Research interests

My research area is mainly focused on Machine Learning.
I am specially interested in generative models
Specifically, I have applied copula theory to different subjects such as

  • Wind Resource Estimation
  • E-Commerce Fraud Detection
  • Longitudinal Data Modeling
  • Estimation of Distribution Algorithms
In addition, I am recently involved in visual tracking, which has led me to novel techniques such as Deep Learning.

Works in the news

Consulting

  • EverVest (2014) Co-inventor of patent
  • PatternEx (2016) Principal investigator
  • Ecoembes (2017) Research staff
  • PixelLabs (2017) Research staff
  • Navmii (2017) Research staff
  • BielGlasses (2017) Research staff
  • AMS Geomatics (2018) Co-Principal investigator
  • Simbiotica (2018) Principal investigator

Competitive Projects

  • HARAMI Human Activity Recognition with AMbient Intelligence methods

    2016 -- 2018 MINECO (TIN2015-69542-C2-1-R)
  • IYELMO PaaS for trading

    2011 -- 2014 INNPACTO – IPT-2011-1198-430000
  • TEDICO controllers design techniques developed with the space of parameters, multirate and fractional order calculus methods

    2004 -- 2007 CICYT - DPI2004-05903

Postdoc projects as visiting faculty

  • Massachusetts Institute of Technology Invited by Dr. Kalyan Veeramachaneni (LIDS)

    January, 2018
  • Massachusetts Institute of Technology Invited by Dr. Una-May O'Reilly (CSAIL)

    September -- December, 2010 September -- December, 2013
  • University of New Mexico Time Series Analysis and Prediction using Copulas and Wavelets. Applications in Control Engineering

    January -- August, 2009 José Castillejo research fellowship (JC2008-00421)
  • RCC at Harvard Design of Control Systems regarding Stochastic Dependencies

    Sept--Dec. 2008, 2009, 2010 RRC at Harvard research fellowship

Selected publications

  • A. Sun, A. Cuesta-Infante, K. Veeramachaneni: "Learning Vine Copula Models For Synthetic Data Generation". Accepted in AAAI (2019)
  • I. Ramírez, A. Cuesta-Infante, J.J. Pantrigo, A.S. Montemayor, et al.: "Convolutional neural networks for computer vision-based detection and recognition of dumpsters". Accepted in Neural Computing and Applications (2018)
  • T. Swearingen, W. Drevo, B. Cyphers, A.Ross, A. Cuesta-Infante, K. Veeramachaneni: "ATM: A distributed, collaborative, scalable system for automated machine learning". IEEE Conference on Big Data, 151-162 (2017)
  • A. Cuesta-Infante, F.J. Garcia-Espinosa, J.J. Pantrigo, A.S. Montemayor: "Pedestrian Detection with LeNet-like Convolutional Networks". Neural Computing and Applications, August, 1-7 (2017)
  • I. Arnaldo, A. Cuesta-Infante, A. Arun, M. Lam, C. Bassias, K. Veeramachaneni: "Learning Representations for Log Data in Cybersecurity". Int. Symp. on Cyber Security Cryptography and Machine Learning, 250-268, (2017)
  • B. Lacabex, A. Cuesta-Infante, A.S. Montemayor, J.J. Pantrigo: "Lightweight tracking-by-detection system for multiple pedestrian targets". Integrated Computer-Aided Engineering 23(3): 299-311 (2016)
  • A. Cuesta-Infante, K. Veeramachaneni: "Markov Switching Copula Models for Longitudinal Data". ICDM Workshops 2016: 1104-1109
  • K. Veeramachaneni, A. Cuesta-Infante, U.M. O'Reilly: "Copula Graphical Models for Wind Resource Estimation". IJCAI 2015: 2646-2654
  • J.I. Hidalgo, J.M. Colmenar, J.L. Risco-Martín, A. Cuesta-Infante, E. Maqueda, M. Botella, J.A. Rubio: "Modeling glycemia in humans by means of Grammatical Evolution". Applied Soft Computing 20: 40-53 (2014)
  • More at ORCID ( 0000-0002-3328-501X ) , Scopus ( 35955730700 ) , Google Scholar and DBLP

Teaching

since 2016 Universidad Rey Juan Carlos


Computer Security, Information Systems, Developing Video Games with Artificial Intelligence, Video Games Engineering

1999-2015 C.E.S. Felipe II
(Universidad Complutense de Madrid)


Logic Design, Lab. of Computer Engineering, Networks, Computer Security, Data Warehouses and Data Mining

2009 "Problemas de Estructura y Arquitectura de Computadores" (Book in spanish about Computer Architecture assignments)


A. Cuesta, J.I. Hidalgo, J. Lanchares, J.L. Risco.
ISBN: 97-884832259-1-2, Ed. Pearson.

Education

  • Ph.D. in Computer Science UNED

    2016
  • Ms.S. in Physics UCM

    1998
  • Faculty position qualification 3 (1 is the top)

    2008