Joana Lino

Joana Lino

Monday, 27 July 2020 14:44

Ibrahem Kandel

ibrahem-kandel

Identification

Ibrahem Kandel, Ph.D. Student of Information Management
with a specialization in Data Science

Contacts

E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Biography

Ibrahem Kandel is a Ph.D. Student of Information Management with a specialization in data science. He has a master's degree from Nova IMS in statistics and information management and a bachelor degree in biomedical engineering from Cairo, Egypt. He possesses vast experience in data science consulting in the financial industry and the medical field. His current research interests include artificial intelligence (in particular, convolutional neural networks) and the application of deep learning techniques to solve complex real-life problems, especially in the fields of computer vision.

Publications

Book Section

  • Transfer Learning with Convolutional Neural Networks for Diabetic Retinopathy Image Classification. A Review Kandel, I.; Castelli, M. Transfer Learning with Convolutional Neural Networks for Diabetic Retinopathy Image Classification. A Review. Appl. Sci. 2020, 10, 2021. https://doi.org/10.3390/app10062021
  • How Deeply to Fine-Tune a Convolutional Neural Network: A Case Study Using a Histopathology Dataset Kandel, I.; Castelli, M. How Deeply to Fine-Tune a Convolutional Neural Network: A Case Study Using a Histopathology Dataset. Appl. Sci. 2020, 10, 3359.https://doi.org/10.3390/app10103359
  • A Novel Architecture to Classify Histopathology Images Using Convolutional Neural Networks Kandel, I.; Castelli, M. A Novel Architecture to Classify Histopathology Images Using Convolutional Neural Networks. Appl. Sci. 2020, 10, 2929. https://doi.org/10.3390/app10082929
  • The effect of batch size on the generalizability of the convolutional neural networks on a histopathology dataset I. Kandel and M. Castelli, “The effect of batch size on the generalizability of the convolutional neural networks on a histopathology dataset,” ICT Express, 2020. https://doi.org/10.1016/j.icte.2020.04.010
Monday, 20 January 2020 12:13

Luís Madureira

luis-madureira

Identification

Luís Alexandre Abrantes Madureira, Invited Lecturer
Licenciado em Economia (NOVA SBE)

Contacts

E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Biography

Luis Madureira is a PhD Student of Information Management - Information and Decision Systems - and a visiting professor at NOVA IMS. He is a lecturer in several courses at the undergraduate and masters degree level internationally on Competitive Intelligence (CI), Strategy, Marketing and Innovation. Graduated from NOVA SBE in Economics and is CIP-I & II / Master of Competitive Intelligence by the Academy of Competitive Intelligence. Awarded the CI Fellowship, the highest recognition in CI by the Council of CI Fellows, he chairs the SCIP Portugal Chapter. As Managing Partner of ÜBERBRANDS, a strategic consultancy boutique, he supports organisations successfully navigate their competitive environment. Previously the Global Competitive Intelligence Practice Lead for Ogilvy Consulting, he possesses a vast experience in Consulting and FMCG - Diageo, Coca-Cola, PepsiCo, Red Bull, United Coffee, and Heineken.

Publications

Book Section

  • Gonçalves, A., & Madureira, L. (2017). Luis Madureira: SMINT Author & Design Thinker on Competitive Intelligence, Strategy, Innovation & Growth. In Apress. Social Media Analytics Strategy—Using Data to Optimize Business Performance (1st ed., pp. 47–52). Retrieved from www.springer.com/br/book/9781484231012
  • Zeferino, A., & Madureira, L. (2016). Digital Marketing Analytics: Optimize The Value Of Your Digital Strategy - SMINT Case Study. In Digital Marketing Analytics (1st ed., pp. 87–88). Retrieved from http://www.webanalytics.pt/
  • Madureira, L. (2014). Market and Competitor Analysis—Real Exercise. In William J. Lahneman & Rubén Arcos (Eds.), The Art of Intelligence: Simulations, Exercises, and Games (1st ed., pp. 125–142). Retrieved from https://rowman.com/ISBN/9781442228979/The-Art-of-Intelligence-Simulations-Exercises-and-Games
  • Hedin, H., Hirvensalo, I., Vaarnas, M., & Madureira, L. (2011). Case: MI Tools Selection as Sociedade Central Cervejas (SCC)—Group Heineken. In The Handbook of Market Intelligence: Understand, Compete and Grow in Global Markets (1st ed., pp. 90–91). Retrieved from https://doi.org/10.1002/9781119208082.ch7
  • Moutinho, L., Dionísio, P., Rodrigues, J. V., Pereira, H. G., & Madureira, L. (2012). Sense & Respond Models | Human Sensing—Example 2: Market Intelligence Strategy. In Marketing FutureCast Lab, ISCTE-IUL - Marketing Trends—Antecipate The Future To Inspire The Present (1st ed., pp. 81–81). Retrieved from www.deplano.pt

