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Teaching Staff

Biography

Roberto Henriques is currently Associate Professor at NOVA IMS from NOVA University, where he is the Associate Dean for Education and Pedagogical Affairs. He is also the coordinator of the Masters in Data Science and Advanced Analytics. He holds a Ph.D. in Information Management (NOVA), a Masters in Geographic Information Systems and Science, and a degree in Biophysics Engineering. His research interest includes data analytics and decision support systems using artificial intelligence and machine learning methods. His work has been published in several international high-quality journals and conferences. He has also been involved in several projects, including health clinical analytics, customer management, and data mining.

Scientific Publications

Hajek, P., & Henriques, R. (2024)

Predicting M&A targets using news sentiment and topic detection. Technological Forecasting and Social Change, 201, 1-12. Article 123270. https://doi.org/10.1016/j.techfore.2024.123270

Sousa, J., & Henriques, R. (2024)

Intersecting reinforcement learning and deep factor methods for optimizing locality and globality in forecasting: A review. Engineering Applications Of Artificial Intelligence, 133, Part B, 1-25. Article 108082. https://doi.org/10.1016/j.engappai.2024.108082

Barsalou, M., Saraiva, P. M., & Henriques, R. (2023)

Exploring Exploratory Data Analysis: An Empirical Test of Run Chart Utility. Management Systems in Production Engineering, 31(4), 442-448. https://doi.org/10.2478/mspe-2023-0050

Elbawab, M., & Henriques, R. (2023)

Machine Learning applied to student attentiveness detection: Using emotional and non-emotional measures. Education and Information Technologies, 28(12), 15717–15737. https://doi.org/10.1007/s10639-023-11814-5

Henriques, R., & Pinto, L. (2023)

A novel evaluation framework for recommender systems in big data environments. Expert Systems with Applications, 231, 1-13. [120659]. https://doi.org/10.1016/j.eswa.2023.120659

Jacob, D., & Henriques, R. (2023)

Educational Data Mining to Predict Bachelors Students’ Success. Emerging Science Journal, 7(Special Issue, "Current Issues, Trends, and New Ideas in Education"), 159-171. https://doi.org/10.28991/ESJ-2023-SIED2-013

Oliveira, M., Seringa, J., Pinto, F. J., Henriques, R., & Magalhães, T. (2023)

Machine learning prediction of mortality in Acute Myocardial Infarction. BMC Medical Informatics and Decision Making, 23(1), 1-16. [70]. https://doi.org/10.1186/s12911-023-02168-6

Pina, A. F., Meneses, M. J., Sousa-Lima, I., Henriques, R., Raposo, J. F., & Macedo, M. P. (2023)

Big data and machine learning to tackle diabetes management. European Journal Of Clinical Investigation, 53 (1), e13890. https://doi.org/10.1111/eci.13890

Santos, R. M., & Henriques, R. (2023)

Accurate, timely, and portable: Course-agnostic early prediction of student performance from LMS logs. Computers and Education: Artificial Intelligence, 5, 1-15. [100175]. https://doi.org/10.1016/j.caeai.2023.100175

Victorino, G., Coelho, P. S., & Henriques, R. (2023)

The Value of Design Thinking for PhD Students: A Retrospective Longitudinal Study. Emerging Science Journal, 7(Special Issue: Trends, and New Ideas in Education), 16-31. https://doi.org/10.28991/ESJ-2023-SIED2-02

Guan, Y., Fernandes, M. L. D. C., & Henriques, R. (2023)

Comparing The Effectiveness Of Face-To-Face, Emergency Remote, And Hybrid Teaching Approaches: A Case Study Of An Information Management School. In L. Gómez Chova, C. González Martínez, & J. Lees (Eds.), 15th  International Conference on Education and New Learning Technologies July 3rd  -5th  , 2023 Palma, Spain (pp. 6107-6116). (EDULEARN23 Proceedings; No. 2023). IATED Academy. https://doi.org/10.21125/edulearn.2023.1594

