank A) - Co-authored 2 patent applications (1 accepted in the US patent office) - Supervision of 15 students (13 MSc, 2 PhD). Lead supervisor for 5 MSc students; Co-supervisor for 2 PhD students (ongoing) and 8 MSc students (2 ongoing) - Developed 4 software packages and technical blog (+330k views, +100k reads) - Principal Investigator in 2 project proposals and participated in 5 funded projects - Principal Investigator in 1 advanced computing project - Developed an international collaboration network across 6 countries. - International research and industry experience in Canada and Germany - PhD granted with honors
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Identification

Personal identification

Full name
Vitor Manuel Araújo Cerqueira

Citation names

  • Cerqueira, Vitor

Author identifiers

Ciência ID
9A1E-20A5-65EA
ORCID iD
0000-0002-9694-8423
Scopus Author Id
56785852000

Knowledge fields

  • Exact Sciences - Computer and Information Sciences - Computer Sciences

Languages

Language Speaking Reading Writing Listening Peer-review
Portuguese Advanced (C1) Advanced (C1) Advanced (C1) Advanced (C1)
English Advanced (C1) Advanced (C1) Advanced (C1) Advanced (C1) Advanced (C1)
Education
Degree Classification
2016/08/01 - 2019/12/20
Concluded
 Doctoral Program in Informatics Engineering (Doutoramento)
Major in Machine Learning
Universidade do Porto Faculdade de Engenharia, Portugal
2012/08/03 - 2014/11/03
Concluded
 Data Analytics (Mestrado)
Major in Network Science
Universidade do Porto Faculdade de Economia, Portugal
2008/09/01 - 2012/01/01
Concluded
 Matemática (Licenciatura)
Major in Matemática Aplicada
Universidade do Porto Faculdade de Ciências, Portugal
Affiliation

Science

Category
Host institution 		Employer
2023/12/01 - Current Researcher (Research) Universidade do Porto Faculdade de Engenharia, Portugal
2021/02/01 - 2023/11/01 Postdoc (Research) Dalhousie University, Canada
2020/02/01 - 2021/02/01 Postdoc (Research) Instituto de Engenharia de Sistemas e Computadores Tecnologia e Ciência, Portugal
2016/01/01 - 2019/12/31 Researcher (Research) Instituto de Engenharia de Sistemas e Computadores Tecnologia e Ciência, Portugal
2015/06/01 - 2015/12/01 Research Assistant (Research) NEC Laboratories Europe, Germany

Teaching in Higher Education

Category
Host institution 		Employer
2018/01/01 - Current Tutor (University Teacher) Universidade do Porto Porto Business School, Portugal
Universidade do Porto Porto Business School, Portugal
2019/02/01 - 2019/07/31 Invited Assistant Professor (University Teacher) Universidade do Porto Faculdade de Engenharia, Portugal
Projects

Grant

Designation Funders
2025/02/15 - 2025/07/01 Benchmarking Deep Learning Approaches for Time Series Forecasting: Empirical Study and Meta-data Collection
2024.12160.CPCA.A0
Principal investigator
Fundação para a Ciência e a Tecnologia
2020/01/01 - 2020/12/01 MetaFlow
MetaFlow
Post-doc Fellow
2019/01/01 - 2019/12/31 Time series forecasting
SFRH/BD/135705/2018
Universidade do Porto Faculdade de Engenharia, Portugal
 Fundação para a Ciência e a Tecnologia
Concluded
2016/01/01 - 2017/12/01 MarineEye
MarineEye
PhD Student Fellow

Contract

Designation Funders
2021/06/01 - 2023/11/01 BigFish
BigFish
Post-doc
2019/01/01 - 2019/12/31 INESC TEC - INESC Technology and Science
UID/EEA/50014/2019
Instituto de Engenharia de Sistemas e Computadores, Portugal

Instituto de Engenharia de Sistemas e Computadores Tecnologia e Ciência, Portugal
Fundação para a Ciência e a Tecnologia
Concluded

Other

Designation Funders
2017/01/01 - 2018/12/31 CORAL
NORTE-01-0145-FEDER-000036
PhD Student Fellow
Concluded
Outputs

