Photo Alberto Cano

Alberto Cano

Associate Vice President for Research Computing
Advanced Research Computing
Associate Professor
Department of Computer Science
College of Engineering
Virginia Tech

Office: Torgersen Hall 3050
Email: acano@vt.edu

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About

Alberto Cano is the Associate Vice President for Research Computing and an Associate Professor in the Department of Computer Science at Virginia Tech, United States, where he leads the Advanced Research Computing unit. His research is focused on machine learning, big data, data streams, concept drift, continual learning, GPUs and distributed computing.

Education

Research

Research interests
  • Machine learning: classification, multi-label learning, imbalanced learning, ensemble learning
  • Data streams: self-adaptive learning, concept drift, explainable stream learning
  • Scalability: large-scale data, big data, parallel and distributed high-performance computing, GPUs
  • Metaheuristics: evolutionary machine learning, genetic programming, nature-inspired optimization
Funding
  • 2024-2025Expanding research computing and AI at the HPRC
    Higher Education Equipment Trust Fund, State Council of Higher Education for Virginia, PI, $744,038.
  • 2024-2027Enhancing Multidisciplinary STEM Undergraduate Education through Living Labs
    National Science Foundation, Co-PI, $750,000.
  • 2024-2026Turning Life Science Research into New Products and Businesses that Improve the Human Condition and Accelerate Virginia's Economy
    Go Virginia, State of Virginia, Co-PI, $5M.
  • 2024-2026Cross Reality (XR) Arts & Technology Empowered by Generative and Emotion AI
    Korea Creative Content Agency, PI, $260,000.
  • 2024-2025Data Ecologies: A Transdisciplinary Approach to Data Centers and Data Justice
    VCU Institute for Sustainable Energy and Environment, Co-PI, $100,000.
  • 2023-2026MRI: Track 1 Acquisition of NVIDIA DGX H100 GPU system for research and education at VCU
    National Science Foundation, PI, $299,621.
  • 2023-2024SentimentVoice: Integrating emotion AI and VR in Performing Arts
    Commonwealth Cyber Initiative (CCI), Co-PI, $25,000.
  • 2022-2023HPRC research computing clusters
    Higher Education Equipment Trust Fund, State Council of Higher Education for Virginia, PI, $1,442,280.
  • 2022-2023Multi-Objective Optimization of Inlet Nozzle Design using Artificial Intelligence for Single Tank Thermal Energy Storage
    VCU Accelerate, Co-PI, $100,000.
  • 2020-2022Machine learning for the supply chain management
    Hamilton Beach, PI, $200,000.
  • 2019-2020Real-time price monitoring tool for business intelligence
    Hamilton Beach, PI, $50,000.
  • 2018-2019Hate Speech Detection on Amazon Reviews using Data Stream Mining on Spark and AWS
    Amazon Machine Learning Awards, PI, $25,000 cash + $50,000 AWS credits.
  • 2018-2019Interpretable Data Mining Models for Early Prediction of Student Performance and Dropout
    VCU Presidential Research Quest Fund, PI, $50,000.

Publications

Journal articles
  1. pdf icon Hoeffding adaptive trees for multi-label classification on data streams
    A. Esteban, A. Cano, A. Zafra, and S. Ventura
    Knowledge-Based Systems, 304, 112561, 2024.
  2. pdf icon Improved KD-tree based imbalanced big data classification and oversampling for MapReduce platforms
    W. Sleeman, M. Roseberry, P. Ghosh, A. Cano, and B. Krawczyk
    Applied Intelligence, 54, 12558-12575, 2024.
  3. pdf icon A comprehensive analysis of concept drift locality in data streams
    G. Aguiar and A. Cano
    Knowledge-Based Systems, 289, 111535, 2024.
  4. pdf icon Spatio-temporal visual learning for home-based monitoring
    Y. Djenouri, A. N. Belbachir, A. Cano, and A. Belhadi
    Information Fusion, 101, 101984, 2024.
  5. pdf icon Dynamic budget allocation for sparsely labeled drifting data streams
    G. Aguiar and A. Cano
    Information Sciences, 654, 119821, 2024.
  6. pdf icon A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework
    G. Aguiar, B. Krawczyk, and A. Cano
    Machine Learning, 113, 4165-4243, 2024.