Conference Proceeding

  • Madureira, L., Castelli, M., & Popovic, A. (2019). Design thinking: the new mindset for competitive intelligence? Impacts on the competitive intelligence model. In Proceedings of the 19th Portuguese Association of Information Systems Conference: Digital Disruption: Living between Data Science, IoT and ... People, 34. Portugal: Associação Portuguesa de Sistemas de Informação. (http://capsi2019.apsi.pt/index.php/en/ ).
  • Sandler Passos, D., & Madureira, L. (2015, November 24). Need To Share—A nova tendência, seus mecanismos e riscos. 1, 1–8. Retrieved from http://www.convibra.com.br/upload/paper/2015/29/2015_29_11213.pdf

Other Publications (Trade Publications)

  • Madureira, L. (2019). Design Thinking: The New Mindset for CI? Competitive Intelligence Magazine, 23(1), 6–15. SCIP.org.
  • Madureira, L. (2017). SMINT - Why CI Needs A New Approach. Competitive Intelligence Magazine, 20(1), 12–16. SCIP.org.
  • Madureira, L. (2013). Social Market Intelligence: An Introduction to “Future Ready CI”. Scip.Insight, 5(1), 1.
  • Madureira, L. (2012). #SCIPEU12: Future Ready – Have You Tried Social Market Intelligence (SMINT)? Scip.Insight, 4(2), 1.

 

 

Thursday, 26 December 2019 11:58

Bruno Damásio

bruno-damasio

Identification

Bruno Miguel Pinto Damásio, Professor Auxiliar Convidado
Doutoramento em Matemática Aplicada Universidade de Lisboa

Contacts

E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Biography

Bruno Damásio holds a PhD Applied Mathematics, a Master in Econometrics and a Degree in Economics by the University of Lisbon. His research interests are nonlinear econometrics, multivariate Markov chains, stochastic processes, financial econometrics, nonlinear time-series, applied economics, and the statistical packages R and Stata. His work has been published in several journals, such as Physica A: Statistical Mechanics and its Applications, Statistics and Probability Letters, Applied Economics Letters, Empirica. Additionally, he is a lecturer of statistics and econometrics courses at NOVA IMS (Information Management School, Nova University of Lisbon) and ISEG (Lisbon School of Economics and Management, University of Lisbon). He is serving as statistical consultant and trainer for numerous private and public organisations including OECD, European Comission, European Court of Auditors, Ministries, Central Banks, Bureau of Statistics, Bureau of Economic Analysis, among others.

