Dr Philipp Otto

  • Reader in Statistics and Data Analytics (Statistics)

Biography

Philipp Otto is currently a Reader in Statistics and Data Analytics at the University of Glasgow and previously served as an Assistant Professor of Big Geospatial Data at Leibniz University Hannover, Germany (2018-2023). He was also a visiting full professor at the University of Göttingen for one year (2020-2021). Philipp earned his PhD in statistics in 2016 with distinction (summa cum laude) from the European University Viadrina, Frankfurt (Oder), Germany, in the so-called fast-track without an M.Sc. degree, a progression reserved for selected students with proven affinity and ability for research. His academic journey began with a B.Sc. in International Economics, with study visits to the State University Saint Petersburg, Russia.

For more details, visit my personal website: www.maths.gla.ac.uk/philipp.otto

Research interests

Philipp Otto is passionate about spatial and spatiotemporal statistics, environmetrics, network modelling, spatial econometrics, machine learning and artificial intelligence, big geospatial data, statistical process monitoring, and data science. His research involves exploring these areas to analyse complex spatial data, develop statistical models for geo-referenced and network data, and create innovative statistical and AI-driven tools for data quality control. Philipp's work addresses key questions in geospatial and data science, applying cutting-edge methods and technologies to advance knowledge in these fields.

Research groups

Publications

List by: Type | Date

Jump to: 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015
Number of items: 40.

2024

Otto, P. (2024) A multivariate spatial and spatiotemporal ARCH model. Spatial Statistics, 60, 100823. (doi: 10.1016/j.spasta.2024.100823)

Mohammadi, R., Taleai, M., Otto, P. and Sester, M. (2024) Analyzing urban crash incidents: an advanced endogenous approach using spatiotemporal weights matrix. Transactions in GIS, 28(2), pp. 368-410. (doi: 10.1111/tgis.13138)

Otto, P. , Fusta Moro, A., Rodeschini, J., Shaboviq, Q., Ignaccolo, R., Golini, N., Cameletti, M., Maranzano, P., Finazzi, F. and Fassò, A. (2024) Spatiotemporal modelling of PM2.5 concentrations in Lombardy (Italy): a comparative study. Environmental and Ecological Statistics, (doi: 10.1007/s10651-023-00589-0) (Early Online Publication)

Malinovskaya, A., Mozharovskyi, P. and Otto, P. (2024) Statistical process monitoring of artificial neural networks. Technometrics, 66(1), pp. 104-117. (doi: 10.1080/00401706.2023.2239886)

Mattera, R. and Otto, P. (2024) Network log-ARCH models for forecasting stock market volatility. International Journal of Forecasting, (doi: 10.1016/j.ijforecast.2024.01.002) (Early Online Publication)

Fülle, M. J. and Otto, P. (2024) Spatial GARCH models for unknown spatial locations – an application to financial stock returns. Spatial Economic Analysis, 19(1), pp. 92-105. (doi: 10.1080/17421772.2023.2237067)

2023

Otto, P. , Doğan, O. and Taşpınar, S. (2023) A dynamic spatiotemporal stochastic volatility model with an application to environmental risks. Econometrics and Statistics, (doi: 10.1016/j.ecosta.2023.11.002) (In Press)

Otto, P. , Doğan, O. and Taşpınar, S. (2023) Dynamic spatiotemporal ARCH models. Spatial Economic Analysis, (doi: 10.1080/17421772.2023.2254817) (Early Online Publication)

Otto, P. and Steinert, R. (2023) Estimation of the spatial weighting matrix for spatiotemporal data under the presence of structural breaks. Journal of Computational and Graphical Statistics, 32(2), pp. 696-711. (doi: 10.1080/10618600.2022.2107530)

Fassò, A., Rodeschini, J., Fusta Moro, A., Shaboviq, Q., Maranzano, P., Cameletti, M., Finazzi, F., Golini, N., Ignaccolo, R. and Otto, P. (2023) Agrimonia: a dataset on livestock, meteorology and air quality in the Lombardy region, Italy. Scientific Data, 10(1), 143. (doi: 10.1038/s41597-023-02034-0) (PMID:36934159) (PMCID:PMC10024000)

