Philipp Otto

Philipp Otto is a Professor of Statistics and Data Science at the University of Glasgow. Previously, he was a Reader in Statistics and Data Analytics (2023–2024) and held a Junior Professorship in Big Geospatial Data at Leibniz University Hannover (2018–2023). He earned his PhD in Statistics (summa cum laude) from European University Viadrina in 2016 and a B.Sc. in International Economics, with study visits to Saint Petersburg State University. His research focuses on spatial and spatiotemporal statistics, environmetrics, network modeling, and machine learning applications.

Education:

• PhD in Statistics (2016), European University Viadrina, Frankfurt (Oder)
• B.Sc. in International Economics (with study visits to Saint Petersburg)

Research Interests:

Philipp’s work centers on spatial statistics, spatiotemporal volatility modeling, environmental data analysis, and network processes. He develops statistical methods for geo-referenced and network data, with applications in climatology, finance, and environmental risk assessment. His contributions include advancements in GARCH models, spatiotemporal clustering detection, and statistical process monitoring for AI systems.

Grants & Projects:

He has secured €1,038,847 in research grants, leading projects on historical map time series analysis, agricultural air quality impacts, and high-dimensional spatial dependence structures. Industry collaborations include survival analysis for building information models.

Awards:

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

Teaching:

He teaches statistics and data science across disciplines, including economics, engineering, and mathematics, at both undergraduate and postgraduate levels.

Professional Activities:

• Editorial Boards: Environmetrics (2021), AStA Advances in Statistical Analysis (2020)
• Member of German Statistical Society (Treasurer, 2013)