Dr Philipp Otto
- Reader in Statistics and Data Analytics (Statistics)
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
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.
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
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)
- 2021: Environmetrics
- 2020: AStA Advances in Statistical Analysis
- 2020: AStA Wirtschafts- und Sozialstatistisches Archiv
Professional & learned societies
- 2013: Treasurer, German Statistical Society