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Tiago J. Rato concluded his Ph.D. in Chemical Engineering by the University of Coimbra in June of 2014. Afterwards, he was a Post-Doctoral Researcher at Katholieke Universiteit Leuven (2015). Since 2016 he has been a Researcher at the Chemical Engineering Department at FCTUC. His topics of interest focus on the development and implementation of data-driven methodologies, machine learning, applied statistics, model-based engineering.
Identification

Personal identification

Full name
Tiago Rato

Citation names

  • Rato, Tiago J.

Author identifiers

Ciência ID
C817-096B-D892
ORCID iD
0000-0002-5247-6583
Researcher Id
I-4991-2014
Scopus Author Id
36761560800

Email addresses

  • trato@eq.uc.pt (Professional)

Addresses

  • Universidade de Coimbra, Faculdade de Ciências e Tecnologia, Departamento de Engenharia Química. Departamento de Engenharia Química, 3030-790, Coimbra, Portugal (Professional)

Knowledge fields

  • Engineering and Technology - Chemical Engineering - Chemical Process Engineering

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)
Education
Degree Classification
2009 - 2014/06/30
Concluded
 Doutoramento em Engenharia Química (Pré-Bolonha) (Doutoramento)
Universidade de Coimbra, Portugal
"Development of integrated data-driven frameworks for the monitoring, analysis and control of complex systems" (THESIS/DISSERTATION)
 Approved with praise and distinction by unanimity
2004 - 2009/07/16
Concluded
 Mestrado Integrado em Engenharia Química (Mestrado)
Universidade de Coimbra, Portugal
"Supervisão de Sistemas de Controlo" (THESIS/DISSERTATION)
 16
Affiliation

Science

Category
Host institution 		Employer
2024/04/01 - Current Invited Auxiliary Researcher (Research) Universidade de Coimbra, Portugal
2021/03 - 2024/03/31 Researcher (Research) Instituto do Ambiente Tecnologia e Vida, Portugal
2016/06 - 2021/02 Researcher (Research) Universidade de Coimbra, Portugal
2015/02 - 2015/12 Researcher (Research) Katholieke Universiteit Leuven, Belgium
2009/09 - 2014/06 Researcher (Research) Universidade de Coimbra, Portugal
2014/01 - 2014/03 Researcher (Research) Katholieke Universiteit Leuven, Belgium
Projects

Grant

Designation Funders
2016/01 - 2019/12 Optimal Fusion of Multiresolution Information for Soft Sensor Development, Process Monitoring and Model-Based Estimation
grant.Provided by PTCRIS: 139948
 Fundação para a Ciência e a Tecnologia
2010/06 - 2013/11 Development of an integrated framework for monitoring and control of complex industrial and biologic systems using advanced partial-correlation and information-theoretic approaches
108374
Provided by PTCRIS: 108374
 Fundação para a Ciência e a Tecnologia, I.P.
Outputs