  7. pdf icon Meta-learning for dynamic tuning of active learning on stream classification
    V. Eiji, A. Cano, and S. Barbon
    Pattern Recognition, 138, 109359, 2023.
  8. pdf icon ROSE: Robust Online Self-Adjusting Ensemble for Continual Learning on Imbalanced Drifting Data Streams
    A. Cano and B. Krawczyk
    Machine Learning, 111, 2561-2599, 2022.
  9. pdf icon Adaptive Ensemble of Self-Adjusting Nearest Neighbor Subspaces for Multi-Label Drifting Data Streams
    G. Alberghini, S. Barbon, and A. Cano
    Neurocomputing, 481, 228-248, 2022.
  10. pdf icon Analysis and forecasting of rivers pH level using Deep Learning
    A. Srivastava and A. Cano
    Progress in Artificial Intelligence, 11, 181-191, 2022.
  11. pdf icon An Ontology Matching Approach for Semantic Modeling: A Case Study in Smart Cities
    Y. Djenouri, H. Belhadi, K. Akli-Astouati, A. Cano, and J. Chun-Wei Lin
    Computational Intelligence, 38(3), 876-902, 2022.
  12. pdf icon Hybrid Group Anomaly Detection for Sequence Data: Application to Trajectory Data Analytics
    A. Belhadi, Y. Djenouri, G. Srivastava, A. Cano, and J. Chun-Wei Lin
    IEEE Transactions on Intelligent Transportation Systems, 23(7), 9346-9357, 2022.
  13. pdf icon Machine learning techiniques application in glioma interactome study: a multicentric analysis of 100 patients
    M.L. Gandia-Gonzalez, A. Cano, et al.
    Brain and Spine, vol. 1, sup. 2, 100552, 2021.
  14. pdf icon Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction
    A. Petri, B. Bogaz, A. Cano, and S. Barbon
    Sensors, 21(21), art. 7333, 2021.
  15. pdf icon Self-Adjusting k Nearest Neighbors for Continual Learning from Multi-Label Drifting Data Streams
    M. Roseberry, B. Krawczyk, Y. Djenouri, and A. Cano
    Neurocomputing, 442, 10-25, 2021.
  16. pdf icon Kappa Updated Ensemble for Drifting Data Stream Mining
    A. Cano and B. Krawczyk
    Machine Learning, 109(1), 175-218, 2020.
  17. pdf icon Distributed multi-label feature selection using individual mutual information measures
    J. Gonzalez-Lopez, S. Ventura, and A. Cano
    Knowledge-Based Systems, vol. 188, 105052, 2020.
  18. pdf icon When the Decomposition Meets the Constraint Satisfaction Problem
    Y. Djenouri, D. Djenouri, Z. Habbas, J. Lin, T. Michalak, and A. Cano
    IEEE Access, vol. 8, 207034-207043, 2020.
  19. pdf icon A Two-Phase Anomaly Detection Model for Secure Intelligent Transportation Ride-Hailing Trajectories
    A. Belhadi, Y. Djenouri, G. Srivastava, D. Djenouri, A. Cano, and J. Lin
    IEEE Transactions on Intelligent Transportation Systems, 22(7), 4496-4506, 2020.
  20. pdf icon A Data-Driven Approach for Twitter Hashtag Recommendation
    A. Belhadi, Y. Djenouri, J. Lin, and A. Cano
    IEEE Access, vol. 8, 79182-79191, 2020.
  21. pdf icon Trajectory Outlier Detection: Algorithms, Taxonomies, Evaluation and Open Challenges
    A. Belhadi, Y. Djenouri, J. Lin, and A. Cano
    ACM Transactions on Management Information Systems, 11(30), art. 16, 2020.
  22. pdf icon Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem
    A. Belhadi, Y. Djenouri, J. Lin, C. Zhang, and A. Cano
    IEEE Access, vol. 8, 10569-10583, 2020.
  23. pdf icon A General-Purpose Distributed Pattern Mining System
    A. Belhadi, Y. Djenouri, J. Lin, and A. Cano
    Applied Intelligence, vol. 50, 2647-2662, 2020.
  24. pdf icon Blocking Self-avoiding Walks Stops Cyber-epidemics: A Scalable GPU-based Approach
    H.T. Nguyen, A. Cano, V. Tam, and T.N. Dinh
    IEEE Transactions on Knowledge and Data Engineering, 32(7), 1263-1275, 2020.