Harke, F. and Otto, P. (2023) Solar self-sufficient households as a driving factor for sustainability transformation. Sustainability, 15(3), 2734. (doi: 10.3390/su15032734)

Otto, P. and Otto, P. (2023) What’s in a name? Significance, 20(1), pp. 34-37. (doi: 10.1093/jrssig/qmad010)

2022

Garthoff, R. and Otto, P. (2022) Spatiotemporal procedures for the statistical surveillance of spatial autoregressive models with heavy tails. Communications in Statistics: Simulation and Computation, 51(10), pp. 5709-5737. (doi: 10.1080/03610918.2020.1779294)

Otto, P. and Schmid, W. (2022) A general framework for spatial GARCH models. Statistical Papers, (doi: 10.1007/s00362-022-01357-1) (Early Online Publication)

Otto, P. and Otto, P. (2022) Impact of academic authorship characteristics on article citations. Revstat Statistical Journal, 20(4), pp. 427-447. (doi: 10.57805/revstat.v20i4.382)

Harke, F. H., Merk, M. S. and Otto, P. (2022) Estimation of Asymmetric Spatial Autoregressive Dependence on Irregular Lattices. Symmetry, 14(7), 1474. (doi: 10.3390/sym14071474)

Piter, A., Otto, P. and Alkhatib, H. (2022) The Helsinki bike‐sharing system—Insights gained from a spatiotemporal functional model. Journal of the Royal Statistical Society: Series A (Statistics in Society), 185(3), pp. 1294-1318. (doi: 10.1111/rssa.12834)

Fassò, A., Maranzano, P. and Otto, P. (2022) Spatiotemporal variable selection and air quality impact assessment of COVID-19 lockdown. Spatial Statistics, 49, 100549. (doi: 10.1016/j.spasta.2021.100549)

Merk, M. S. and Otto, P. (2022) Estimation of the spatial weighting matrix for regular lattice data—An adaptive lasso approach with cross-sectional resampling. Environmetrics, 33(1), e2705. (doi: 10.1002/env.2705)

Malinovskaya, A., Otto, P. and Peters, T. (2022) Statistical learning for change point and anomaly detection in graphs. In: Steland, A. and Tsui, K.-L. (eds.) Artificial Intelligence, Big Data and Data Science in Statistics. Springer, pp. 85-109. ISBN 9783031071553 (doi: 10.1007/978-3-031-07155-3_4)

2021

Otto, P. , Piter, A. and Gijsman, R. (2021) Statistical analysis of beach profiles – A spatiotemporal functional approach. Coastal Engineering, 170, 103999. (doi: 10.1016/j.coastaleng.2021.103999)

Malinovskaya, A. and Otto, P. (2021) Online network monitoring. Statistical Methods and Applications, 30, pp. 1337-1364. (doi: 10.1007/s10260-021-00589-z)

Otto, P. , Schmid, W. and Garthoff, R. (2021) Stochastic properties of spatial and spatiotemporal ARCH models. Statistical Papers, 62(2), pp. 623-638. (doi: 10.1007/s00362-019-01106-x)

Merk, M.S. and Otto, P. (2021) Directional spatial autoregressive dependence in the conditional first- and second-order moments. Spatial Statistics, 41, 100490. (doi: 10.1016/j.spasta.2020.100490)

Antoniuk, A., Merk, M. S. and Otto, P. (2021) Spatial statistics, or how to extract knowledge from data. In: Werner, M. and Chiang, Y.-Y. (eds.) Handbook of Big Geospatial Data. Springer, pp. 399-426. ISBN 9783030554620 (doi: 10.1007/978-3-030-55462-0_15)