Henriques, R., Oliveira, L., Santos, R., & Albuquerque, C. (2023)

Implementing Team-Based Learning In Data Science Education: Enhancing Student Satisfaction And Performance. In L. Gómez Chova, C. González Martínez, & J. Lees (Eds.), 15th  International Conference on Education and New Learning Technologies July 3rd  -5th  , 2023 Palma, Spain (pp. 6720-6729). (EDULEARN23 Proceedings; No. 2023). IATED Academy. https://doi.org/10.21125/edulearn.2023.1770

Pesovski, I., Santos, R., Trajkovik, V., & Henriques, R. (2023)

Comparing Perception and Reality: Exploring Test Complexity and Student Performance in Higher Education. In L. G. Chova, C. G. Martínez, & J. Lees (Eds.), 16th  International Conference of Education, Research and Innovation (pp. 6654-6660). (ICERI Proceedings). IATED Academy. https://doi.org/10.21125/iceri.2023.1660

Santos, R. M. C., & Henriques, R. (2023)

Predicting student performance from Moodle logs in higher education: A course-agnostic approach. In M. Carmo (Ed.), Education and New Developments 2023 (Vol. 2, pp. 77-81). Science Press. https://end-educationconference.org/wp-content/uploads/2023/06/Education-and-New-Developments_2023_Vol_II.pdf

Santos, R., & Henriques, R. (2023)

Grouping Bachelor's Students According To Their Moodle Interaction Profiles: A K-Means Clustering Approach. In L. Gómez Chova, C. González Martínez, & J. Lees (Eds.), 15th  International Conference on Education and New Learning Technologies July 3rd  -5th  , 2023 Palma, Spain (pp. 7383-7389). (EDULEARN23 Proceedings; No. 2023). IATED Academy. https://doi.org/10.21125/edulearn.2023.1920

Albuquerque, C., Henriques, R., & Castelli, M. (2022)

A stacking-based artificial intelligence framework for an effective detection and localization of colon polyps. Scientific Reports, 12, 1-12. [17678]. https://doi.org/10.21203/rs.3.rs-1862362/v1, https://doi.org/10.1038/s41598-022-21574-w

Henriques, R., Ferreira, A., & Castelli, M. (2022)

A Use Case of Patent Classification Using Deep Learning with Transfer Learning. Journal of Data and Information Science, 7(3), 49-70. https://doi.org/10.2478/jdis-2022-0015

Principe, V. A., de Souza Vale, R. G., de Castro, J. B. P., Carvano, L. M., Henriques, R. A. P., Lobo, V. J. D. A. E. S., & de Alkmim Moreira Nunes, R. (2022)

A computational literature review of football performance analysis through probabilistic topic modeling. Artificial Intelligence Review, 55(2). [Advanced online publication on 4 April 2021]. https://doi.org/10.1007/s10462-021-09998-8

Victorino, G., Bandeira, R., Painho, M., Henriques, R., & Coelho, P. S. (2022)

Rethinking the Campus Experience in a Post-COVID World: A Multi-Stakeholder Design Thinking Experiment. Sustainability (Switzerland), 14(13), 1-13. [7655]. https://doi.org/10.3390/su14137655

Albuquerque, C., Vanneschi, L., Henriques, R., Castelli, M., Póvoa, V., Fior, R., & Papanikolaou, N. (2021)

Object detection for automatic cancer cell counting in zebrafish xenografts. PLoS ONE, 16(11), 1-28. [e0260609]. https://doi.org/10.1371/journal.pone.0260609

Silva, M. I., & Henriques, R. (2021)

TripMD: Driving patterns investigation via motif analysis. Expert Systems with Applications, 184, 1-12. [115527]. https://doi.org/10.1016/j.eswa.2021.115527

