Gómez Losada, Álvaro
Imagen
Categoria: Investigador/a Área de conocimiento: Estadística e Investigación Operativa Departamento: Métodos Cuantitativos
FORMACIÓN
    • Doctor en Estadística e Investigación Operativa, Universidad de Sevilla, 2016.
    • Diploma de Estudios Avanzados Universidad de Sevilla
    • Máster Universitario en Estadística Aplicada Universidad de Granada
    • Licenciado en Ciencias (Biológicas) Universidad de Córdoba
    • Licenciado en Ciencias y Técnicas Estadísticas Universidad de Sevilla
EXPERIENCIA DOCENTE

El profesor/a ha impartido las siguientes asignaturas en los últimos años:

    • Bioestadística
    • Estadística
    • Estadística Empresarial I
    • Estadística y Combinatoria
    • Probabilidad y Estadística II
ACTIVIDAD INVESTIGADORA
Publicaciones
Artículos
  • Air quality assessment during the low emission zone implementation in Madrid (Spain)
    GÓMEZ LOSADA, ALVARO, Pires J.C.M. , 2024, Urban Clim.
    10.1016/j.uclim.2024.101995
  • Risk Assessment and Source Apportionment of Metals on Atmospheric Particulate Matter in a Suburban Background Area of Gran Canaria (Spain)
    Martín-Cruz Y. , GÓMEZ LOSADA, ALVARO , 2023, Int. J. Environ. Res. Public Health
    10.3390/ijerph20105763
  • Automatic Eligibility of Sellers in an Online Marketplace: A Case Study of Amazon Algorithm
    GÓMEZ LOSADA, ALVARO, Asencio-Cortes, Gualberto , Duch-Brown, Nestor , 2022, Information
    10.3390/info13020044
  • Empirical ozone isopleths at urban and suburban sites through evolutionary procedure-based models
    Santos, Francisca M. , GÓMEZ LOSADA, ALVARO, Pires, Jose C. M. , 2021, J. Hazard. Mater.
    10.1016/j.jhazmat.2021.126386
  • Estimation of Particulate Matter Contributions from Desert Outbreaks in Mediterranean Countries (2015-2018) Using the Time Series Clustering Method
    GÓMEZ LOSADA, ALVARO, Pires, Jose C. M. , 2021, Atmosphere
    10.3390/atmos12010005
  • Characterization of background particulate matter concentrations using the combination of two clustering techniques in zones with heterogeneous emission sources
    Martin-Cruz, Yumara , Vera-Castellano, Antonio , GÓMEZ LOSADA, ALVARO , 2020, Atmos. Environ.
    10.1016/j.atmosenv.2020.117832
  • Estimation of background PM2.5 concentrations for an air-polluted environment
    Wang, Sheng-Hsiang , Hung, Ruo-Ya , Lin, Neng-Huei , GÓMEZ LOSADA, ALVARO, Pires, Jose C. M. , Shimada, Kojiro , Hatakeyama, Shiro , Takami, Akinori , 2020, Atmos. Res.
    10.1016/j.atmosres.2019.104636
  • Email Based Institutional Network Analysis: Applications and Risks
    Christidis, Panayotis , GÓMEZ LOSADA, ALVARO , 2019, Soc. Sci.
    10.3390/socsci8110306
  • A data science approach for spatiotemporal modelling of low and resident air pollution in Madrid (Spain): Implications for epidemiological studies
    GÓMEZ LOSADA, ALVARO, Santos, Francisca M. , Gibert, Karina , Pires, Jose C. M. , 2019, Comput. Environ. Urban Syst.
    10.1016/j.compenvurbsys.2018.12.005
  • Impact of the implementation of Lisbon low emission zone on air quality
    Santos, Francisca M. , GÓMEZ LOSADA, ALVARO, Pires, Jose C. M. , 2019, J. Hazard. Mater.
    10.1016/j.jhazmat.2018.11.061
  • Forecasting ozone threshold exceedances in urban background areas using supervised classification and easy-access information
    GÓMEZ LOSADA, ALVARO , 2018, Atmos. Pollut. Res.
    10.1016/j.apr.2018.04.002
  • Modelling background air pollution exposure in urban environments: Implications for epidemiological research
    GÓMEZ LOSADA, ALVARO, Pires, Jose Carlos M. , Pino-Mejias, Rafael , 2018, Environ. Modell. Softw.
    10.1016/j.envsoft.2018.02.011
  • Characterization of background air pollution exposure in urban environments using a metric based on Hidden Markov Models
    GÓMEZ LOSADA, ALVARO, Pires, Jose Carlos M. , Pino-Mejias, Rafael , 2016, Atmos. Environ.
    10.1016/j.atmosenv.2015.12.046
  • Time series clustering for estimating particulate matter contributions and its use in quantifying impacts from deserts
    GÓMEZ LOSADA, ALVARO, Pires, Jose Carlos M. , Pino-Mejias, Rafael , 2015, Atmos. Environ.
    10.1016/j.atmosenv.2015.07.027
  • Finite mixture models to characterize and refine air quality monitoring networks
    GÓMEZ LOSADA, ALVARO, Lozano-Garcia, Antonio , Pino-Mejias, Rafael , Contreras-Gonzalez, Juan , 2014, Sci. Total Environ.
    10.1016/j.scitotenv.2014.03.091
Congresos
  • Competing for Amazon\'s Buy Box: A Machine-Learning Approach
    Proceedings Paper - 22nd International Conference on Business Information Systems (BIS)
    2019
  • Time Series Forecasting by Recommendation: An Empirical Analysis on Amazon Marketplace
    Proceedings Paper - 22nd International Conference on Business Information Systems (BIS)
    2019
  • Clustering Air Monitoring Stations According to Background and Ambient Pollution Using Hidden Markov Models and Multidimensional Scaling
    Proceedings Paper - 15th Conference of the International Federation of Classification Societies (IFCS)
    2017