Xurxo Rigueira

Ph.D. Student at the University of Vigo.

xurxo.rigueira@uvigo.es

About me

I am a Computer Science Ph.D. Student at the School of Mining and Energy Engineering and the Higher School of Computer Engineering with affiliation to the University of Vigo. My research focuses on the development of robust, efficient, and intelligent algorithms for the detection and prediction of extreme events in hydrology.

Here you can find my research profiles and CV.

Education

• Ph.D. at the University of Vigo, Spain, present
  School of Mining and Energy Engineering and Higher School of Computer Engineering
  Advisers: Prof. Dr. Maria Araujo Fernandez and Prof. Dr. David N. Olivieri
  Thesis: Contributions to functional data analysis and machine learning for environmental modeling.
  

• M.S. at the University of Vigo, Spain, 2020
  School of Mining and Energy Engineering
  Advisers: Prof. Dr. Pablo Eguia Oller and David Lopez Mera
  Thesis: Design and simulation on MATLAB/Simulink of a solar carport.
  

• B.S. at California State University, East Bay, USA, 2018
  Major: Environmental Engineering
  International Student
  

• B.S. at the University of Vigo, Spain, 2018
  Major: Mining and Energy Resources Engineering
  

Work experience

• University of Vigo, Vigo, Spain
  Graduate Research Assistant, present
  University of Vigo

• Soltec Ingenieros, Vigo, Spain
  Industrial and Process Engineer, 2020
  Soltec Ingenieros

Research on functional data analysis in hydrology

• Bayesian machine learning and functional data analysis as a two-fold approach for the study of acid mine drainage events
  X. Rigueira, M. Pazo, M. Araujo, S. Gerassis, and E. Bocos
  Water, 2023, 15 (8), 1553

• Functional data analysis for the detection of outliers and study of the effects of the COVID-19 pandemic on air quality: a case study in Gijon, Spain
  X. Rigueira, J. Martinez, M. Araujo, P.J. Garcia-Nieto, and I. Ocarranza
  Mathematics, 2022, 10 (14), 2374

• Directional outlyingness for the detection of functional outliers in water quality data
  X. Rigueira, J. Martinez, M. Araujo, and E. Giraldez
  6th International Congress on Water, Waste and Energy Management, July, 2022. Rome, Italy

• Multivariate functional data analysis for outlier detection in environmental data
  X. Rigueira, J. Martinez, M. Araujo, M. Pazo-Rodriguez, and J. Taboada
  14th Congress on Mathematical Modelling in Engineering and Human Behaviour, July, 2022. Valencia, Spain

Research on machine learning in hydrology

• Enhancing water quality prediction for fluctuating missing data scenarios: A dynamic Bayesian network-based processing system to monitor cyanobacteria proliferation
  M. Pazo, S. Gerassis, M. Araujo, M. Antunes, and X. Rigueira
  Science of the Total Environment, 2024, 927, 172340

• Real-time incremental machine learning for anomaly detection and surveillance in water quality
  X. Rigueira, D. Olivieri, M. Araujo, M. Pazo, and E. Alonso
  Water Innovation and Circularity Conference, June, 2023. Athens, Greece

Research on computer vision

• Automatic Characterization of Block-In-Matrix Rock Outcrops through Segmentation Algorithms and Its Application to an Archaeo-Mining Case Study
  A. Cristobal, X. Rigueira, I. Perez-Rey, X. Estevez-Ventosa, M. Pazo, M. L. Napoli, B. X. Curras and L. R. Alejano
  Geosciences, 2024, 14 (2), 29

• Computer Vision Application for Improved Product Traceability in the Granite Manufacturing Industry
  X. Rigueira, J. Martinez, M. Araujo, and A. Recaman
  Materiales de Construcción, 2022, 73 (351), 93-103

Research on artificial intelligence in education

• Impact of artificial intelligence on assessment methods in primary and secondary education: Systematic literature review
  M. Martinez-Comesana X. Rigueira-Diaz, A. Larranaga-Janeiro, J. Martinez-Torres, I. Ocarranza-Prado, and D. Kreibel
  Psicodicatica, 2023, 28 (2)

Extra: my grandpa's brother wrote a book. You can find it here