Otto, P. (2021) Parallelized monitoring of dependent spatiotemporal processes. In: Knoth, S. and Schmid, W. (eds.) Frontiers in Statistical Quality Control 13. Springer, pp. 165-183. ISBN 9783030678562 (doi: 10.1007/978-3-030-67856-2_10)

2020

Merk, M. S. and Otto, P. (2020) Estimation of anisotropic, time-varying spatial spillovers of fine particulate matter due to wind direction. Geographical Analysis, 52(2), pp. 254-277. (doi: 10.1111/gean.12205)

2019

Otto, P. (2019) spGARCH: An R-package for spatial and spatiotemporal ARCH and GARCH models. R Journal, 11(2), pp. 401-420.

Otto, P. (2019) Modeling Spatial Dependence in Local Risks and Uncertainties. In: 29th European Safety and Reliability Conference, ESREL 2019, Hannover, Germany, 22 September-26 September 2019, pp. 2685-2692. ISBN 9789811127243

Otto, P. (2019) Parallelized Monitoring of Dependent Spatiotemporal Processes. In: 13th International Workshop on Intelligent Statistical Quality Control, IWISQC 2019, Hong Kong, 12 - 14 August 2019, pp. 181-194.

2018

Otto, P. and Schmid, W. (2018) Discussion of “Statistical methods for network surveillance” by Daniel Jeske, Nathaniel Stevens, Alexander Tartakovsky, and James Wilson. Applied Stochastic Models in Business and Industry, 34(4), pp. 452-456. (doi: 10.1002/asmb.2360)

Garthoff, R. and Otto, P. (2018) Verfahren zur Überwachung räumlicher autoregressiver Prozesse mit externen Regressoren = Statistical surveillance of spatial autoregressive processes with exogenous regressors. AStA Wirtschafts- und Sozialstatistisches Archiv, 12(2), pp. 107-133. (doi: 10.1007/s11943-018-0224-1)

2017

Otto, P. (2017) A note on efficient simulation of multidimensional spatial autoregressive processes. Communications in Statistics: Simulation and Computation, 46(6), pp. 4547-4558. (doi: 10.1080/03610918.2015.1122050)

Otto, P. and Lange, A.-L. (2017) Arbeitsbuch der Angewandten Statistik: Mit Aufgaben zur Software R und detaillierten Lösungen. Springer Gabler: Berlin, Heidelberg. ISBN 9783662492116 (doi: 10.1007/978-3-662-49212-3)

2016

Lange, A.-L. and Otto, P. (2016) Bayes’sche Statistik in der Dienstleistungsforschung. AStA Wirtschafts- und Sozialstatistisches Archiv, 10(4), pp. 247-267. (doi: 10.1007/s11943-016-0189-x)

Otto, P. and Schmid, W. (2016) Spatiotemporal analysis of German real-estate prices. Annals of Regional Science, 60, pp. 41-72. (doi: 10.1007/s00168-016-0789-y)

Otto, P. (2016) Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models. Biometrical Journal, 58(5), pp. 1113-1137. (doi: 10.1002/bimj.201500148)

Otto, P. and Schmid, W. (2016) Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models. Biometrical Journal, 58(5), pp. 1113-1137. (doi: 10.1002/bimj.201500148)

Garthoff, R. and Otto, P. (2016) Control charts for multivariate spatial autoregressive models. AStA Advances in Statistical Analysis, 101, pp. 67-94. (doi: 10.1007/s10182-016-0276-x)

2015

Garthoff, R. and Otto, P. (2015) Simultaneous surveillance of means and covariances of spatial models. In: Steland, A., Rafajłowicz, E. and Szajowski, K. (eds.) Stochastic Models, Statistics and Their Applications. Series: Springer proceedings in mathematics and statistics (122). Springer: Cham, pp. 271-281. ISBN 9783319138800 (doi: 10.1007/978-3-319-13881-7_30)

This list was generated on Mon May 20 12:31:27 2024 BST.
Number of items: 40.