  25. pdf icon Distributed selection of continuous features in multi-label classification using mutual information
    J. Gonzalez-Lopez, S. Ventura, and A. Cano
    IEEE Transactions on Neural Networks and Learning Systems, 31(7), 2280-2293, 2020.
  26. pdf icon PSIONplusm Server for Accurate Multi-Label Prediction of Ion Channels and Their Types
    J. Gao, H. Wei, A. Cano, and L. Kurgan
    Biomolecules, 10(6), art. 876, 2020.
  27. pdf icon Multi-label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams
    M. Roseberry, B. Krawczyk, and A. Cano
    ACM Transactions on Knowledge Discovery from Data, 13(6), art. 60, 2019.
  28. pdf icon Evolving Rule-Based Classifiers with Genetic Programming on GPUs for Drifting Data Streams
    A. Cano and B. Krawczyk
    Pattern Recognition, vol. 87, 248-268, 2019.
  29. pdf icon Metabolomics and molecular profiling in glioma patients: an interactomic approach
    A.C. Fuentes-Fayos, M.L. Gandia-Gonzalez, A. Cano, et al.
    Neuro-Oncology, 21(3), 64-65, 2019.
  30. pdf icon Interpretable Multi-view Early Warning System adapted to Underrepresented Student Populations
    A. Cano and J.D. Leonard
    IEEE Transactions on Learning Technologies, 12(2), 198-211, 2019.
  31. pdf icon A Survey on Urban Traffic Anomalies Detection Algorithms
    Y. Djenouri, A. Belhadi, J. Lin, D. Djenouri, and A. Cano
    IEEE Access, vol. 7, 12192-12205, 2019.
  32. pdf icon Adapted k Nearest Neighbors for Detecting Anomalies on Spatio-Temporal Traffic Flow
    Y. Djenouri, A. Belhadi, J. Lin, and A. Cano
    IEEE Access, vol. 7, 10015-10027, 2019.
  33. pdf icon Speeding up k-Nearest Neighbors Classifier for Large-Scale Multi-Label Learning on GPUs
    P. Skryjomski, B. Krawczyk, and A. Cano
    Neurocomputing, vol. 354, 10-19, 2019.
  34. pdf icon Exploiting GPU and Cluster Parallelism in Single Scan Frequent Itemset Mining
    Y. Djenouri, D. Djenouri, A. Belhadi, and A. Cano
    Information Sciences, vol. 496, 363-377, 2019.
  35. pdf icon A survey on graphic processing unit computing for large-scale data mining
    A. Cano
    Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8(1), e1232, 2018.
  36. pdf icon Distributed Nearest Neighbor Classification for Large-Scale Multi-label Data on Spark
    J. Gonzalez-Lopez, S. Ventura, and A. Cano
    Future Generation Computer Systems, vol. 87, 66-82, 2018.
  37. pdf icon OLLAWV: OnLine Learning Algorithm using Worst-Violators
    G. Melki, V. Kecman, S. Ventura, and A. Cano
    Applied Soft Computing, vol. 66, 384-393, 2018.
  38. pdf icon MIRSVM: Multi-Instance Support Vector Machine with Bag Representatives
    G. Melki, A. Cano, and S. Ventura
    Pattern Recognition, vol. 79, 228-241, 2018.
  39. pdf icon Online Ensemble Learning with Abstaining Classifiers for Drifting and Noisy Data Streams
    B. Krawczyk and A. Cano
    Applied Soft Computing, vol. 68, 677-692, 2018.
  40. pdf icon Parallelization Strategies for Markerless Human Motion Capture
    A. Cano, E. Yeguas-Bolivar, R. Muñoz-Salinas, R. Medina-Carnicer, and S. Ventura
    Journal of Real-Time Image Processing, 14(2), 453-467, 2018.
  41. pdf icon A locally weighted learning method based on a data gravitation model for multi-target regression
    O. Reyes, A. Cano, H. Fardoun, and S. Ventura
    International Journal of Computational Intelligence Systems, 11(1), 282-295, 2018.
  42. pdf icon An ensemble approach to multi-view multi-instance learning
    A. Cano
    Knowledge-Based Systems, vol. 136, 46-57, 2017.
  43. pdf icon Extremely High-dimensional Optimization with MapReduce: Scaling Functions and Algorithm
    A. Cano, C. Garcia, and S. Ventura
    Information Sciences, vol. 415-416, 110-127, 2017.