G. Victorino, R. Henriques (2021)

DESIGN OF LEARNING ENVIRONMENTS: A ROOM AFFECTING WHAT WE DO AND HOW WE FEEL. In EDULEARN21 Proceedings, pp. 10849-10859. (13th  International Conference on Education and New Learning Technologies, Dates: 5-6 July, 2021 (online)). ISBN: 978-84-09-31267-2. ISSN: 2340-1117. doi: 10.21125/edulearn.2021.2256

Victorino, G., Henriques, R., & Bandeira, R. (2021)

Teaching Design Thinking in times of COVID-19: an online learning experience. In J. Domenech, P. Merello, & E. D. L. Poza (Eds.), 7th  International Conference on Higher Education Advances (HEAd’21) (pp. 263-270). Editorial Universitat Politècnica de València. https://doi.org/10.4995/HEAD21.2021.13621

Castelli, M., Dobreva, M., Henriques, R., & Vanneschi, L. (2020)

Predicting Days on Market to Optimize Real Estate Sales Strategy. Complexity, 2020, 1-22. [4603190]. https://doi.org/10.1155/2020/4603190

Pina, A. L. F., Patarrao, R. S., Ribeiro, R. T., Penha-Goncalves, C., Raposo, J. F., Gardete-Correia, L., Duarte, R., M. Boavida, J., L. Medina, J., Henriques, R., & Macedo, M. P. (2020)

Metabolic Footprint, towards Understanding Type 2 Diabetes beyond Glycemia. Journal of Clinical Medicine, 9(8), [2588]. https://doi.org/10.3390/jcm9082588

Pina, A., Helgadottir, S., Mancina, R. M., Pavanello, C., Pirazzi, C., Montalcini, T., … Romeo, S. (2020)

Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning. European Journal of Preventive Cardiology. [Advanced online publication February 4, 2020]. Doi: https://doi.org/10.1177/2047487319898951

Silva, M. I & Henriques, R. (2020)

Finding manoeuvre motifs in vehicle telematics. Accident Analysis & Prevention, 138,(April), 105467. https://doi.org/10.1016/j.aap.2020.105467

Pina, A., Macedo, M. P., & Henriques, R. (2020)

Clustering Clinical Data in R. Methods In Molecular Biology (Clifton, N.J.), 2051, 309-343. https://doi.org/10.1007/978-1-4939-9744-2_14

Alceo, P., & Henriques, R. (2020)

Beat the Streak: Prediction of MLB Base Hits Using Machine Learning. In A. Fred, A. Fred, A. Salgado, D. Aveiro, J. Dietz, J. Bernardino, & J. Filipe (Eds.), Knowledge Discovery, Knowledge Engineering and Knowledge Management: 11th  International Joint Conference, IC3K 2019, Revised Selected Papers (pp. 108-133). (Communications in Computer and Information Science; Vol. 1297). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-66196-0_6

Silva, M. I., & Henriques, R. (2020)

Exploring time-series motifs through DTW-SOM. In 2020 International Joint Conference on Neural Networks, IJCNN: 2020 Conference Proceedings (pp. 1-8). [9207614] (Proceedings of the International Joint Conference on Neural Networks). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN48605.2020.9207614

Campos, S. R. M. D., Henriques, R., & Yanaze, M. H. (2019)

Knowledge discovery through higher education census data. Technological Forecasting and Social Change, 149, [119742]. https://doi.org/10.1016/j.techfore.2019.119742

Costa, A., Guerreiro, J., Moro, S., & Henriques, R. (2019)

Unfolding the characteristics of incentivized online reviews. Journal of Retailing and Consumer Services, 47, 272-281. DOI: 10.1016/j.jretconser.2018.12.006

Hajek, P., Henriques, R., Castelli, M., & Vanneschi, L. (2019)

Forecasting performance of regional innovation systems using semantic-based genetic programming with local search optimizer. Computers and Operations Research, 106(June), 179-190. [advanced online on 7 February 2018]https://doi.org/10.1016/j.cor.2018.02.001 . Doi: https://doi.org/10.1016/j.cor.2018.02.001