Articles

Otto, P. (2024) A multivariate spatial and spatiotemporal ARCH model. Spatial Statistics, 60, 100823. (doi: 10.1016/j.spasta.2024.100823)

Mohammadi, R., Taleai, M., Otto, P. and Sester, M. (2024) Analyzing urban crash incidents: an advanced endogenous approach using spatiotemporal weights matrix. Transactions in GIS, 28(2), pp. 368-410. (doi: 10.1111/tgis.13138)

Otto, P. , Fusta Moro, A., Rodeschini, J., Shaboviq, Q., Ignaccolo, R., Golini, N., Cameletti, M., Maranzano, P., Finazzi, F. and Fassò, A. (2024) Spatiotemporal modelling of PM2.5 concentrations in Lombardy (Italy): a comparative study. Environmental and Ecological Statistics, (doi: 10.1007/s10651-023-00589-0) (Early Online Publication)

Malinovskaya, A., Mozharovskyi, P. and Otto, P. (2024) Statistical process monitoring of artificial neural networks. Technometrics, 66(1), pp. 104-117. (doi: 10.1080/00401706.2023.2239886)

Mattera, R. and Otto, P. (2024) Network log-ARCH models for forecasting stock market volatility. International Journal of Forecasting, (doi: 10.1016/j.ijforecast.2024.01.002) (Early Online Publication)

Fülle, M. J. and Otto, P. (2024) Spatial GARCH models for unknown spatial locations – an application to financial stock returns. Spatial Economic Analysis, 19(1), pp. 92-105. (doi: 10.1080/17421772.2023.2237067)

Otto, P. , Doğan, O. and Taşpınar, S. (2023) A dynamic spatiotemporal stochastic volatility model with an application to environmental risks. Econometrics and Statistics, (doi: 10.1016/j.ecosta.2023.11.002) (In Press)

Otto, P. , Doğan, O. and Taşpınar, S. (2023) Dynamic spatiotemporal ARCH models. Spatial Economic Analysis, (doi: 10.1080/17421772.2023.2254817) (Early Online Publication)

Otto, P. and Steinert, R. (2023) Estimation of the spatial weighting matrix for spatiotemporal data under the presence of structural breaks. Journal of Computational and Graphical Statistics, 32(2), pp. 696-711. (doi: 10.1080/10618600.2022.2107530)

Fassò, A., Rodeschini, J., Fusta Moro, A., Shaboviq, Q., Maranzano, P., Cameletti, M., Finazzi, F., Golini, N., Ignaccolo, R. and Otto, P. (2023) Agrimonia: a dataset on livestock, meteorology and air quality in the Lombardy region, Italy. Scientific Data, 10(1), 143. (doi: 10.1038/s41597-023-02034-0) (PMID:36934159) (PMCID:PMC10024000)

Harke, F. and Otto, P. (2023) Solar self-sufficient households as a driving factor for sustainability transformation. Sustainability, 15(3), 2734. (doi: 10.3390/su15032734)

Otto, P. and Otto, P. (2023) What’s in a name? Significance, 20(1), pp. 34-37. (doi: 10.1093/jrssig/qmad010)

Garthoff, R. and Otto, P. (2022) Spatiotemporal procedures for the statistical surveillance of spatial autoregressive models with heavy tails. Communications in Statistics: Simulation and Computation, 51(10), pp. 5709-5737. (doi: 10.1080/03610918.2020.1779294)

Otto, P. and Schmid, W. (2022) A general framework for spatial GARCH models. Statistical Papers, (doi: 10.1007/s00362-022-01357-1) (Early Online Publication)

Otto, P. and Otto, P. (2022) Impact of academic authorship characteristics on article citations. Revstat Statistical Journal, 20(4), pp. 427-447. (doi: 10.57805/revstat.v20i4.382)

Harke, F. H., Merk, M. S. and Otto, P. (2022) Estimation of Asymmetric Spatial Autoregressive Dependence on Irregular Lattices. Symmetry, 14(7), 1474. (doi: 10.3390/sym14071474)