Publications

Book chapter
  1. Rúben Gariso; Tiago J. Rato; Margarida J. Quina; Licínio Ferreira; Marco S. Reis. "Predicting the coagulation potential of waste lubricant oil (WLO) using multiblock machine learning of NIR and MIR spectroscopy". 2024.
    10.1016/b978-0-443-28824-1.50308-2
  2. Reis, M.S.; Strelet, E.; Sansana, J.; Quina, M.J.; Gando-Ferreira, L.M.; Rato, T.J.. "Development of a Centralized Classifier for Decentralized Decision Making". 1891-1896. 2023.
    10.1016/B978-0-443-15274-0.50300-0
  3. Paredes, R.; Rato, T.J.; Santos, L.O.; Reis, M.S.. "Hierarchical Statistical Process Monitoring based on a Functional Decomposition of the Causal Network". In Computer Aided Chemical Engineering, 1417-1422. 2022.
    10.1016/B978-0-323-95879-0.50237-X
  4. Reis, M.S.; Rendall, R.; Rato, T.J.; Martins, C.; Delgado, P.. "The truncated Q statistic for Statistical Process Monitoring of High-Dimensional Systems". In Computer Aided Chemical Engineering, 1381-1386. 2022.
    10.1016/B978-0-323-95879-0.50231-9
  5. Reis, M.S.; Rato, T.J.. "An Advanced Data-Centric Multi-Granularity Platform for Industrial Data Analysis". 1225-1230. 2019.
    10.1016/B978-0-12-818634-3.50205-8
  6. Rato, T.J.; Reis, M.S.; Tiago J. Rato; Marco S. Reis. "Improved Fault Diagnosis in Online Process Monitoring of Complex Networked Processes: a Data-Driven Approach". In Computer Aided Chemical Engineering, 1681-1686. 2017.
    Published • 10.1016/B978-0-444-63965-3.50282-8
  7. Rato, Tiago J.; Reis, Marco S.. "Sensitivity Enhancing Transformations for Large-Scale Process Monitoring". In 24th European Symposium on Computer Aided Process Engineering, 643-648. Oxford: Elsevier, 2014.
    Published • 10.1016/B978-0-444-63456-6.50108-3
  8. Rato, Tiago J.; Reis, Marco S.. "A new data driven index for control performance monitoring". In Computer Aided Chemical Engineering, 852-856. Oxford: Elsevier, 2012.
    Published • 10.1016/B978-0-444-59520-1.50029-4
  9. Rato, Tiago J.; Reis, Marco S.. "Statistical Process Control of Multivariate Systems with Autocorrelation". In Computer Aided Chemical Engineering, 497-501. Oxford: Elsevier, 2011.
    Published • 10.1016/B978-0-444-53711-9.50100-0
Conference paper
  1. Reis, M.S.; Rato, T.J.. "Platforms for automatic PAT soft sensor development and analysis". 2020.
    10.1016/j.ifacol.2020.12.541
  2. Rato, T.; Rendall, R.; Gomes, V.; Chin, S.-T.; Chiang, L.H.; Saraiva, P.; Reis, M.. "An extensive comparison study of batch process monitoring approaches". 2015.
  3. Reis, M.; Rato, T.. "Multivariate SPC of dynamic processes using integrated dynamic principal components analysis and missing data methods (DPCA-MD)". 2012.
Conference poster
  1. Rúben Gariso; Rato, Tiago J.; Margarida J. Quina; Licínio Ferreira; Marco S. Reis. "Predicting the coagulation potential of waste lubricant oil using multiblock machine learning of NIR and MIR spectroscopy". Paper presented in ESCAPE 34 – 34th European Symposium on Computer Aided Process Engineering, 2024.
  2. Rato, Tiago J.; Marco Reis. "Advanced Multi-Granularity Analytics for Industry 4.0". Paper presented in CHEMPOR 2018 - 13th International Chemical and Biological Engineering Conference, 2018.
  3. Rato, Tiago J.; Marco Reis. "Improved Fault Diagnosis in Online Process Monitoring of Complex Networked Processes: a Data-Driven Approach". Paper presented in ESCAPE 27 – 27th European Symposium on Computer Aided Process Engineering, 2017.
  4. Rato, Tiago J.; Marco Reis. "Large-scale statistical process control: should we use partial or marginal correlations?". Paper presented in 2013 AIChE Annual Meeting, 2013.
  5. Rato, Tiago J.; Marco Reis. "On the use of partial versus marginal correlations in SPC". Paper presented in ENBIS 12 - European Network for Business and Industrial Statistics, 2012.
