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Researcher profile


Juan Carlos Cuevas Tello

Personal Data:
Academic Degree:  PhD Degree
SNI Level:  I
SCOPUS ID: 14059970200
ORBIS ID: n70184
Institutional Data:
Affiliation: Faculty of Engineering

Office address: Av. Dr. Manuel Nava 8 Zona Universitaria Poniente CP. 78290 San Luis Potosí
Phone number: (+52) 4448262300
Ext.: 6252
Email: cuevas@uaslp.mx
  1. PhD Degree in Doctor of Philosophy
    University of Birmingham
  2. Master's Degree in Master of Science
    Universidad Nacional Autónoma de México
  3. Bachelor's Degree in Computer Engineering
    Universidad Autónoma de San Luis Potosí

He is a full-time research professor at the Engineering Faculty – Universidad Autonoma de San Luis Potosi (UASLP) in Mexico. He is research coordinator at the Research and Postgraduate Studies Center (UASLP). He did a postdoc at Tec de Monterrey campus Monterrey (2015). He received his MSc in Computer Science (Artificial Intelligence) from Universidad Nacional Autonoma de Mexico (UNAM) in 2001. He obtained his PhD in Computer Science and Artificial Intelligence at the University of Birmingham (UK) in 2007. He is member of the Mexican Society on Artificial Intelligence, and also of the Institute of Electrical and Electronics Engineers (IEEE). He is member of the National Research System (known as SNI), level 1. He is leader of the consolidated research group Intelligent Systems and Cybersecurity. He is paper reviewer of Neural Networks, Pattern Recognition journals (both from Elsevier) and IEEE Access. He is expert on artificial intelligence in research areas such as Data Mining, Machine Learning, Pattern Recognition, Artificial Neural Networks, Evolutionary Computation, Computer Vision, Deep Learning, High Performance Computing, Bioinformatics and Astroinformatics. The current projects with artificial intelligence includes pattern recognition in time series (astrophysics), algorithms for classification and prediction in health (HIV, influenza, leukemia, etc.), fault diagnosis in batteries with artificial neural networks, and computer vision for the automotive industry (industry 4.0) and health (COVIDx dataset).

Personal Researchs Interest
  1. Artificial Intelligence
Research Interests of Research Group
  1. Social Media Data and Machine Learning to predict Acute Respiratory Infectious diseases
    31/08/2020 - 30/08/2024
    Plenumsoft
  2. Computational model based on Capsule Networks for image classi?cation and object detection
    01/03/2018 - 29/09/2023
    CONACYT
  3. Data science model to estimate accurately time delays of gravitationally lensed quasars
    01/03/2018 - 28/02/2023
    CONACYT
  4. Towards An Intelligent Electric Wheelchair: Computer Vision Module
    31/08/2020 - 28/09/2022
    Université de Pau et des Pays de l'Adour (UPPA)
  5. ModuleNet: A Convolutional Neural Network for Stereo Vision
    28/08/2017 - 15/12/2020
    CIMAT, A.C.
  6. Computational forecasting methodology for Acute respiratory infection using artificial neural networks and search terms
    01/02/2017 - 27/11/2020
    PRODEP-SEP
  7. Machine learning approaches for pattern recognition on genetic data from the Human Immunodeficiency Virus
    01/02/2016 - 13/11/2020
    CONACYT