Piter, A., Otto, P. and Alkhatib, H. (2022) The Helsinki bike‐sharing system—Insights gained from a spatiotemporal functional model. Journal of the Royal Statistical Society: Series A (Statistics in Society), 185(3), pp. 1294-1318. (doi: 10.1111/rssa.12834)

Fassò, A., Maranzano, P. and Otto, P. (2022) Spatiotemporal variable selection and air quality impact assessment of COVID-19 lockdown. Spatial Statistics, 49, 100549. (doi: 10.1016/j.spasta.2021.100549)

Merk, M. S. and Otto, P. (2022) Estimation of the spatial weighting matrix for regular lattice data—An adaptive lasso approach with cross-sectional resampling. Environmetrics, 33(1), e2705. (doi: 10.1002/env.2705)

Otto, P. , Piter, A. and Gijsman, R. (2021) Statistical analysis of beach profiles – A spatiotemporal functional approach. Coastal Engineering, 170, 103999. (doi: 10.1016/j.coastaleng.2021.103999)

Malinovskaya, A. and Otto, P. (2021) Online network monitoring. Statistical Methods and Applications, 30, pp. 1337-1364. (doi: 10.1007/s10260-021-00589-z)

Otto, P. , Schmid, W. and Garthoff, R. (2021) Stochastic properties of spatial and spatiotemporal ARCH models. Statistical Papers, 62(2), pp. 623-638. (doi: 10.1007/s00362-019-01106-x)

Merk, M.S. and Otto, P. (2021) Directional spatial autoregressive dependence in the conditional first- and second-order moments. Spatial Statistics, 41, 100490. (doi: 10.1016/j.spasta.2020.100490)

Merk, M. S. and Otto, P. (2020) Estimation of anisotropic, time-varying spatial spillovers of fine particulate matter due to wind direction. Geographical Analysis, 52(2), pp. 254-277. (doi: 10.1111/gean.12205)

Otto, P. (2019) spGARCH: An R-package for spatial and spatiotemporal ARCH and GARCH models. R Journal, 11(2), pp. 401-420.

Otto, P. and Schmid, W. (2018) Discussion of “Statistical methods for network surveillance” by Daniel Jeske, Nathaniel Stevens, Alexander Tartakovsky, and James Wilson. Applied Stochastic Models in Business and Industry, 34(4), pp. 452-456. (doi: 10.1002/asmb.2360)

Garthoff, R. and Otto, P. (2018) Verfahren zur Überwachung räumlicher autoregressiver Prozesse mit externen Regressoren = Statistical surveillance of spatial autoregressive processes with exogenous regressors. AStA Wirtschafts- und Sozialstatistisches Archiv, 12(2), pp. 107-133. (doi: 10.1007/s11943-018-0224-1)

Otto, P. (2017) A note on efficient simulation of multidimensional spatial autoregressive processes. Communications in Statistics: Simulation and Computation, 46(6), pp. 4547-4558. (doi: 10.1080/03610918.2015.1122050)

Lange, A.-L. and Otto, P. (2016) Bayes’sche Statistik in der Dienstleistungsforschung. AStA Wirtschafts- und Sozialstatistisches Archiv, 10(4), pp. 247-267. (doi: 10.1007/s11943-016-0189-x)

Otto, P. and Schmid, W. (2016) Spatiotemporal analysis of German real-estate prices. Annals of Regional Science, 60, pp. 41-72. (doi: 10.1007/s00168-016-0789-y)

Otto, P. (2016) Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models. Biometrical Journal, 58(5), pp. 1113-1137. (doi: 10.1002/bimj.201500148)

Otto, P. and Schmid, W. (2016) Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models. Biometrical Journal, 58(5), pp. 1113-1137. (doi: 10.1002/bimj.201500148)

Garthoff, R. and Otto, P. (2016) Control charts for multivariate spatial autoregressive models. AStA Advances in Statistical Analysis, 101, pp. 67-94. (doi: 10.1007/s10182-016-0276-x)