  44. pdf icon Multi-Target Support Vector Regression Via Correlation Regressor Chains
    G. Melki, A. Cano, V. Kecman, and S. Ventura
    Information Sciences, vol. 415-416, 53-69, 2017.
  45. pdf icon Multi-Objective Genetic Programming for Feature Extraction and Data Visualization
    A. Cano, S. Ventura, and K.J. Cios
    Soft Computing, 21(8), 2069-2089, 2017.
  46. pdf icon Discovering Useful Patterns from Multiple Instance Data
    J.M. Luna, A. Cano, V. Sakalauskas, and S. Ventura
    Information Sciences, vol. 357, 23-38, 2016.
  47. pdf icon LAIM discretization for multi-label data
    A. Cano, J.M. Luna, E.L. Gibaja, and S. Ventura
    Information Sciences, vol. 330, 370-384, 2016.
  48. pdf icon ur-CAIM: improved CAIM discretization for unbalanced and balanced data
    A. Cano, D.T. Nguyen, S. Ventura and K.J. Cios
    Soft Computing, 20(1), 173-188, 2016.
  49. pdf icon Speeding-up Association Rule Mining with Inverted Index Compression
    J.M. Luna, A. Cano, M. Pecheniskiy, and S. Ventura
    IEEE Transactions on Cybernetics, 46(12), 3059-3072, 2016.
  50. pdf icon Early Dropout Prediction using Data Mining: A Case Study with High School Students
    C. Márquez-Vera, A. Cano, C. Romero, A. Yousef Mohammad, H. Mousa Fardoun, and S. Ventura
    Expert Systems, 33(1), 107-124, 2016.
  51. pdf icon A Classification Module for Genetic Programming Algorithms in JCLEC
    A. Cano, J.M. Luna, A. Zafra, and S. Ventura
    Journal of Machine Learning Research, vol. 16, 491-494, 2015.
  52. pdf icon Speeding up multiple instance learning classification rules on GPUs
    A. Cano, A. Zafra, and S. Ventura
    Knowledge and Information Systems, 44(1), 127-145, 2015.
  53. pdf icon Scalable CAIM discretization on multiple GPUs using concurrent kernels
    A. Cano, S. Ventura, and K.J. Cios
    Journal of Supercomputing, 69(1), 273-292, 2014.
  54. pdf icon Parallel evaluation of Pittsburgh rule-based classifiers on GPUs
    A. Cano, A. Zafra, and S. Ventura
    Neurocomputing, vol. 126, 45-57, 2014.
  55. pdf icon Predicting student failure at school using genetic programming and different data mining approaches with high dimensional and imbalanced data
    C. Márquez-Vera, A. Cano, C. Romero, and S. Ventura
    Applied Intelligence, 38 (3), 315-330, 2013.
  56. pdf icon High Performance Evaluation of Evolutionary-Mined Association Rules on GPUs
    A. Cano, J.M. Luna, and S. Ventura
    Journal of Supercomputing, 66(3), 1438-1461, 2013.
  57. pdf icon An Interpretable Classification Rule Mining Algorithm
    A. Cano, A. Zafra, and S. Ventura
    Information Sciences, vol. 240, 1-20, 2013.
  58. pdf icon Parallel Multi-Objective Ant Programming for Classification Using GPUs
    A. Cano, J.L. Olmo, and S. Ventura
    Journal of Parallel and Distributed Computing, 73 (6), 713-728, 2013.
  59. pdf icon Weighted Data Gravitation Classification for Standard and Imbalanced Data
    A. Cano, A. Zafra, and S. Ventura
    IEEE Transactions on Cybernetics, 43 (6) pages 1672-1687, 2013.
  60. pdf icon Speeding up the evaluation phase of GP classification algorithms on GPUs
    A. Cano, A. Zafra, and S. Ventura
    Soft Computing, 16 (2), 187-202, 2012.
Edited books
  1. pdf icon Social Media and Machine Learning
    A. Cano
    InTech, ISBN 978-1-78984-028-5, 2020.
  2. pdf icon Big Data on Real-World Applications
    S. Ventura, J. M. Luna, and A. Cano
    InTech, ISBN 978-953-51-2490-0, 2016.
Book chapters
  1. pdf icon Genetic Programming for Mining Association Rules in Relational Database Environments
    J.M. Luna, A. Cano and S. Ventura
    Handbook of Genetic Programming Applications, Springer, ISBN 978-3-319-20882-4, 2015.