  6. Rato, Tiago J.; Marco Reis. "Multivariate SPC of dynamic processes using integrated dynamic principal components analysis and missing data methods". Paper presented in 2012 AIChE Annual Meeting, 2012.
  7. Rato, Tiago J.; Marco Reis. "A new data driven index for control performance monitoring". Paper presented in ESCAPE 22 – 22nd European Symposium on Computer Aided Process Engineering, 2012.
  8. Rato, Tiago J.; M.S. Reis. "Fault detection in the Tennessee Eastman process using integrated dynamic principal components analysis and missing data methods". Paper presented in CHEMPOR 2011 - 11th International Chemical and Biological Engineering Conference, 2011.
  9. Rato, Tiago J.; Marco Reis. "Multivariate SPC of dynamic processes: application of DPCA-MD to the Tennessee Eastman process". Paper presented in ENBIS 11 - European Network for Business and Industrial Statistics, 2011.
  10. Rato, Tiago J.; Marco Reis. "Statistical process control of multivariate systems with autocorrelation". Paper presented in ESCAPE 21 - 21st European Symposium on Computer Aided Process Engineering, 2011.
Journal article
  1. Reis, M.S.; Rato, T.J.. "Hybrid modelling through latent differential-regression analysis (LDRA) for predicting long-term equipment degradation in the chemical process industry". Chemical Engineering Science 278 (2023): http://www.scopus.com/inward/record.url?eid=2-s2.0-85160261587&partnerID=MN8TOARS.
    10.1016/j.ces.2023.118902
  2. Rato, T.J.; Reis, M.S.. "Real-time risk assessment and surveillance for early prediction of unplanned shutdown events". Chemical Engineering Science 282 (2023): http://www.scopus.com/inward/record.url?eid=2-s2.0-85173912099&partnerID=MN8TOARS.
    10.1016/j.ces.2023.119364
  3. Paredes, R.; Rato, T.J.; Reis, M.S.. "Causal network inference and functional decomposition for decentralized statistical process monitoring: Detection and diagnosis". Chemical Engineering Science 267 (2023): http://www.scopus.com/inward/record.url?eid=2-s2.0-85143786333&partnerID=MN8TOARS.
    10.1016/j.ces.2022.118338
  4. Reis, M.S.; Strelet, E.; Sansana, J.; Quina, M.J.; Gando-Ferreira, L.M.; Rato, T.J.. "A Federated Classification Approach of Waste Lubricant Oils in Geographically Distributed Laboratories". Industrial and Engineering Chemistry Research (2022): http://www.scopus.com/inward/record.url?eid=2-s2.0-85142697761&partnerID=MN8TOARS.
    10.1021/acs.iecr.2c02293
  5. Fernandes, N.C.P.; Rato, T.J.; Reis, M.S.. "Modeling in the observable or latent space? A comparison of dynamic latent variable based monitoring methods for sensor fault detection". Chemometrics and Intelligent Laboratory Systems 231 (2022): http://www.scopus.com/inward/record.url?eid=2-s2.0-85140890709&partnerID=MN8TOARS.
    10.1016/j.chemolab.2022.104684
  6. de Souza, D.C.M.; Cabrita, L.; Galinha, C.F.; Rato, T.J.; Reis, M.S.. "A Spectral AutoML approach for industrial soft sensor development: Validation in an oil refinery plant". Computers and Chemical Engineering 150 (2021): http://www.scopus.com/inward/record.url?eid=2-s2.0-85104789838&partnerID=MN8TOARS.
    10.1016/j.compchemeng.2021.107324
  7. Reis, M.S.; Rendall, R.; Rato, T.J.; Martins, C.; Delgado, P.. "Improving the sensitivity of statistical process monitoring of manifolds embedded in high-dimensional spaces: The truncated-Q statistic". Chemometrics and Intelligent Laboratory Systems 215 (2021): http://www.scopus.com/inward/record.url?eid=2-s2.0-85121283626&partnerID=MN8TOARS.
    10.1016/j.chemolab.2021.104369
  8. Rato, Tiago J.; Neves, Diogo M.G.; Antunes, Anabela; Reis, Marco S.. "A systematic PAT Soft Sensor screening and development methodology applied to the prediction of free fatty acids in industrial biodiesel production". Fuel 282 (2020): 118800. http://dx.doi.org/10.1016/j.fuel.2020.118800.
    10.1016/j.fuel.2020.118800