Books

Otto, P. and Lange, A.-L. (2017) Arbeitsbuch der Angewandten Statistik: Mit Aufgaben zur Software R und detaillierten Lösungen. Springer Gabler: Berlin, Heidelberg. ISBN 9783662492116 (doi: 10.1007/978-3-662-49212-3)

Book Sections

Malinovskaya, A., Otto, P. and Peters, T. (2022) Statistical learning for change point and anomaly detection in graphs. In: Steland, A. and Tsui, K.-L. (eds.) Artificial Intelligence, Big Data and Data Science in Statistics. Springer, pp. 85-109. ISBN 9783031071553 (doi: 10.1007/978-3-031-07155-3_4)

Antoniuk, A., Merk, M. S. and Otto, P. (2021) Spatial statistics, or how to extract knowledge from data. In: Werner, M. and Chiang, Y.-Y. (eds.) Handbook of Big Geospatial Data. Springer, pp. 399-426. ISBN 9783030554620 (doi: 10.1007/978-3-030-55462-0_15)

Otto, P. (2021) Parallelized monitoring of dependent spatiotemporal processes. In: Knoth, S. and Schmid, W. (eds.) Frontiers in Statistical Quality Control 13. Springer, pp. 165-183. ISBN 9783030678562 (doi: 10.1007/978-3-030-67856-2_10)

Garthoff, R. and Otto, P. (2015) Simultaneous surveillance of means and covariances of spatial models. In: Steland, A., Rafajłowicz, E. and Szajowski, K. (eds.) Stochastic Models, Statistics and Their Applications. Series: Springer proceedings in mathematics and statistics (122). Springer: Cham, pp. 271-281. ISBN 9783319138800 (doi: 10.1007/978-3-319-13881-7_30)

Conference Proceedings

Otto, P. (2019) Modeling Spatial Dependence in Local Risks and Uncertainties. In: 29th European Safety and Reliability Conference, ESREL 2019, Hannover, Germany, 22 September-26 September 2019, pp. 2685-2692. ISBN 9789811127243

Otto, P. (2019) Parallelized Monitoring of Dependent Spatiotemporal Processes. In: 13th International Workshop on Intelligent Statistical Quality Control, IWISQC 2019, Hong Kong, 12 - 14 August 2019, pp. 181-194.

This list was generated on Mon May 20 12:31:27 2024 BST.

Grants

I received research grants amounting to 1,038,847 euros (counting my own share only). My main/recent research projects dealt with:

- Time series analysis of historical maps,
- Statistical estimation of high-dimensional, spatial dependence structures using machine learning methods,
- Agricultural impact on air quality,
- Spatial and spatiotemporal GARCH models,
- Detection of spatiotemporal clusters.

Furthermore, I successfully collaborated on industry-funded projects, e.g., on survival analysis for building information models.

More information about my current projects can be found on my website: https://philot789.github.io/projects.html

 

Supervision

Teaching

Philipp Otto has a wide-ranging teaching background, imparting knowledge in statistics and data science across various disciplines, including economics, geodesy/geoinformatics, engineering, mechatronics, computer science, and mathematics/statistics. He has engaged with students at different educational levels, spanning undergraduates, post-graduates, and Ph.D. candidates. Philipp's teaching experience encompasses various formats, including lectures, seminars, and hands-on labs and tutorials.

Professional activities & recognition

Prizes, awards & distinctions

  • 2017: Fellowship to attend the Lindau Nobel Laureate Meeting (6th Lindau Nobel Laureate Meeting on Economic Sciences)
  • 2017: Best Presentation Award (Data Science, Statistics and Visualisation)

Editorial boards

  • 2021: Environmetrics
  • 2020: AStA Advances in Statistical Analysis
  • 2020: AStA Wirtschafts- und Sozialstatistisches Archiv

Professional & learned societies

  • 2013: Treasurer, German Statistical Society