  2. pdf icon An Evolutionary Self-Adaptive Algorithm for Mining Association Rules. In Data Mining: Principles
    J.M. Luna, A. Cano and S. Ventura
    Applications and Emerging Challenges, Nova Publishers, ISBN 978-1-63463-770-1, 2015.
International conference contributions
  1. pdf icon Vision-based Spatiotemporal Learning for Human Activity Recognition
    Y. Djenouri, G. Srivastava, A. Nabil, and A. Cano
    IEEE International Joint Conference on Neural Networks, 2024.
  2. pdf icon Enhancing Concept Drift Detection in Drifting and Imbalanced Data Streams through Meta-Learning
    G. Aguiar and A. Cano
    IEEE International Conference on Big Data, 2648-2657, 2023.
  3. pdf icon Aging and rejuvenating strategies for fading windows in multi-label classification on data streams
    M. Roseberry, S. Dzeroski, A. Bifet and A. Cano
    38th ACM/SIGAPP Symposium On Applied Computing, 390-397, 2023.
  4. pdf icon An active learning budget-based oversampling approach for partially labeled multi-class imbalanced data streams
    G. Aguiar and A. Cano
    38th ACM/SIGAPP Symposium On Applied Computing, 382-389, 2023.
  5. pdf icon An explainable classifier based on genetically evolved graph structures
    J. Bertini and A. Cano
    IEEE Congress on Evolutionary Computation, 2022.
  6. pdf icon Locally Linear Support Vector Machines for Imbalanced Data Classification
    B. Krawczyk and A. Cano
    Pacific-Asia Conference on Knowledge Discovery and Data Mining, 616-628, 2021.
  7. pdf icon An Endocrine and metabolic interactomic approach to identify novel diagnostic/prognostic biomarkers and therapeutic targets in gliomas
    J. Perez, [...], A. Cano, et. al.
    22nd European Congress of Endocrinology, 2020.
  8. pdf icon Active Learning with Abstaining Classifiers for Imbalanced Drifting Data Streams
    L. Korycki, A. Cano, and B. Krawczyk
    IEEE BigData, 2334-2343, 2019.
  9. pdf icon Adaptive ensemble active learning for drifting data stream mining
    B. Krawczyk and A. Cano
    International Joint Conference on Artificial Intelligence, 2763-2771, 2019.
  10. pdf icon ARFF data source library for distributed single/multiple instance, single/multiple output learning on Apache Spark
    J. Gonzalez-Lopez, S. Ventura, and A. Cano
    International Conference on Computational Science, 173-179, 2019.
  11. pdf icon Speeding up Classifier Chains in Multi-Label Classification
    J.M. Moyano, E. Gibaja, S. Ventura, and A. Cano
    International Conference on Internet of Things, Big Data and Security, 29-37, 2019.
  12. pdf icon Multi-label kNN Classifier with Self Adjusting Memory for Drifting Data Streams
    M. Roseberry and A. Cano
    Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA@PKDD/ECML, PMLR 94:23-37, 2018.
  13. pdf icon Learning classification rules with differential evolution for high-speed data stream mining on GPUs
    A. Cano and B. Krawczyk
    IEEE Congress on Evolutionary Computation, 197-204, 2018.
  14. pdf icon Selecting local ensembles for multi-class imbalanced data classification
    B. Krawczyk, A. Cano, and M. Wozniak
    International Joint Conference on Neural Networks, 1848-1855, 2018.
  15. pdf icon Large-scale multi-label ensemble learning on Spark
    J. Gonzalez-Lopez, A. Cano, and S. Ventura
    IEEE Trustcom/BigDataSE/ICESS, 893-900, 2017.
  16. pdf icon Parsing MetaMap Files in Hadoop
    A. Olex, B. McInnes, and A. Cano
    American Medical Informatics Association Symposium, 2017.
  17. pdf icon Sentiment Classification from Multi-Class Imbalanced Twitter Data using Binarization
    B. Krawczyk, B. McInnes, and A. Cano
    12th International Conference on Hybrid Artificial Intelligent Systems, Lecture Notes in Computer Science, vol 10334, 26-37, 2017.
  18. pdf icon 100 Million Dimensions Large-Scale Global Optimization Using Distributed GPU Computing
    A. Cano and C. Garcia-Martinez
    IEEE Congress on Evolutionary Computation, 3566-3573, 2016.