Santa, F., Henriques, R., Torres-Sospedra, J., & Pebesma, E. (2019)

A statistical approach for studying the spatio-temporal distribution of geolocated tweets in urban environments. Sustainability (Switzerland), 11(3), [595]. DOI: 10.3390/su11030595

Alceo, P., & Henriques, R. (2019)

Sports Analytics: maximizing precision in predicting MLB base hits. In A. Fred, & J. Filipe (Eds.), Proceedings of the 11th  International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) (pp. 190-201). (IC3K 2019 - Proceedings of the 11th  International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management; Vol. 1). SciTePress. https://doi.org/10.5220/0008362201900201

De Campos, S. R. M., & Henriques, R. (2019)

THE BRAZILIAN HIGHER EDUCATION: THE UNDERGRADUATE COURSES IN LIGHT OF ITS RECENT POLICIES. In M. Carmo (Ed.), Education and New Developments 2019 (Vol. II, pp. 371-375). InScience Press. https://doi.org/10.36315/2019v2end084

Dias, H., & Henriques, R. (2019)

Augmenting data warehousing architectures with Hadoop. In Proceedings of the 19th  Portuguese Association of Information Systems Conferemce: digital disruption: living between data science, IoT and ... people (pp. 27). Associação Portuguesa de Sistemas de Informação.

Duarte, A., Henriques, R., & Ribeiro, S. (2019)

Use of different optimization algorithms to define service areas of police stations in Portugal . In Evidence-based territorial policymaking: formulation, implementation and evaluation of policy: 26th  APDR Congress Proceedings (pp. 108-115). Associacao Portuguesa para o Desenvolvimento Regional (APDR).

Joshi, A., Pebesma, E., Henriques, R., & Appel, M. (2019)

Scidb based framework for storage and analysis of remote sensing big data. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 42(5/W3), 43-47. https://doi.org/10.5194/isprs-archives-XLII-5-W3-43-2019

Bação, F. J. F. L., Henriques, R., & Antunes, J. (2017)

Contribution Towards Smart Cities: Exploring Block Level Census Data for the Characterization of Change in Lisbon. In M. Behnisch, & G. Meinel (Eds.), Trends in Spatial Analysis and Modelling: Decision-Support and Planning Strategies (pp. 59-73). [Chapter 4] (Geotechnologies and the Environment; Vol. 19). Springer. https://doi.org/10.1007/978-3-319-52522-8_4

Beretta, S., Castelli, M., Goncalves, I., Henriques, R., & Ramazzotti, D. (2018)

Learning the Structure of Bayesian Networks: A Quantitative Assessment of the Effect of Different Algorithmic Schemes. Complexity, [1591878]. DOI: 10.1155/2018/1591878

Galvão, M. & Henriques, R. (2018)

Forecasting Movie Box Office Profitability. Journal of Information Systems Engineering & Management, 3(3), 22. https://doi.org/10.20897/jisem/2658

Ribeiro, S., Cabral, P., Henriques, R., Bravo, J., Rodrigues, T., & Painho, M. (2018)

Modelação do crescimento urbano para a distribuição eficaz das forças de segurança: o caso português. PROELIUM – Revista da Academia Militar, 7(14), 45-68.

Ribeiro, S. & Henriques, R. (2018)

Aplicação de Self-Organizing Maps na análise da criminalidade em Portugal, 2011,2016. In T. Rodrigues, & M. Painho (Eds.), Modelos preditivos e segurança pública (pp. 253-280). Porto: Fronteira do Caos. ISBN: 978-989-54148-7-1

Ribeiro, S., Henriques, R. & Castelli, M. (2018)

Modelo de otimização. In T. Rodrigues, & M. Painho (Eds.), Modelos preditivos e segurança pública (pp. 281-302). Porto: Fronteira do Caos. ISBN: 978-989-54148-7-1

