Docente

Mario Inostroza-Ponta

Ingeniero Civil en Informática de la Universidad de Santiago de Chile y PhD en Computer Science de la Universidad de Newcastle Australia. Director del Departamento de Ingeniería Informática de la Universidad de Santiago de Chile. Sus principales líneas de investigación se vinculan con las áreas de la inteligencia artificial y aprendizaje de máquinas, aplicadas a problemas de optimización combinatoria en bioinformática y otras áreas. Ha desarrollado proyectos en los campos de salud, energía, agricultura y sectores productivos.

Formación académica

  • Ingeniero Civil en Informática de la Universidad de Santiago de Chile y PhD en Computer Science de la Universidad de Newcastle

Publicaciones

  • PUBLICACIÓN, 2020, Exploring the high selectivity of 3-D protein structures using distributed memetic algorithms, DOI: 10.1016/j.jocs.2020.101087
  • PUBLICACIÓN, 2020, Molecular modeling of epithiospecifier and nitrile-specifier proteins of broccoli and their interaction with aglycones, DOI: 10.3390/molecules25040772
  • PUBLICACIÓN,  2020, Comparison of phylogenetic tree topologies for nitrogen associated genes partially reconstruct the evolutionary history of saccharomyces cerevisiae, DOI: 10.3390/microorganisms8010032
  • PUBLICACIÓN, 2019, Dealing with the Balanced Academic Curriculum Problem considering the Chilean Academic Credit Transfer System, DOI: 10.1109/SCCC49216.2019.8966411
  • PUBLICACIÓN, 2019, A multi-objective optimisation evolutionary approach for the Multidimensional Scaling Problem, DOI: 10.1109/SCCC49216.2019.8966433
  • PUBLICACIÓN, 2019, An Unsupervised Learning Approach for Automatically to Categorize Potential Suicide Messages in Social Media, DOI: 10.1109/SCCC49216.2019.8966443
  • PUBLICACIÓN, 2019, A Memetic Algorithm Based on an NSGA-II Scheme for Phylogenetic Tree Inference, DOI: 10.1109/TEVC.2018.2883888
  • PUBLICACIÓN, 2018, World’s best universities and personalized rankings, DOI: 10.1007/978-3-319-07124-4_60
  • PUBLICACIÓN, 2018, A multi-objective gene clustering algorithm guided by apriori biological knowledge with intensification and diversification strategies, DOI: 10.1186/s13040-018-0178-4
  • PUBLICACIÓN, 2018, Application of different multi-objective decision making techniques in the phylogenetic inference problem, DOI: 10.1109/SCCC.2017.8405145
  • PUBLICACIÓN, 2018, Tackling the bi-objective quadratic assignment problem by characterizing different memory strategies in a memetic algorithm, DOI: 10.1109/SCCC.2017.8405140
  • PUBLICACIÓN, 2018, Unsupervised Pattern Recognition for Geographical Clustering of Seismic Events Post MW 7.8 Ecuador Earthquake, DOI: 10.1109/SCCC.2018.8705248
  • PUBLICACIÓN, 2017, A bi-objective model for gene clustering combining expression data and external biological knowledge, DOI: 10.1109/CLEI.2016.7833327
  • PUBLICACIÓN, 2017, An evolutionary multi-agent algorithm to explore the high degree of selectivity in three-dimensional protein structures, DOI: 10.1109/CEC.2017.7969431
  • PUBLICACIÓN, 2017, NIAS-Server: Neighbors Influence of Amino acids and Secondary Structures in Proteins, DOI:  10.1089/cmb.2016.0074
  • PUBLICACIÓN, 2017, Using local search strategies to improve the performance of NSGA-II for the Multi-Criteria Minimum Spanning Tree problem, DOI: 10.1109/CEC.2017.7969432
  • PUBLICACIÓN, 2017,  Using the QAP grid visualization approach for biomarker identification of cell-specific transcriptomic signatures, DOI: 10.1007/978-1-4939-6613-4_16
  • FONDECYT, 2012, DESIGNING AND CONSTRUCTING A SCALABLE PIPELINE OF GRAPH-BASED METHODS FOR THE ANALYSIS OF GENE EXPRESSION DATA, DOI: N.C.
  • DICYT, 2016, ROBUST METAHEURISTIC ALGORITHMS TO TACKLE MULTI-OBJECTIVE OPTIMIZATION PROBLEMS IN BIOINFORMATICS, DOI: N.C.

 

 

 

 

Especialistas USACH © 2020
Todos los derechos reservados

Instagram Facebook Twitter Youtube Linkedin

BD

© USACH 2024, Todos los derechos reservados.

Facebook Twitter Youtube Linkedin Instagram