  19. pdf icon A Data Structure to Speed-Up Machine Learning Algorithms on Massive Datasets
    F. Padillo, J.M. Luna, A. Cano, and S. Ventura
    11th International Conference on Hybrid Artificial Intelligent Systems. Lecture Notes in Computer Science, vol 9648, 365-376, 2016.
  20. pdf icon Synthesis of In-Place Iterative Sorting Algorithms Using GP: A Comparison Between STGP, SFGP, G3P and GE
    D. Pinheiro, A. Cano and S. Ventura
    17th Portuguese Conference on Artificial Intelligence. Lecture Notes in Computer Science, vol 9273, 305-310, 2015.
  21. pdf icon GPU-parallel subtree interpreter for genetic programming
    A. Cano and S. Ventura
    Conference on Genetic and Evolutionary Computation, 887-894, 2014.
  22. pdf icon Classification Rule Mining with Iterated Greedy
    J.A. Pedraza, C. Garcia-Martinez, A. Cano, and S. Ventura
    9th International Conference on Hybrid Artificial Intelligent Systems (HAIS). Lecture Notes in Computer Science, 8480 LNCS:585-596, 2014.
  23. pdf icon A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification
    A. Cano, A. Zafra, E.L. Gibaja, and S. Ventura
    16th European Conference on Genetic Programming, EuroGP'13. Lecture Notes in Computer Science, vol 7831, 217-228, 2013.
  24. pdf icon Binary and Multiclass Imbalanced Classification Using Multi-Objective Ant Programming
    J.L. Olmo, A. Cano, J.R. Romero, and S. Ventura
    12th International Conference on Intelligent Systems Design and Applications, ISDA'12, 70-76, 2012.
  25. pdf icon An EP algorithm for learning highly interpretable classifiers
    A. Cano, A. Zafra, and S. Ventura
    11th International Conference on Intelligent Systems Design and Applications, ISDA'11, 325-330, 2011.
  26. pdf icon A parallel genetic programming algorithm for classification
    A. Cano, A. Zafra, and S. Ventura
    6th International Conference on Hybrid Artificial Intelligent Systems (HAIS). Lecture Notes in Computer Science, 6678 LNAI(PART 1):172-181, 2011.
  27. pdf icon JCLEC meets WEKA!
    A. Cano, J.M. Luna, J.L. Olmo, and S. Ventura
    6th International Conference on Hybrid Artificial Intelligent Systems (HAIS). Lecture Notes in Computer Science, 6678 LNAI(PART 1):388-395, 2011.
  28. pdf icon Solving classification problems using genetic programming algorithms on GPUs
    A. Cano, A. Zafra, and S. Ventura
    5th International Conference on Hybrid Artificial Intelligent Systems (HAIS). Lecture Notes in Computer Science, 6077 LNAI(PART 2):17-26, 2010.
  29. pdf icon On-site forest fire smoke detection by low-power autonomous vision sensor
    J. Fernández-Berni, R. Carmona-Galán, L. Carranza-González, A. Cano-Rojas, J. F. Martínez-Carmona, Á. Rodríguez-Vázquez, and S. Morillas-Castillo
    VI International Conference on Forest Fire Research, page 94, 2010.
Tutorials in international conferences
  1. pdf icon Learning from imbalanced data streams
    A. Cano
    IEEE World Congress on Computational Intelligence, 2024.
  2. pdf icon Big Data Stream Mining
    B. Krawczyk and A. Cano
    IEEE International Conference on Big Data, 2020.
  3. pdf icon Learning from non-stationary data streams
    B. Krawczyk and A. Cano
    IEEE International Conference on Data Science and Advanced Analytics, 2019.
Research & teaching and innovation publications in Spanish
  1. pdf icon Optimización con 100 millones de variables reales sobre múltiples unidades de procesamiento gráfico
    A. Cano and C. Garcia-Martinez
    XI Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), 377-386, 2016.
  2. pdf icon Autómatas celulares y aplicaciones
    A. Cano and A. Rojas
    UNIÓN. Revista Iberoamericana de Educación Matemática, (46):33-48, 2016.
  3. pdf icon Evaluación distribuida transparente para algoritmos evolutivos en JCLEC
    F. Ibáñez A. Cano, and S. Ventura
    II Jornadas de Algoritmos Evolutivos y Metaheurísticas (XVI CAEPIA), 231-240, 2015.