Publications

Book
  1. Cerqueira, Vitor; Roque, Luis. Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection. Packt. 2024.
Conference abstract
  1. Bravo, Francisco; Amorim, Joana; Amirkandeh, Melika Besharati; Bodorik, Peter; Cerqueira, Vitor; Gomes, Nuno R.C.; Korus, Jennie; et al. "Advancing Precision Aquaculture Through Big Data Analytics and Machine Learning in Canadian Fish Farming". Paper presented in OCEANS, Halifax, 2024.
    10.1109/oceans55160.2024.10754571
Conference paper
  1. Roque, Luis; Cerqueira, Vitor; Carlos Soares; Luis Torgo. "Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine". Paper presented in Association for the Advancement of Artificial Intelligence 2025, 2025.
    Accepted
  2. Cerqueira, Vitor; Roque, Luis; Soares, Carlos. "Forecasting with Deep Learning: Beyond Average of Average of Average Performance". Paper presented in 27th International Conference on Discovery Science, Pisa, Italy, October 13–17, 2024. Springer International Publishing (CORE Rank B), Pisa, 2024.
    In press
  3. Silva, Inês Oliveira e; Soares, Carlos; Cerqueira, Vitor; Rodrigues, Arlete; Bastardo, Pedro. "Meta-TadGAN: Time Series Anomaly Detection Using TadGAN with Meta-features". Paper presented in EPIA Conference on Artificial Intelligence (CORE Rank B), Viana do Castelo, 2024.
    10.1007/978-3-031-73503-5_28
  4. Leites, José; Cerqueira, Vitor; Soares, Carlos. "Lag Selection for Univariate Time Series Forecasting Using Deep Learning: An Empirical Study". Paper presented in EPIA Conference on Artificial Intelligence (CORE Rank B), Viana do Castelo, 2024.
    10.1007/978-3-031-73503-5_26
  5. Cerqueira, Vitor; Moniz, Nuno; Inácio, Ricardo; Soares, Carlos. "Time Series Data Augmentation as an Imbalanced Learning Problem". Paper presented in EPIA Conference on Artificial Intelligence (CORE Rank B), Viana do Castelo, 2024.
    10.1007/978-3-031-73500-4_28
  6. Ribeiro, B; Cerqueira, V; Santos, R; Gamboa, H. "Layered Learning for Acute Hypotensive Episode Prediction in the ICU: An Alternative Approach". Paper presented in International Conference on e-Health and Bioengineering (EHB). IEEE, 2021.
    10.1109/ehb52898.2021.9657577
  7. Barros, Filipa; Cerqueira, Vitor; Soares, carlos. "Empirical Study on the Impact of Different Sets of Parameters of Gradient Boosting Algorithms for Time-Series Forecasting with LightGBM". Paper presented in PRICAI 2021: Trends in Artificial Intelligence: 18th Pacific Rim International Conference on Artificial Intelligence (CORE Rank B), Hanoi, 2021.
    10.1007/978-3-030-89188-6_34
  8. Cerqueira, Vitor; Gomes, Heitor; Bifet, Albert. "Unsupervised Concept Drift Detection Using a Student-Teacher Approach". Paper presented in 23rd International Conference on Discovery Science, DS 2020, Thessaloniki, Greece, October 19–21 (CORE Rank B), Thessaloniki, 2020.
    10.1007/978-3-030-61527-7_13
  9. Cerqueira, V; Torgo, L; Soares, C. "Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes". Paper presented in 22nd International Conference on Discovery Science, DS 2019, Split, Croatia, October 28–30 (CORE Rank B), Split, 2019.
    10.1007/978-3-030-33778-0_33
  10. Moniz, N; Ribeiro, RP; Cerqueira, V; Chawla, N. "SMOTEBoost for Regression: Improving the Prediction of Extreme Values". Paper presented in 5th international conference on data science and advanced analytics, DSAA, IEEE (CORE Rank B), 2018.
    10.1109/dsaa.2018.00025