Publications

Journal Article

  • Damásio, B., & Mendonça, S. (2019). Modelling insurgent-incumbent dynamics: Vector autoregressions, multivariate Markov chains, and the nature of technological competition. Applied Economics Letters, 26(10), 843-849. [Advanced online publication 30 july 2018]. https://doi.org/10.1080/13504851.2018.1502863. DOI: 10.1080/13504851.2018.1502863
  • Martins, D., & Damásio, B. (2019). One Troika fits all?: job crash, pro-market structural reform and austerity-driven therapy in Portugal. Empirica. [Advanced online publication on 11 february 2019]. Doi: https://doi.org/10.1007/s10663-019-09433-w
  • Damásio, B.; Louçã, F. & Nicolau, J. (2018). The changing economic regimes and expected time to recover of the peripheral countries under the euro: A nonparametric approach. Physica A: Statistical Mechanics and its Applications, 507, 524-533. doi: https://doi.org/10.1016/j.physa.2018.05.089
  • Barros, C., Damásio, B. and Faria, J. (2014). Reverse FDI in Europe: An Analysis of Angola's FDI in Portugal. African Development Review, 26 (1), 160-171. https://doi.org/10.1111/1467-8268.12072
  • Damásio, B. and Nicolau, J. (2014). Combining a Regression Model with a Multivariate Markov Chain in a Forecasting Problem.Statistics & Probability Letters, 90 (july), 108-113. https://doi.org/10.1016/j.spl.2014.03.026

 

 

Wednesday, 18 December 2019 10:49

Mijail Naranjo

Mijail-Naranjo

Identification

Mijail Naranjo, Invited Assistant Professor,
PhD degree (2018) in Information Management from a consortium of three Universities: Universidade Nova de Lisboa (UNL), University of Münster (WWU), and Universitat Jaume I (UJI)

Contacts

E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Biography

Mijail Naranjo-Zolotov is an Invited Assistant Professor at NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Portugal. He holds a PhD degree (2018) in Information Management from a consortium of three Universities: Universidade Nova de Lisboa (UNL), University of Münster (WWU), and Universitat Jaume I (UJI). He holds a Master degree in Geospatial Technologies obtained in 2014 from the NOVA IMS. His research interests include e-participation, e-government, technology adoption and diffusion, and Geographic Information Systems. He has published articles in several academic journals and conferences, including the Computers in Human Behavior, Information Technology & People, Future Generation Computer Systems, and Government Information Quarterly, among others.

Publications

Journal Article

  • Acedo, A., Oliveira, T., Naranjo-Zolotov, M., & Painho, M. (2019). Place and city: toward a geography of engagement. Heliyon, 5(8). https://doi.org/10.1016/j.heliyon.2019.e02261
  • Martins, J., Branco, F., Gonçalves, R., Au-Yong-Oliveira, M., Oliveira, T., Naranjo-Zolotov, M., & Cruz-Jesus, F. (2018). Assessing the success behind the use of education management information systems in higher education. Telematics and Informatics. https://doi.org/10.1016/j.tele.2018.10.001
  • Naranjo-Zolotov, M., Oliveira, T., Cruz-Jesus, F., Martins, J., Gonçalves, R., Branco, F., & Xavier, N. (2019). Examining social capital and individual motivators to explain the adoption of online citizen participation. Future Generation Computer Systems, 92. https://doi.org/10.1016/j.future.2018.09.044
  • Naranjo-Zolotov, Mijail, Oliveira, T., & Casteleyn, S. (2018). Citizens’ intention to use and recommend e-participation: Drawing upon UTAUT and citizen empowerment. Information Technology & People. https://doi.org/10.1108/ITP-08-2017-0257
  • Naranjo-Zolotov, Mijail, Oliveira, T., Casteleyn, S., & Irani, Z. (2019). Continuous usage of e-participation: The role of the sense of virtual community. Government Information Quarterly, 36(3), 536–545. https://doi.org/10.1016/J.GIQ.2019.05.009
  • Naranjo Zolotov, M., Oliveira, T., & Casteleyn, S. (2018). E-participation adoption models research in the last 17 years: A weight and meta-analytical review. Computers in Human Behavior, 81, 350–365. https://doi.org/10.1016/j.chb.2017.12.031