  9. Tiago J. Rato; Pedro Delgado; Cristina Martins; Marco S. Reis. "First Principles Statistical Process Monitoring of High-Dimensional Industrial Microelectronics Assembly Processes". Processes (2020): https://www.mdpi.com/2227-9717/8/11/1520.
    10.3390/pr8111520
  10. Rato, Tiago J.; Reis, Marco S.. "An integrated multiresolution framework for quality prediction and process monitoring in batch processes". Journal of Manufacturing Systems 57 (2020): 198-216. http://dx.doi.org/10.1016/j.jmsy.2020.09.007.
    10.1016/j.jmsy.2020.09.007
  11. Rato, Tiago J.; Reis, Marco S.. "Multiresolution interval partial least squares: A framework for waveband selection and resolution optimization". Chemometrics and Intelligent Laboratory Systems 186 (2019): 41-54. http://dx.doi.org/10.1016/j.chemolab.2019.02.002.
    10.1016/j.chemolab.2019.02.002
  12. Santos, C.P.; Rato, Tiago J.; Reis, M.S.. "Design of Experiments: A comparison study from the non-expert user's perspective". Journal of Chemometrics (2019): http://www.scopus.com/inward/record.url?eid=2-s2.0-85054919301&partnerID=MN8TOARS.
    10.1002/cem.3087
  13. Rato, T.J.; Reis, M.S.. "SS-DAC: A systematic framework for selecting the best modeling approach and pre-processing for spectroscopic data". Computers and Chemical Engineering 128 (2019): 437-449. http://www.scopus.com/inward/record.url?eid=2-s2.0-85068368897&partnerID=MN8TOARS.
    10.1016/j.compchemeng.2019.05.036
  14. Rato, T.J.; Reis, M.S.. "Optimal fusion of industrial data streams with different granularities". Computers and Chemical Engineering 130 (2019): http://www.scopus.com/inward/record.url?eid=2-s2.0-85071842652&partnerID=MN8TOARS.
    10.1016/j.compchemeng.2019.106564
  15. Reis, M.S.; Gins, G.; Rato, T.J.. "Incorporation of process-specific structure in statistical process monitoring: A review". Journal of Quality Technology 51 4 (2019): 407-421. http://www.scopus.com/inward/record.url?eid=2-s2.0-85068188652&partnerID=MN8TOARS.
    10.1080/00224065.2019.1569954
  16. Rato, T.J.; Reis, M.S.. "Building Optimal Multiresolution Soft Sensors for Continuous Processes". Industrial and Engineering Chemistry Research 57 30 (2018): 9750-9765. http://www.scopus.com/inward/record.url?eid=2-s2.0-85051075585&partnerID=MN8TOARS.
    10.1021/acs.iecr.7b04623
  17. Rato, T.J.; Rendall, R.; Gomes, V.; Saraiva, P.M.; Reis, M.S.. "A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part II - Assessing Detection Speed". Industrial and Engineering Chemistry Research 57 15 (2018): 5338-5350. http://www.scopus.com/inward/record.url?eid=2-s2.0-85045645685&partnerID=MN8TOARS.
    10.1021/acs.iecr.7b04911
  18. Reis, M.S.; Rato, T.J.. "Multiresolution Analytics for Large Scale Industrial Processes". IFAC-PapersOnLine 51 18 (2018): 464-469. http://www.scopus.com/inward/record.url?eid=2-s2.0-85054380303&partnerID=MN8TOARS.
    10.1016/j.ifacol.2018.09.381
  19. Rato, T.J.; Reis, M.S.. "Optimal selection of time resolution for batch data analysis. Part I: Predictive modeling". AIChE Journal 64 11 (2018): 3923-3933. http://www.scopus.com/inward/record.url?eid=2-s2.0-85053255584&partnerID=MN8TOARS.
    10.1002/aic.16361
  20. Rato, Tiago J.; Reis, Marco S.. "Multiresolution Soft Sensors: A New Class of Model Structures for Handling Multiresolution Data". Industrial & Engineering Chemistry Research 56 13 (2017): 3640-3654.
    Published • 10.1021/acs.iecr.6b04349
  21. Rato, Tiago J.; Reis, Marco S.. "Markovian and Non-Markovian sensitivity enhancing transformations for process monitoring". Chemical Engineering Science 163 - (2017): 223-233.
    Published • 10.1016/j.ces.2017.01.047
  22. Tiago J. Rato; Jakey Blue; Jacques Pinaton; Marco S. Reis; Rato, Tiago J.; Blue, Jakey; Pinaton, Jacques; Reis, Marco S.. "Translation-Invariant Multiscale Energy-Based PCA for Monitoring Batch Processes in Semiconductor Manufacturing". IEEE Transactions on Automation Science and Engineering 14 2 (2017): 1-11. https://doi.org/10.1109%2Ftase.2016.2545744.