  11. Cerqueira, V; Pinto, F; Torgo, L; Soares, C; Moniz, N. "Constructive Aggregation and Its Application to Forecasting with Dynamic Ensembles". Paper presented in Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018 (CORE Rank A), Dublin, 2018.
    10.1007/978-3-030-10925-7_38
  12. Cerqueira, V.; Torgo, L.; Soares, C.. "Arbitrated ensemble for solar radiation forecasting". Paper presented in 14th International Work-Conference on Artificial Neural Networks, IWANN (CORE Rank B), Cadiz, 2017.
    10.1007/978-3-319-59153-7_62
  13. Cerqueira, V; Torgo, L; Oliveira, M; Pfahringer, B. "Dynamic and Heterogeneous Ensembles for Time Series Forecasting". Paper presented in International conference on data science and advanced analytics IEEE-DSAA (CORE Rank B), 2017.
    10.1109/dsaa.2017.26
  14. Cerqueira, V; Torgo, L; Pinto, F; Soares, C. "Arbitrated Ensemble for Time Series Forecasting". Paper presented in Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD (CORE Rank A, BEST PAPER), Skopje, 2017.
    10.1007/978-3-319-71246-8_29
  15. Cerqueira, V; Torgo, L; Smailovic, J; Mozetic, I. "A Comparative Study of Performance Estimation Methods for Time Series Forecasting". Paper presented in International conference on data science and advanced analytics, DSAA IEEE (CORE Rank B), 2017.
    10.1109/dsaa.2017.7
  16. Cerqueira, V.; Pinto, F.; Sá, C.; Soares, C.. "Combining boosted trees with metafeature engineering for predictive maintenance". Paper presented in Advances in Intelligent Data Analysis: 15th International Symposium, IDA (CORE Rank B), Stockholm, 2016.
    10.1007/978-3-319-46349-0_35
  17. Moreira-Matias, L.; Cerqueira, V.. "CJAMmer - Traffic jam cause prediction using boosted trees". Paper presented in 19th International Conference on Intelligent Transportation Systems, IEEE-ITSC (CORE Rank B), 2016.
    10.1109/ITSC.2016.7795637
  18. Khiari, J.; Moreira-Matias, L.; Cerqueira, V.; Cats, O.. "Automated setting of bus schedule coverage using unsupervised machine learning". Paper presented in Advances in Knowledge Discovery and Data Mining: 20th Pacific-Asia Conference, PAKDD (CORE Rank A), Auckland, 2015.
    10.1007/978-3-319-31753-3_44
  19. Cerqueira, V.; Oliveira, M.; Gama, J.. "A framework for analysing dynamic communities in large-scale social networks". Paper presented in International Conference on Enterprise Information Systems (CORE Rank C), Barcelona, 2015.
    10.5220/0005345602350242
Conference poster
  1. INACIO, RICARDO; Cerqueira, Vitor; Barandas, Marília; Soares, Carlos. "Meta-learning and Data Augmentation for Stress Testing Forecasting Models". Paper presented in Discovery Science 2024, 2024.
Journal article
  1. Cerqueira, Vitor; Torgo, Luis; Bontempi, Gianluca. "Instance-based meta-learning for conditionally dependent univariate multi-step forecasting". International Journal of Forecasting 40 4 (2024): 1507-1520. http://dx.doi.org/10.1016/j.ijforecast.2023.12.010.
    10.1016/j.ijforecast.2023.12.010
  2. Cerqueira, Vitor; Pimentel, João; Korus, Jennie; Bravo, Francisco; Amorim, Joana; Oliveira, Mariana; Swanson, Andrew; et al. "Forecasting ocean hypoxia in salmonid fish farms". Frontiers in Aquaculture 3 (2024): http://dx.doi.org/10.3389/faquc.2024.1365123.
    10.3389/faquc.2024.1365123
  3. Ziffer, Giacomo; Bernardo, Alessio; Della Valle, Emanuele; Cerqueira, Vitor; Bifet, Albert. "Towards time-evolving analytics: Online learning for time-dependent evolving data streams". Data Science 6 1-2 (2023): 1-16. http://dx.doi.org/10.3233/ds-220057.
