Professor Philipp Otto

Professor of Statistics and Data Science (Statistics)

Biography

Philipp Otto is currently a Professor of Statistics and Data Science, after being a Reader in Statistics and Data Analytics at the University of Glasgow for one year. Until 2023, he 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: 2025 | 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015

Number of items: 48.

2025

Colombo, Pietro, Mattera, Raffaele and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2025) Simple yet effective: a comparative study of statistical models for yearly hurricane forecasting. Environmetrics, 36(3), e70009. (doi: 10.1002/env.70009)

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2025) Discussion on “Assessing predictability of environmental time series with statistical and machine learning models” by Bonas et al. Environmetrics, 36(2), e2898. (doi: 10.1002/env.2898)

2024

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682, Fasso, Alessandro and Maranzano, Paolo (2024) A review of regularised estimation methods and cross-validation in spatiotemporal statistics. Statistics Surveys, 18, pp. 299-340. (doi: 10.1214/24-SS150)

Belbe, Ștefana, Moldovan, Darie, Andrieș, Alin Marius, Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Mare, Codruța (2024) Evaluation of the space-time effects of Covid-19 on household loans and savings in Romania - A spatial panel data approach at county level. Emerging Markets Review, 63, 101209. (doi: 10.1016/j.ememar.2024.101209)

Dorau, Kristof, Rückamp, Daniel, Weber, Christian, Scheeder, Georg, Reßing, Ronja, Peth, Stephan, Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682, Altmann, Korinna, Fries, Elke and Hoppe, Martin (2024) Characterization and spatial distribution of mesoplastics in an arable soil. European Journal of Soil Science, 75(6), e70016. (doi: 10.1111/ejss.70016)

Knoth, Sven, Okhrin, Yarema and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (Eds.) (2024) Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science: Essays in Honour of Wolfgang Schmid. Springer: Cham. ISBN 9783031691102 (In Press)

Mattera, Raffaele and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2024) Network log-ARCH models for forecasting stock market volatility. International Journal of Forecasting, 40(4), pp. 1539-1555. (doi: 10.1016/j.ijforecast.2024.01.002)

Khoo, Tzung Hsuen, Pathmanathan, Dharini, Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Dabo‐Niang, Sophie (2024) A Markov‐switching spatio‐temporal ARCH model. Stat, 13(3), e713. (doi: 10.1002/sta4.713)

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682, Doğan, Osman, Taspinar, Suleyman, Schmid, Wolfgang and Bera, Anil (2024) Spatial and spatiotemporal volatility models: a review. Journal of Economic Surveys, (doi: 10.1111/joes.12643) (Early Online Publication)

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2024) A multivariate spatial and spatiotemporal ARCH model. Spatial Statistics, 60, 100823. (doi: 10.1016/j.spasta.2024.100823)

Mohammadi, Reza, Taleai, Mohammad, Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Sester, Monika (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682, Doğan, Osman and Taşpınar, Süleyman (2024) Dynamic spatiotemporal ARCH models. Spatial Economic Analysis, 19(2), pp. 250-271. (doi: 10.1080/17421772.2023.2254817)

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682, Fusta Moro, Alessandro, Rodeschini, Jacopo, Shaboviq, Qendrim, Ignaccolo, Rosaria, Golini, Natalia, Cameletti, Michela, Maranzano, Paolo, Finazzi, Francesco and Fassò, Alessandro (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, Anna, Mozharovskyi, Pavlo and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2024) Statistical process monitoring of artificial neural networks. Technometrics, 66(1), pp. 104-117. (doi: 10.1080/00401706.2023.2239886)

Fülle, Markus J. and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682, Doğan, Osman and Taşpınar, Süleyman (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Steinert, Rick (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, Alessandro, Rodeschini, Jacopo, Fusta Moro, Alessandro, Shaboviq, Qendrim, Maranzano, Paolo, Cameletti, Michela, Finazzi, Francesco, Golini, Natalia, Ignaccolo, Rosaria and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Franz and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2023) Solar self-sufficient households as a driving factor for sustainability transformation. Sustainability, 15(3), 2734. (doi: 10.3390/su15032734)