Bernardo, I., Henriques, R., & Lobo, V. (2018)

Social market: Stock market and twitter correlation. In Intelligent Decision Technologies 2017: Proceedings of the 9th  KES International Conference on Intelligent Decision Technologies, KES-IDT 2017 (pp. 341-356) (advanced online publication on 26 May 2017). (Smart Innovation, Systems and Technologies; Vol. 73). DOI: 10.1007/978-3-319-59424-8_32

de Campos, S. R. M., & Henriques, R. (2018)

The knowledge discovery through the student's higher education census data. In Proceedings of CISTI 2018: 13th  Iberian Conference on Information Systems and Technologies [Memorias de la CISTI 2018: 13a Conferencia Iberica de Sistemas y Tecnologias de Informacion] (Vol. 2018, pp. 1-6). IEEE Computer Society. DOI: 10.23919/CISTI.2018.8399164

Galvao, M., & Henriques, R. (2018)

Forecasting model of a movie's profitability. In Proceedings of CISTI 2018: 13th  Iberian Conference on Information Systems and Technologies [Memorias de la CISTI 2018: 13a Conferencia Iberica de Sistemas y Tecnologias de Informacion] (Vol. 2018, pp. 1-6). IEEE Computer Society. DOI: 10.23919/CISTI.2018.8399184

Henriques, R., & Feiteira, I. (2018)

Predictive modelling: Flight delays and associated factors, Hartsfield-Jackson Atlanta international airport. Procedia Computer Science, 138, 638-645. CENTERIS - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN/HCist, 21-23 november 2018, Lisbon, Portugal. https://doi.org/10.1016/j.procs.2018.10.085

Tsakalos, V., & Henriques, R. (2018)

Sentiment classification using N-ary tree-structured gated recurrent unit networks. In A. Fred, & J. Filipe (Eds.), Proceedings of the 10th  International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) (Vol. 1, pp. 149-154). (IC3K 2018; Seville; Spain; 18-September) Scitepress. ISBN: 978-989-758-330-8. DOI: 10.5220/0006894201490154

Adeoluwa Akande, Ana Cristina Costa, Jorge Mateu and Roberto Henriques (2017)

Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps. Advances in Meteorology, 2017, Article ID 8576150, 11 p. https://doi.org/10.1155/2017/8576150

de Campos, S. R. M., Henriques, R., & Yanaze, M. H. (2017)

Higher education in Brazil: an exploratory study based on supply and demand conditions. Universal Access in the Information Society, 1-23 (advanced online publication on 24 april 2017). DOI: 10.1007/s10209-017-0537-9

Leonardo Vanneschi; Roberto Henriques; Mauro Castelli (2017)

Multi-objective genetic algorithm with variable neighbourhood search for the electoral redistricting problem. Swarm and Evolutionary Computation, 36, 37-51. https://doi.org/10.1016/j.swevo.2017.04.003

Petr Hajek & Roberto Henriques (2017)

Mining Corporate Annual Reports for Intelligent Detection of Financial Statement Fraud - A Comparative Study of Machine Learning Methods. Knowledge-Based Systems, 128, 139-152. https://doi.org/10.1016/j.knosys.2017.05.001

Petr Hajek & Roberto Henriques (2017)

Modelling innovation performance of European regions using multi-output neural networks. PLoS ONE 12(10): e0185755. doi: https://doi.org/10.1371/journal.pone.0185755

Vitor Principe, Luiz Octáio Gavião, Roberto Henriques, Victor Lobo, Gilson Brito Alves Lima and Annibal Parracho Sant’anna (2017)

Multicriteria Analysis of Football Match Performances: Composition Of Probabilistic Preferences Applied To The English Premier League 2015/2016. Pesquisa Operacional, 37 (2), 333-363. DOI: 10.1590/0101-7438.2017.037.02.0333

Monteiro, R. Cabral, P. D. C. B., & Henriques, R. (2017)