  4. pdf icon Diseño Automático de Multi-Clasificadores Basados en Proyecciones de Etiquetas
    J.M. Moyano, E.L. Gibaja, A. Cano, J.M. Luna, and S. Ventura
    II Jornadas de Fusión de la Información y ensembles (XVI CAEPIA), 355-366, 2015.
  5. pdf icon Algoritmo evolutivo para optimizar ensembles de clasificadores multi-etiqueta
    J.M. Moyano, E.L. Gibaja, A. Cano, J.M. Luna, and S. Ventura
    X Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), 219-225, 2015.
  6. pdf icon Cómo compartir un secreto usando sistemas de ecuaciones lineales
    A. Cano, J.M. Luna, and A. Rojas
    Suma, (79):33-39, 2015.
  7. pdf icon Programación Automática con Colonias de Hormigas Multi-Objetivo en GPUs
    A. Cano, J.L. Olmo, and S. Ventura
    IX Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), 288-297, 2013.
  8. pdf icon Parallel Data Mining Algorithms on GPUs
    A. Cano, A. Zafra, and S. Ventura
    Doctoral Consortium de la Conferencia de la Asociacion Española para la Inteligencia Artificial (CAEPIA), 1603-1606, 2013.
  9. pdf icon Modelo gravitacional para clasificación
    A. Cano, J.M. Luna, A. Zafra, and S. Ventura
    VIII Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), 63-70, 2012.
  10. pdf icon Programación con Hormigas Multi-Objetivo para la Extracción de Reglas de Clasificación
    J.L. Olmo, A. Cano, J.R. Romero, and S. Ventura
    VIII Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), 219-226, 2012.
  11. pdf icon Motivando el aprendizaje del Álgebra lineal a través de sus aplicaciones: la división de secretos
    A. Rojas and A. Cano
    XX Congreso universitario de innovación educativa en las enseñanzas técnicas, 2012.
  12. pdf icon Interpolación polinómica y la división de secretos
    A. Rojas and A. Cano
    XIV Congreso de Enseñanza y Aprendizaje de las Matemáticas, 2012.
  13. pdf icon Cifrado de imágenes y matemáticas
    A. Rojas and A. Cano
    TE&ET. Revista Iberoamericana de Tecnología en Educación y Educación en Tecnología, (6):30-37, 2011.
  14. pdf icon Una clase de aritmética modular, matrices y cifrado para ingeniería
    A. Rojas and A. Cano
    UNIÓN. Revista Iberoamericana de Educación Matemática, 1(25):89-108, 2011.
  15. pdf icon Speeding up evolutionary learning algorithms using GPUs
    A. Cano, A. Zafra, and S. Ventura
    ESTYLF 2010 XV Congreso Español sobre Tecnologías y Lógica Fuzzy, 229-234, 2010.
  16. pdf icon Trabajando con imágenes digitales en clase de matemáticas
    A. Rojas and A. Cano
    La Gaceta de la Real Sociedad Matemática Española, 2(13):317-336, 2010.
  17. pdf icon Recursos didácticos en el grado en ingeniería informática para el aprendizaje de matemáticas a través de la programación de ordenadores
    E. Gibaja, A. Zafra, M. Luque, and A. Cano
    II Jornadas Andaluzas de Informática, 90-95, 2011.
  18. pdf icon Cifrado de imágenes y reparto de secretos en clase de matemáticas
    A. Rojas and A. Cano
    XV Jornadas para el Aprendizaje y Enseñanza de las Matemáticas, 2011.
  19. pdf icon Motivando el aprendizaje del álgebra lineal a través de sus aplicaciones
    A. Rojas and A. Cano
    II Jornadas sobre Innovación Docente y Adaptación al EEES en las Titulaciones Técnicas, 2011.
  20. Álgebra lineal y cifrado de imágenes
    A. Rojas and A. Cano
    CEAM 2010 XIII Congreso de enseñanza y aprendizaje de las matemáticas, 2010.
  21. Reparto de secretos usando un sudoku
    A. Cano
    CEAM 2010 XIII Congreso de enseñanza y aprendizaje de las matemáticas, 2010.
  22. Coloreado de imágenes y sistemas de ecuaciones lineales
    A. Cano and A. Rojas
    CEAM 2010 XIII Congreso de enseñanza y aprendizaje de las matemáticas, 2010.