Conferences

  • Zolotov, M. N., Oliveira, T., & Casteleyn, S. (2018). Continued intention to use online participatory budgeting: The effect of empowerment and habit. Proceedings of the 11th International Conference on Theory and Practice of Electronic Governance - ICEGOV ’18, 209–216. https://doi.org/10.1145/3209415.3209461
  • Cruz-Jesus, F., Oliveira, T., & Naranjo, M. (2018). Understanding the Adoption of Business Analytics and Intelligence. In World Conference on Information Systems and Technologies (pp. 1094–1103). Springer, Cham. https://doi.org/10.1007/978-3-319-77703-0_106
  • Zolotov, M. N., Oliveira, T., Cruz-Jesus, F., & Martins, J. (2018). Satisfaction with e-participation: A model from the citizen’s perspective, expectations, and affective ties to the place. In Á. Rocha, H. Adeli, L. P. Reis, & S. Costanzo (Eds.), Trends and Advances in Information Systems and Technologies. WorldCIST’18 2018. (pp. 1049–1059). Cham: Springer International Publishing.
  • Nunes, S., Martins, J., Branco, F., & Zolotov, M. (2018). An online focus group approach to e-Government acceptance and use. Advances in Intelligent Systems and Computing (Vol. 745). https://doi.org/10.1007/978-3-319-77703-0_44

 

 

Wednesday, 18 December 2019 10:45

Mijail Naranjo

This email address is being protected from spambots. You need JavaScript enabled to view it.
Integrated Researcher
(Resident)

Friday, 18 October 2019 08:39

CAPSI 2019

More information, click here.

Thursday, 17 October 2019 10:30

Public Sessions: CAPSI 2019

More information, click here.

venkatesh-evento

More information, click here.

Tuesday, 14 May 2019 15:57

Hugo Costa

This email address is being protected from spambots. You need JavaScript enabled to view it.
Integrated Researcher (Non Resident)

Tuesday, 14 May 2019 15:31

Hugo Costa

Euclides Batalha

Identification

Hugo Costa, Invited Lecturer,
Ph.D in Geographical Information Science (University of Nottingham)

Contacts

E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Biography

Hugo Costa is Invited Lecturer at NOVA Information Management School (NOVA IMS) and works at Direção-Geral do Território (DGT). He holds a Ph.D. degree in Geographical Information Science (University of Nottingham, UK). His main research area is remote sensing, in particular image classification for land cover mapping, along with ecological modelling. He is the first author of >10 peer-reviewed publications, including articles in scientific journals, international conference proceedings, and one book section.

Publications

Journal Article

  • Berhane, T., Costa, H., Lane, C., Anenkhonov, O., Chepinoga, V., Autrey, B., 2019. The influence of region of interest heterogeneity on classification accuracy in wetland Systems. Remote Sensing 11(5), 551.
  • Costa, H., Almeida, D., Vala, F., Marcelino, F., Caetano, M., 2018. Land cover mapping from remotely sensed and auxiliary data for harmonized official statistics. ISPRS International Journal of Geo-Information 7(4), 157.
  • Costa, H., Foody, G.M., Boyd, D.S., 2018. Supervised methods of image segmentation accuracy assessment in land cover mapping. Remote Sensing of Environment 205, 338-351.
  • Costa, H., Foody, G.M., Boyd, D.S., 2017. Using mixed objects in the training of object-based image classifications. Remote Sensing of Environment 190, 188-197.
  • Costa, H., Foody, G.M., Jiménez, S., Silva, L., 2015. Impacts of species mis-identification on species distribution modelling with presence-only data. ISPRS International Journal of Geo-Information 4(4), 2496-2518.
  • Costa, H., Ponte, N.B., Azevedo, E.B., Gil, A., 2015. Fuzzy set theory for predicting the potential distribution and cost-effective monitoring of invasive species. Ecological Modelling 316, 122-132.
  • Costa, H., Foody, G.M., Boyd, D.S., 2015. Integrating user needs on misclassification error sensitivity into image segmentation quality assessment. Photogrammetric Engineering & Remote Sensing 81(6), 451-459.
  • Martins, J., Costa, H., Moreira, O., Azevedo, E.B., Moura, M. and Silva, L., 2015. Distribution and conservation status of the endangered Azorean tree Picconia azorica. International Journal of Biological Sciences and Applications 2(1), 1–9.
  • Moreira, O., Costa, H., Martins, J., Azevedo, E.B., Moura, M., Silva, L., 2014. Present and potential distribution of the endangered tree Prunus lusitanica subsp. azorica: Implications in conservation. International Journal of Biological Sciences and Applications 1(5), 190–200.
  • Costa, H., Carrão, H., Bação, F., Caetano, M., 2014. Combining per-pixel and object based classifications for mapping land cover over large areas. International Journal of Remote Sensing 35(2), 738-753.
  • Costa, H., Medeiro, V., Azevedo, E., Silva, L., 2013. Evaluating ecological-niche factor analysis as a modelling tool for environmental weed management in island systems. Weed Research 53(3), 221-230.
  • Costa, H., Aranda, S.C., Lourenço, P., Medeiro, V., Azevedo, E., Silva, L., 2012. Predicting successful replacement of forest invaders by native species using species distribution models: The case of Pittosporum undulatum and Morella faya in the Azores. Forest Ecology and Management 279, 90-96.