Crawling public massive data to solve air traffic data issues. In Atas da 12a Conferencia Iberica de Sistemas e Tecnologias de Informacao, CISTI 2017 / Proceedings of the 12th  Iberian Conference on Information Systems and Technologies, CISTI 2017 [7976006] IEEE Computer Society. DOI: 10.23919/CISTI.2017.7976006

Ribeiro, S., Caineta, J., Costa, A. C., Henriques, R., & Soares, A. (2016)

Detection of inhomogeneities in precipitation time series in Portugal using direct sequential simulation. Atmospheric Research, 171, 147-158. doi: http://dx.doi.org/10.1016/j.atmosres.2015.11.014

De Campos, S. R. M., Henriques, R., & Yanaze, M. H. (2016)

Governance of higher education institutions in brazil: An exploratory study based on supply and demand conditions. Paper presented at the Advances in Intelligent Systems and Computing.

Castelli, M., Henriques, R., & Vanneschi, L. (2015)

A geometric semantic genetic programming system for the electoral redistricting problem. Neurocomputing, 154, 200-207. doi: 10.1016/j.neucom.2014.12.003

Hajek, P., Henriques, R., & Hajkova, V. (2014)

Visualising components of regional innovation systems using self-organizing maps-Evidence from European regions. [Article]. Technological Forecasting and Social Change, 84, 197-214. doi: 10.1016/j.techfore.2013.07.013

Monteiro, V., Henriques, R., Painho, M., & Vaz, E. (2014)

Sensing World Heritage. In B. Murgante, S. Misra, A. C. Rocha, C. Torre, J. Rocha, M. Falcão, D. Taniar, B. Apduhan & O. Gervasi (Eds.), Computational Science and Its Applications – ICCSA 2014 (Vol. 8580, pp. 404-419): Springer International Publishing.

Fernandes, L., Henriques, R., & Lobo, V. (2014)

Selection of instances in Condition Based Monitoring: the case of aircraft engines. Paper presented at the Maintenance Performance Measurement and Management (MPMM) Conference 2014, Coimbra.

Henriques, R., Bacao, F., & Lobo, V. (2012)

Exploratory geospatial data analysis using the GeoSOM suite. Computers Environment and Urban Systems, 36(3), 218-232. doi: 10.1016/j.compenvurbsys.2011.11.003

Henriques, R., Lobo, V., & Bação, F. (2012)

Spatial Clustering Using Hierarchical SOM. In M. Johnsson (Ed.), Applications of Self-Organizing Maps: InTech.

Painho, M., Henriques, R., Oliveira, T. M., Seabra, I., Leitão, J., Laginha, C., & Neves, M. (2012)

Outputs from SIGGESC: bus lines management geographic information system. Paper presented at the ESRI International Conference, California.

Henriques, R., Bacao, F., & Lobo, V. (2009)

Carto-SOM: cartogram creation using self-organizing maps. International Journal of Geographical Information Science, 23(4), 483-511.

Henriques, R., Bação, F., & Lobo, V. (2009)

Cartograms, Self-Organizing Maps, and Magnification Control. Paper presented at the Advances in Self-Organizing Maps 7th  International Workshop, WSOM 2009, St. Augustine, USA.

Henriques, R., Bacao, F., & Lobo, V. (2009)

GeoSOM Suite: A Tool for Spatial Clustering. In O. Gervasi, D. Taniar, B. Murgante, A. Lagana, Y. Mun & M. L. Gavrilova (Eds.), Computational Science and Its Applications - Iccsa 2009, Pt I (Vol. 5592, pp. 453-466). Berlin: Springer-Verlag Berlin.

Henriques, R., Bacao, F., & Lobo, V. (2009)

UAV path planning based on event density detection. In S. Dragicevic, D. Roman & V. Tanasescu (Eds.), International Conference on Advanced Geographic Information Systems and Web Services: Geows 2009, Proceedings (pp. 112-116). Los Alamitos: IEEE Computer Soc.