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Otto, Philip (2023) What’s in a name? Significance, 20(1), pp. 34-37. (doi: 10.1093/jrssig/qmad010)

2022

Garthoff, Robert and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Schmid, Wolfgang (2022) A general framework for spatial GARCH models. Statistical Papers, (doi: 10.1007/s00362-022-01357-1) (Early Online Publication)

Otto, Philipp and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2022) Impact of academic authorship characteristics on article citations. Revstat Statistical Journal, 20(4), pp. 427-447. (doi: 10.57805/revstat.v20i4.382)

Harke, Franz H., Merk, Miryam S. and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2022) Estimation of Asymmetric Spatial Autoregressive Dependence on Irregular Lattices. Symmetry, 14(7), 1474. (doi: 10.3390/sym14071474)

Piter, Andreas, Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Alkhatib, Hamza (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, Alessandro, Maranzano, Paolo and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Miryam S. and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Anna, Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Peters, Torben (2022) Statistical learning for change point and anomaly detection in graphs. In: Steland, Ansgar and Tsui, Kwok-Leung (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682, Piter, Andreas and Gijsman, Rik (2021) Statistical analysis of beach profiles – A spatiotemporal functional approach. Coastal Engineering, 170, 103999. (doi: 10.1016/j.coastaleng.2021.103999)

Malinovskaya, Anna and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2021) Online network monitoring. Statistical Methods and Applications, 30, pp. 1337-1364. (doi: 10.1007/s10260-021-00589-z)

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682, Schmid, Wolfgang and Garthoff, Robert (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Anna, Merk, Miryam S. and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2021) Spatial statistics, or how to extract knowledge from data. In: Werner, Martin and Chiang, Yao-Yi (eds.) Handbook of Big Geospatial Data. Springer, pp. 399-426. ISBN 9783030554620 (doi: 10.1007/978-3-030-55462-0_15)

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2021) Parallelized monitoring of dependent spatiotemporal processes. In: Knoth, Sven and Schmid, Wolfgang (eds.) Frontiers in Statistical Quality Control 13. Springer, pp. 165-183. ISBN 9783030678562 (doi: 10.1007/978-3-030-67856-2_10)

2020

Merk, Miryam S. and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2019) spGARCH: An R-package for spatial and spatiotemporal ARCH and GARCH models. R Journal, 11(2), pp. 401-420.

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Schmid, Wolfgang (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, Robert and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Lange, Anna-Liesa (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, Anna-Liesa and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Schmid, Wolfgang (2016) Spatiotemporal analysis of German real-estate prices. Annals of Regional Science, 60, pp. 41-72. (doi: 10.1007/s00168-016-0789-y)

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Schmid, Wolfgang (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, Robert and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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, Robert and Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (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 Sat Jun 14 07:20:29 2025 BST.

Jump to: Articles | Books | Book Sections | Edited Books | Conference Proceedings

Number of items: 48.

Articles

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2024) A multivariate spatial and spatiotemporal ARCH model. Spatial Statistics, 60, 100823. (doi: 10.1016/j.spasta.2024.100823)

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 and Otto, Philip (2023) What’s in a name? Significance, 20(1), pp. 34-37. (doi: 10.1093/jrssig/qmad010)

Otto, Philipp ORCID: https://orcid.org/0000-0002-9796-6682 (2019) spGARCH: An R-package for spatial and spatiotemporal ARCH and GARCH models. R Journal, 11(2), pp. 401-420.

Books

Book Sections

Edited Books

Conference Proceedings

This list was generated on Sat Jun 14 07:20:29 2025 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

Meli Chrisko, Ariane Nidelle
Spatiotemporal GARCH Models with Asymmetric Volatility Spillovers
Nyabuto, Elkanah Magembe
Spatiotemporal Uncertainty Modelling

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

Philipp Otto

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