    10.3233/ds-220057
  4. Cerqueira, Vitor; Torgo, Luis; Soares, Carlos. "Model Selection for Time Series Forecasting An Empirical Analysis of Multiple Estimators". Neural Processing Letters 55 7 (2023): 10073-10091. http://dx.doi.org/10.1007/s11063-023-11239-8.
    10.1007/s11063-023-11239-8
  5. Cerqueira, V; Torgo, L; Soares, C. "Early anomaly detection in time series: a hierarchical approach for predicting critical health episodes". MACHINE LEARNING (2023):
    10.1007/s10994-022-06300-x
  6. Cerqueira, Vitor; Torgo, Luis; Branco, Paula; Bellinger, Colin. "Automated imbalanced classification via layered learning". Machine Learning 112 6 (2022): 2083-2104. http://dx.doi.org/10.1007/s10994-022-06282-w.
    10.1007/s10994-022-06282-w
  7. Cerqueira, Vitor; Gomes, Heitor Murilo; Bifet, Albert; Torgo, Luis. "STUDD: a student–teacher method for unsupervised concept drift detection". Machine Learning 112 11 (2022): 4351-4378. http://dx.doi.org/10.1007/s10994-022-06188-7.
    10.1007/s10994-022-06188-7
  8. Cerqueira, V; Torgo, L; Soares, C. "A case study comparing machine learning with statistical methods for time series forecasting: size matters". JOURNAL OF INTELLIGENT INFORMATION SYSTEMS (2022):
    10.1007/s10844-022-00713-9
  9. Pereira, Luis Nobre; Cerqueira, Vitor. "Forecasting hotel demand for revenue management using machine learning regression methods". Current Issues in Tourism 25 17 (2021): 2733-2750. http://dx.doi.org/10.1080/13683500.2021.1999397.
    10.1080/13683500.2021.1999397
  10. Moniz, N; Cerqueira, V. "Automated imbalanced classification via meta-learning". EXPERT SYSTEMS WITH APPLICATIONS (2021):
    10.1016/j.eswa.2021.115011
  11. Cerqueira, V; Moniz, N; Soares, C. "VEST: automatic feature engineering for forecasting". MACHINE LEARNING (2021):
    10.1007/s10994-021-05959-y
  12. Cerqueira, V; Torgo, L; Mozetic, I. "Evaluating time series forecasting models: an empirical study on performance estimation methods". MACHINE LEARNING (2020):
    10.1007/s10994-020-05910-7
  13. Cerqueira, V; Torgo, L; Pinto, F; Soares, C. "Arbitrage of forecasting experts". MACHINE LEARNING (2019):
    10.1007/s10994-018-05774-y
  14. Cerqueira, V; Moreira Matias, L; Khiari, J; van Lint, H. "On Evaluating Floating Car Data Quality for Knowledge Discovery". IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2018):
    10.1109/tits.2018.2867834
  15. Mozetic, I; Torgo, L; Cerqueira, V; Smailovic, J. "How to evaluate sentiment classifiers for Twitter time-ordered data?". PLOS ONE (2018):
    10.1371/journal.pone.0194317
Preprint
  1. Cerqueira, Vitor; Torgo, L. "Exceedance Probability Forecasting via Regression for Significant Wave Height Forecasting". 2024.
  2. Cerqueira, Vitor; Santos, Moisés; Baghoussi, Yassine; Soares, Carlos. "On-the-fly Data Augmentation for Forecasting with Deep Learning". 2024. https://arxiv.org/pdf/2404.16918.
  3. Cerqueira, Vitor; Torgo, Luis. "Multi-output Ensembles for Multi-step Forecasting". 2023.
  4. Costa, P; Cerqueira, V; Vinagre, J. "AutoFITS: Automatic Feature Engineering for Irregular Time Series". 2021.
  5. Cerqueira, V; Torgo, L; Soares, C; Bifet, A. "Model Compression for Dynamic Forecast Combination". 2020.
  6. Pinto, F.; Cerqueira, V.; Soares, C.; Mendes-Moreira, J.. "Autobagging: Learning to rank bagging workows with metalearning". 2017.