  23. Fotomontajes de imágenes digitales y sistemas de ecuaciones lineales
    A. Cano and A. Rojas
    CEAM 2010 XIII Congreso de enseñanza y aprendizaje de las matemáticas, 2010.
  24. Descomposición en valores singulares e imágenes
    A. Rojas and A. Cano
    CEAM 2010 XIII Congreso de enseñanza y aprendizaje de las matemáticas, 2010.
  25. Álgebra lineal, secretos e imágenes
    A. Rojas and A. Cano
    CUIEET 2010 XVIII Congreso universitario de innovación educativa en las enseñanzas técnicas, 2010.
  26. Innovación en clase de matemáticas
    A. Rojas and A. Cano
    CUIEET 2010 XVIII Congreso universitario de innovación educativa en las enseñanzas técnicas, 2010.
  27. Descomposición en valores singulares e imágenes
    A. Cano and A. Rojas
    I Jornadas Andaluzas de Informática, 2009.
  28. Aplicaciones del álgebra lineal en la vida cotidiana
    A. Rojas and A. Cano
    XIV Jornadas para el Aprendizaje y Enseñanza de las Matemáticas, 2009
  29. Adecuación de la red WiFi para cumplimiento de la normativa y permitir acceso a internet a los pacientes
    R. Molina, J. Jiménez, C. Sánchez, and A. Cano
    XI Congreso Nacional de Informática de la Salud, 2008.

Professional Services

Editor in journals
  • Area Editor of Information Fusion2022-date
  • Associate Editor of PeerJ Computer Science2020-date
  • Associate Editor of Applied Intelligence2019-date
  • Associate Editor of IEEE Access2018-date
Reviewer in journals (selection)
  • Applied Intelligence
  • IEEE Access
  • Soft Computing
  • Expert Systems with Applications
  • IEEE Transactions on Cybernetics
  • Information Sciences
  • Neural Computing and Applications
  • Knowledge-Based Systems
  • Neurocomputing
  • Machine Learning
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Evolutionary Computation
  • Knowledge and Information Systems
  • ACM Transactions on Knowledge Discovery from Data
  • IEEE Transactions on Knowledge and Data Engineering
  • Pattern Recognition
Conference organization (selection)
  • IEEE International Conference on Omni-layer Intelligent Systems. Track: Artificial Intelligence, Machine Learning, and Analytics2022
  • IEA/AIE. Special Session Lifelong and Continual Learning on Data Streams: Algorithms and Applications2022
  • Federated Conference on Computer Science and Information Systems. Track 4: Advances in Information Systems and Technologies2021-2023
  • IEA/AIE. Special Session on Data Stream Mining: Algorithms and Applications2021
  • IEEE International Symposium on Computer-Based Medical Systems2019
  • IEEE International Conference on Big Data. Special Track on Real-Time Big Data Analytics2018
  • International Conference on Intelligent Systems Design and Applications2011
Technical program committee in conferences (selection)
  • International Conference on Intelligent Systems Design and Applications
  • IEEE International Conference on Big Data Intelligence and Computing
  • IEEE Congress on Evolutionary Computation
  • International Conference on Educational Data Mining
  • International Joint Conference on Neural Networks
  • International Conference on Computational Collective Intelligence
  • International Conference on Soft Computing and Pattern Recognition
  • Federated Conference on Computer Science and Information Systems
  • International Conference on Hybrid Artificial Intelligence Systems
  • IEEE International Conference on Big Data
  • International Conference on Computational Science
  • International Conference on Discovery Science
  • IEEE World Congress on Computational Intelligence
  • International Joint Conference on Artificial Intelligence
  • ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Funding proposal reviewer
  • National Science Foundation, United StatesAnnually
  • Fonds Wetenschappelijk Onderzoek, Belgium2018
  • Chilean National Science and Technology, Chile2018
  • Israeli Science Foundation, Israel2017
  • National Centre of Science and Technology Evaluation, Kazakhstan2017
Memberships
  • IEEE Senior Member2019-date
  • IEEE Member2009-2019
  • ACM Senior Member2023-date
  • ACM Member2016-2023

Teaching

  • (VCU) CMSC 508 - Databases2016-date
  • (VCU) CMSC 603 - High Performance Distributed Systems2016-date
  • (UCO) Graduate Teaching Assistant for Operating Systems2013-2015
  • (UCO) Graduate Teaching Assistant for Databases2013-2015