    Published • 10.1109/tase.2016.2545744
  23. De Ketelaere, Bart; Rato, Tiago; Schmitt, Eric; Hubert, Mia. "Statistical process monitoring of time-dependent data". Quality Engineering 28 1 (2016): 127-142.
    Published • 10.1080/08982112.2015.1100474
  24. De Ketelaere, Bart; Schmitt, Eric; Rato, Tiago; Hubert, Mia. "Rejoinder". Quality Engineering 28 1 (2016): 151-154.
    Published • 10.1080/08982112.2015.1100478
  25. Rato, Tiago; Reis, Marco; Schmitt, Eric; Hubert, Mia; De Ketelaere, Bart. "A systematic comparison of PCA-based Statistical Process Monitoring methods for high-dimensional, time-dependent Processes". AIChE Journal 62 5 (2016): 1478-1493.
    Published • 10.1002/aic.15062
  26. Rato, Tiago J.; Rendall, Ricardo; Gomes, Veronique; Chin, Swee-Teng; Chiang, Leo H.; Saraiva, Pedro M.; Reis, Marco S.. "A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part I - Assessing Detection Strength". Industrial & Engineering Chemistry Research 55 18 (2016): 5342-5358.
    Published • 10.1021/acs.iecr.5b04851
  27. Schmitt, Eric; Rato, Tiago; De Ketelaere, Bart; Reis, Marco; Hubert, Mia. "Parameter selection guidelines for adaptive PCA-based control charts". Journal of Chemometrics 30 4 (2016): 163-176.
    Published • 10.1002/cem.2783
  28. Rato, Tiago J.; Reis, Marco S.. "On-line process monitoring using local measures of association: Part I - Detection performance". Chemometrics and Intelligent Laboratory Systems 142 0 (2015): 255-264.
    Published • 10.1016/j.chemolab.2015.02.011
  29. Rato, Tiago J.; Reis, Marco S.. "On-line process monitoring using local measures of association. Part II: Design issues and fault diagnosis". Chemometrics and Intelligent Laboratory Systems 142 0 (2015): 265-275.
    Published • 10.1016/j.chemolab.2015.02.007
  30. Rato, Tiago J.; Reis, Marco S.. "Multiscale and megavariate monitoring of the process networked structure: M2NET". Journal of Chemometrics na (2015): n/a-n/a.
    Published • 10.1002/cem.2703
  31. Rato, Tiago J.; Reis, Marco S.. "Sensitivity enhancing transformations for monitoring the process correlation structure". Journal of Process Control 24 6 (2014): 905-915.
    Published • 10.1016/j.jprocont.2014.04.006
  32. Rato, Tiago J.; Reis, Marco S.. "Non-causal data-driven monitoring of the process correlation structure: A comparison study with new methods". Computers & Chemical Engineering 71 0 (2014): 307-322.
    Published • 10.1016/j.compchemeng.2014.09.003
  33. Rato, Tiago J.; Reis, Marco S.. "Defining the structure of DPCA models and its impact on process monitoring and prediction activities". Chemometrics and Intelligent Laboratory Systems 125 15 (2013): 74-86.
    Published • 10.1016/j.chemolab.2013.03.009
  34. Rato, Tiago J.; Reis, Marco S.. "Fault detection in the Tennessee Eastman benchmark process using dynamic principal components analysis based on decorrelated residuals (DPCA-DR)". Chemometrics and Intelligent Laboratory Systems 125 15 (2013): 101-108.
    Published • 10.1016/j.chemolab.2013.04.002
  35. Rato, Tiago J.; Reis, Marco S.. "Advantage of Using Decorrelated Residuals in Dynamic Principal Component Analysis for Monitoring Large-Scale Systems". Industrial & Engineering Chemistry Research 52 38 (2013): 13685-13698.
    Published • 10.1021/ie3035306
  36. Rato, Tiago J.; Reis, Marco S.. "Statistical monitoring of control loops performance: an improved historical-data benchmark index". Quality and Reliability Engineering International 26 8 (2010): 831-844.
    Published • 10.1002/qre.1139
Thesis / Dissertation
  1. Rato, Tiago J.. "Development of integrated data-driven frameworks for the monitoring, analysis and control of complex systems". PhD, Faculdade de Ciências e Tecnologias da Universidade de Coimbra, 2014.
Activities

