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Carlos Beltrán Pérez

Professor en Tecnológico de Monterrey
Profile Carlos Beltrán

Tecnológico de Monterrey, Campus Toluca.

Professors

Semblance

Degrees obtained:
Ph.D. in Automatic Control and Systems Engineering from the University of Sheffield, United Kingdom, 2019.
Master of Science in Systems Engineering from the Universidad Autónoma de Nuevo León, Mexico, 2012.
Bachelor's Degree in Industrial Engineering from the Universidad Autónoma Metropolitana, Mexico, 2009.

Research interests:
General: Machine learning, dynamic systems modeling, operations research, industrial engineering.
Specific: Nonlinear identification of dynamic systems, optimization models for logistics and management, multiclass classification models for static and dynamic problems, medical image processing, forecasting, and time series analysis.

Expertise and Skills

  • Industrial Computing
  • Image Processing
  • Medical Image Analysis
  • Operations Research
  • System Identification
  • Metaheuristic Algorithms
  • Nonlinear Analysis
  • Advanced Machine Learning
  • NARMAX (Nonlinear Autoregressive Moving Average with Exogenous Inputs)
  • Multilayer Neural Networks
  • Nonlinear Identification of Dynamic Systems
  • Optimization Models for Logistics and Management
  • Multiclass Classification Models for Static and Dynamic Problems
  • Forecasting
  • Time Series Analysis


Academic Publications

 

  1. Models for predicting corrosion inhibition efficiency of common drugs on steel surfaces: A rationalized comparison among methodologies
    https://www.scopus.com/record/display.uri?eid=2-s2.0-85199504315&origin=resultslist
  2. An Extended Unit Restriction Model with Environmental Considerations for Forest Harvesting
    https://www.scopus.com/record/display.uri?eid=2-s2.0-85156154689&origin=resultslist
  3. Classification of EEG Signals for Brain-Computer Interfaces using a Bayesian-Fuzzy Extreme Learning Machine
  4. A general use QSAR-ARX model to predict the corrosion inhibition efficiency of drugs in terms of quantum mechanical descriptors and experimental • comparison for lidocaine
    https://www.scopus.com/record/display.uri?eid=2-s2.0-85129432592&origin=resultslist
  5. A multilayer interval type-2 fuzzy extreme learning machine for the recognition of walking activities and gait events using wearable sensors
  6. Generalized multiscale RBF networks and the DCT for breast cancer detection
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