Book Section

  • Silva, L.D., Costa, H., Azevedo, E..B, Medeiros, V., Alves, M., Elias, E.B., Silva, L., 2017. “Modelling native and invasive woody species: a comparison of ENFA and MaxEnt applied to the Azorean forest” in A. Pinto and D. Zilberman (Eds.), Modeling, Dynamics, Optimization and Bioeconomics II. Springer Proceedings in Mathematics & Statistics. Springer.
  • Costa, H., Bettencourt, M.J., Silva, C.M.N., Teodósio, J., Gil, A., Silva, L., 2013. “Invasive alien plants in the Azorean protected areas: Invasion status and mitigation actions”, in L.C. Foxcroft, D.M. Richardson, P. Pyšek and P. Genovesi (eds.), Alien Plant Invasions in Protected Areas: Patterns, Problems and Challenges. Dordrecht : Springer, 375-397.

Conference Proceeding

  • Maianti, P, Artés Vivancos, T., Guillaume, B., Miranda, A. I., Monteiro, A., Gama, C., Houston Durrant, T., Libertà, G., Boca, R., Branco, A., de Rigo, D., Ferrari, D., Lana, F., Costa, H., San-Miguel-Ayanz, J. (2019) Integration of the emissions and smoke dispersion models in the European Forest Fire Information System. In Advances in forest fire research 2018, Viegas, D. X. (ed.), 10-16 Novembro, 2019, Coimbra, Portugal (Coimbra: Imprensa da Universidade de Coimbra), pp 1043-1052.
  • Costa, H., Foody, G. M., Boyd, D. S. (2016). Using pure and mixed objects in the training of object-based image classification. GEOBIA 2016 : Solutions and Synergie, 14-16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC).
  • Costa, H., Foody, G. M., Boyd, D. S. (2014). Integrating thematic information into the assessment of image segmentation analyses for Object-Based land cover classification. South-Eastern European Journal of Earth Observation and Geomatics 3(2S), pp. 155–159.
  • Costa, H., Carrão, H., Bação, F., Caetano, M., 2009, Land cover classification in Portugal with multitemporal AWiFS images: a comparative study. In Remote Sensing for a Changing Europe-Proceedings of the 28th Symposium of the European Association of Remote Sensing Laboratories, D. Maktav (Ed.), 2-5 Junho 2008, Istambul, Turquia (Amesterdão: IOS Press), pp. 356-363.
  • Costa, H., Caetano, M., 2009, Classificação de imagens AWiFS com uma abordagem combinada pixel/objecto. In Anais do 14º Simpósio Brasileiro de Sensoriamento Remoto, J. Epiphanio e L. Galvão (Eds.), 25-30 Abril 2009, Natal, Brasil (São José dos Campos: Instituto Nacional de Pesquisas Espaciais), pp. 7781-7788.
  • Costa, H., Araújo, A., Carrão, H., Caetano, M., 2008, Influência das características técnicas das imagens de satélite na produção de cartografia de ocupação do solo: estudo baseado em imagens MERIS e AWiFS. In Actas do X Encontro de Utilizadores de Informação Geográfica, J. Rocha (Ed.), 14-16 Maio 2008, Oeiras, Portugal (Guimarães: Universidade do Minho), pp. 325-341.

 

 

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