Oral presentation

Presentation title Event name
Host (Event location)
2024/09 Process Analytics Technology (PAT) modeling using linear and non-linear convolutional approaches ENBIS 24 - European Network for Business and Industrial Statistics
(Leuven, Belgium)
2023/09 Modeling in the Observable or Latent Space? A Comparison of Dynamic Latent Variable based Monitoring for Sensor Fault Detection ENBIS 23 - European Network for Business and Industrial Statistics
(Valência, Spain)
2021/09 A Digital Twin Approach for Statistical Process Monitoring of a High-Dimensional Microelectronic Assembly Process ENBIS 21 - European Network for Business and Industrial Statistics
2018/07/27 Multiresolution Analytics for Large Scale Industrial Processes 10th IFAC Symposium on Advanced Control of Chemical Processes ADCHEM 2018
(China)
2018 A Multiresolution Framework for Building Industrial Soft Sensors ENBIS 18 - European Network for Business and Industrial Statistics
(France)
2016 Markovian and Non-Markovian Sensitivity Enhancing Transformations for Process Monitoring ENBIS 16 - European Network for Business and Industrial Statistics
(United Kingdom)
2015 Translation Invariant Multiscale Energy-based PCA (TIME-PCA) for Monitoring Batch Processes in Semiconductor Manufacturing ENBIS 15 - European Network for Business and Industrial Statistics
(Czech Republic)
2015 Effects of time-varying data on multivariate SPC ENBIS 15 - European Network for Business and Industrial Statistics
(Czech Republic)
2015 An Extensive Comparison Study of Batch Process Monitoring Approaches 2015 AICHE Spring Meeting
(United States)
2014 Fault detection in the Tennessee Eastman process using dynamic principal components analysis with decorrelated residuals 8th International Conference on Partial Least Squares and Related Methods
(France)
2014 Sensitivity enhancing transformations for large-scale process monitoring ESCAPE 24 – 24nd European Symposium on Computer Aided Process Engineering
(Hungary)
2014 Megavariate and Multiscale Monitoring of the Process NETworked Structure: M2NET ENBIS 14 - European Network for Business and Industrial Statistics
(Austria)
2014 Monitoring the Process Correlated Structure Using Partial Correlation Information CHEMPOR 2014 - 12th International Chemical and Biological Engineering Conference
(Portugal)
2014 The Challenges of PCA-Based Statistical Process Monitoring: An Overview and Solutions ENBIS 14 - European Network for Business and Industrial Statistics
(Austria)
2013 A Systematic Comparison of Statistical Process Monitoring Methods for High-dimensional, Time-dependent Processes ENBIS 13 - European Network for Business and Industrial Statistics
(Turkey)
2013 On-line process monitoring using partial correlations ENBIS 13 - European Network for Business and Industrial Statistics
(Turkey)
2011 Multivariate SPC/EPC integration in MIMO dynamic processes CHEMPOR 2011 - 11th International Chemical and Biological Engineering Conference
(Portugal)
2010 Statistical process control of multivariate systems with autocorrelation ENBIS 10 - European Network for Business and Industrial Statistics
(Belgium)
2009 Statistical monitoring of control loops performance ENBIS 9 - European Network for Business and Industrial Statistics
(Sweden)

Supervision

Thesis Title
Role 		Degree Subject (Type)
Institution / Organization
2016 - 2016 Planeamento Estatístico de Experiências para Otimização da Operação de Sensores Analíticos
Co-supervisor of Catarina Pedrosa Santos
Faculdade de Ciências e Tecnologias da Universidade de Coimbra, Portugal

Event organisation

Event name
Type of event (Role) 		Institution / Organization
2019/06/01 - 2019/10/04 Workshop on Advanced Production & Monitoring for the Industry 4.0 (2019/10/04 - 2019/10/04)
Workshop (Member of the Organising Committee)
 Faculdade de Ciências e Tecnologias da Universidade de Coimbra, Portugal
Distinctions

Award

2008 Top 3 % of Students
Faculdade de Ciências e Tecnologias da Universidade de Coimbra, Portugal
2006 Top 3 % of Students
Faculdade de Ciências e Tecnologias da Universidade de Coimbra, Portugal

Other distinction

2014 Winner of 2014 ENBIS Challenge by JMP
European Network for Business and Industrial Statistics, Portugal
2010 Honorable mention for the master dissertation
Associação Portuguesa para a Qualidade, Portugal