José Rodellar, PhD

José Rodellar, PhD

Department of Mathematics

Technical University of Catalunya

Barcelona Est Engineering School

Eduard Maristany 16

08019, Barcelona, Spain






Current position



Director of the Department of Mathematics

Director of the Research Group Control, Modelling, Identification and Applications (CoDAlab)



  • Degree in Physics (1976), PhD in Physics (automatic control) (1982), both in Universty of Barcelona.
  • Fullbright postdoc in the University of California, Berkeley, Department of Mechanical Engineering, 1989-1990

Research interests


  • Modelling and control of dynamical systems in different engineering domains
  • Monitoring and detection of abnomalies in engineering systems using data models and machine learning
  • Machine learning and deep learning approaches for automatic classification
  • Automatic recognition of abnormal peripheral blood cells using machine and deep learning to support haematological diagnosis based on microscope digital image processing.


J. Rodellar has achieved international recognition, publishing extensively in the above lines (around 250 references in JCR), including three books and six patents. He has been principal investigator of 27 competitive projects. He has supervised 26 doctoral thesis (4 in progress) and a dozen of postdocs and visiting researchers.


Selected publications

A full organized list is available by CLICKING to the web of the UPC Scientific Production.


Acevedo, A.; Alférez, S.; Merino, A.; Puigví, L.; Rodellar, J. Recognition of peripheral blood cell images using convolutional neural networks. Computer Methods and Programs in Biomedicine 2019.


Boldú, L.; Merino, A.; Alférez, S.; Molina, A.; Acevedo, A.; Rodellar, J. Automatic recognition of different types of acute leukaemia in peripheral blood by image analysis. Journal of Clinical Pathology 2019. DOI:10.1136/jclinpath-2019-205949.


Alférez, S.; Merino, A.; Acevedo, A.; Puigví, L.; Rodellar, J. Colour clustering segmentation framework for image analysis of malignant lymphoid cells in peripheral blood. Medical & Biological Engineering & Computing 2019. DOI:10.1007/s11517-019-01954-7.


Puigví, L.; Merino, A.; Boldú L.; Acevedo, A.; Alférez, S.; Rodellar, J. Quantitative cytological descriptors to differentiate CLL, Sézary, granular and villous lymphocytes through image analysis. American Journal of Clinical Pathology 2019. DOI: 10.1093/ajcp/aqz025.


Mújica, L.E.; Gharibnezhad, F.; Rodellar, J.; Todd, M. Considering temperature effect on robust principal component analysis orthogonal distance as a damage detector. Structural Health Monitoring 2019.


Rodellar, J.; Alférez, S.; Acevedo, A.; Molina A.; Merino A. Image processing and machine learning in the morphological analysis of blood cells. International Journal of Laboratory Hematology 2018. DOI: 10.1111/ijlh.12818.


Merino, A.; Puigví, L.; Boldú, L.; Alferez, S.; Rodellar, J. Optimizing morphology through blood cell image analysis. International Journal of Laboratory Hematology 2018. DOI:10.1111/ijlh.12832.


Ruiz, M.; Mujica, L.E.; Alférez, S.; Acho, L.; Tutivén, C.; Vidal, Y.; Rodellar, J.; Pozo, F.; Wind turbine fault detection and classification by means of image texture analysis. Mechanical Systems and Signal Processing 2018. DOI:10.1016/j.ymssp.2017.12.035.


Ruiz, M.; Mújica, L.E.; Sierra, J.; Pozo, F.; Rodellar, J. Multiway principal component analysis contributions for structural damage location. Structural Health Monitoring-an International Journal, 2018; 17(5), 1151-1165.


Puigví, L.; Merino, A.; Alférez, S.; Acevedo, A.; Rodellar, J. New quantitative features for the morphological differentiation of abnormal lymphoid cell images from peripheral blood. Journal of Clinical Pathology 2017; 70: 1038-48. DOI: 10.1136/jclinpath-2017-204389.


Alferez, E.; Merino, A.; Bigorra, L.; Rodellar, J. Characterization and automatic screening of reactive and abnormal neoplastic B lymphoid cells from peripheral blood. International Journal of Laboratory Hematology 2016; 38(2): 209-219. DOI: 10.1111/ijlh.12473.


Bigorra, L.; Merino, A.; Alferez, E.; Rodellar, J. Feature Analysis and Automatic Identification of Leukemic Lineage Blast Cells and Reactive Lymphoid Cells from Peripheral Blood Cell Images. Journal of Clinical Laboratory Analysis 2016. DOI: 10.1002/jcla.22024.


Alferez, E.; Merino, A.; Bigorra, L.; Mujica, L.E.; Ruiz, M.; Rodellar, J. Automatic recognition of atypical lymphoid cells from peripheral blood by digital image analysis. American Journal of Clinical Pathology 2015; 143(2): 168-76. DOI: 10.1309/AJCP78IFSTOGZZJN.


Alferez, E.; Merino, A.; Mujica, L.E.; Ruiz, M.; Bigorra, L.; Rodellar, J. Automatic classification of atypical lymphoid B cells using digital blood image processing. International Journal of Laboratory Hematology 2014; 36(4): 472-80. DOI: 10.1111/ijlh.12175.


Gharibnezhad, F.; Mújica, L.E.; Rodellar, J. Applying robust variant of Principal Component Analysis as a damage detector in the presence of outliers. Mechanical Systems and Signal Processing 2015 50-51: 467-479.


Mújica, L.E.; Ruiz, M.; Pozo, F.; Rodellar, J.; Güemes, A. A structural damage detection indicator based on principal component analysis and statistical hypothesis testing, Smart Materials and Structures 2014; 23(2).


Torres-Arredondo, A.;  Tibaduiza, D.; Mújica, L.E.; Rodellar, J.; Fritzen, C.P.  Data-driven multivariate algorithms for damage detection and identification: Evaluation and comparison, Structural Health Monitoring-an International Journal 2014; 13(1): 19-32.


Tibaduiza, D.; Torres-Arredondo, M.A.; Mújica, l.E.; Rodellar, J.; Fritzen. C.P.  A study of two unsupervised data driven statistical methodologies for detecting and classifying damages in structural health monitoring, Mechanical Systems and Signal Processing 2013; 41: 467-484.


Mújica, L.E.; Rodellar, J.; Fernández, A.; Güemes, A. Q-statistic and T-2-statistic PCA-based measures for damage assessment in structures, Structural Health Monitoring-an International Journal 2011; 10(5): 539-553.


Scientific societies


  • Vocal of the Education Committee of the International Society of the Laboratory of Hematology (ISLH)
  • European Committee for External Quality Assurance Programmes in Laboratory Medicine. Virtual Microscopy Working Group
  • Member of the EFLM distance education group
  • Member of the IFCC distance education group
  • Member of the ICSH group