Intellectual property

Patent
  1. Moreira-Matias, L.; Cerqueira, Vitor. 2018. "Real-time filtering of digital data sources for traffic control centers".
Activities

Oral presentation

Presentation title Event name
Host (Event location)
2022 Machine Learning for Time Series Forecasting Keynote speaker
Sennder, Germany (Germany)
2020 Towards Unsupervised Concept Drift Detection Machine Learning Seminars at Waikato University
Waikato University (New Zealand)
2017/08/01 Arbitrage of Forecasting Experts Invited talk
Farfetch (Portugal)
2017/07/01 Arbitrage of Forecasting Experts Invited talk
Feedzai (Portugal)

Supervision

Thesis Title
Role 		Degree Subject (Type)
Institution / Organization
2024/09/01 - Current Bridging the gap between forecasting accuracy and utility: case study with forex trading
Supervisor
Universidade do Porto Faculdade de Engenharia, Portugal
2024/09 - Current Enhancing Time Series Forecasting with a Deep Learning-Based Mixture of Experts Framework
Supervisor
Universidade do Porto Faculdade de Engenharia, Portugal
2024/09 - Current Predicting the Weights of Neural Networks using Meta-learning
Supervisor
Universidade do Porto Faculdade de Engenharia, Portugal
2024/09 - Current Stress testing forecasting models using resampling methods
Supervisor
Universidade do Porto Faculdade de Engenharia, Portugal
2024/09 - Current Feature engineering for predictive maintenance
Supervisor
Universidade do Porto Faculdade de Engenharia, Portugal
2023/09 - Current Stress-Testing of Multimodal Models in Medical Image-Based Report Generation
Co-supervisor
Universidade do Porto Faculdade de Engenharia, Portugal
2023 - Current GASReN: Generative Adversarial Stress Resistant Networks for Time Series Forecasting – an Application to Finance
Co-supervisor
Universidade do Porto Faculdade de Engenharia, Portugal
2023/01/01 - 2023/08/01 XTadGAN: Generative Adversarial Networks to Detect Extremely Rare Anomalies
Co-supervisor
Universidade do Porto Faculdade de Engenharia, Portugal
2022/09/01 - 2023 LEVERAGING CLUSTERING ANALYSIS FOR GLOBAL FORECASTING MODELS: A CASE STUDY WITH BUOY SIGNIFICANT WAVE HEIGHT
Co-supervisor
Dalhousie University, Canada
2022/02/01 - 2022/12/01 Prediction of dividend yields
Co-supervisor
 Engenharia de Redes e Sistemas Informáticos (Master)
Universidade do Porto Faculdade de Ciências, Portugal
2021/06/01 - 2022/02/01 Machine Learning for the Early Detection of Acute Episodes in Intensive Care Units
Co-supervisor
 MASTER IN BIOMEDICAL ENGINEERING (Master)
Universidade Nova de Lisboa, Portugal
2021/01/01 - 2021/12/01 AutoFITS: Automated feature engineering for irregular time-series
Co-supervisor
 Engenharia de Redes e Sistemas Informáticos (Master)
Universidade do Porto Faculdade de Ciências, Portugal
2018/08/24 - 2019/07/12 Ordinal Regression for Stress Levels Classification in Real-World Scenarios
Co-supervisor
Universidade do Porto Faculdade de Engenharia, Portugal

Event organisation

Event name
Type of event (Role) 		Institution / Organization
2021/10/01 - 2021/10/05 Member of local organizing committee of Discovery Science 2021 (2021/10/01 - 2021/10/05)
Conference (Member of the Organising Committee)
2019/06/28 - 2019/06/29 Symposium Committee Member (2019/06/28 - 2019/06/29)
Congress (Member of the Organising Committee)

Committee member

Activity description
Role 		Institution / Organization
2023/06 - Current Thesis Monitoring Committee member Doctoral thesis: Optimizing locality and globality in large scale operational forecasting through Deep Reinforcement Learning
Member
 Universidade Nova de Lisboa, Portugal
2022/06/01 - 2023 Guest Editor at Special Issue of Machine Learning journal
Member
Distinctions

Award

2019 Ph.D. Cum Laude
Universidade do Porto Faculdade de Engenharia, Portugal
2017 Best Student Machine Learning Paper Award
ECML PKDD , Macedonia
2017 Best Paper Award
Doctoral Symposium in Informatics Engineering, Portugal

Other distinction

2017 "Fora de Série" - investigador do mês (outubro)
Instituto de Engenharia de Sistemas e Computadores Tecnologia e Ciência, Portugal