Small Area Estimation
Developing statistical methods for reliable estimates in small geographic areas or subpopulations with limited sample sizes.
The pace of AI fascinates me. The rigor it demands and the people it affects keep me grounded.
A statistician who builds with AI every day, and who cares as much about how teams adapt to these tools as about what the tools can do.
Research interests
Spatial Data Analysis
Analyzing geographically referenced data, including density estimation from aggregated spatial information and choropleth mapping.
Kernel Density Estimation
Extending measurement error models for density estimation when precise geocoordinates are unavailable due to privacy constraints.
Random Forests for Ordinal Data
Applying and adapting machine learning methods, particularly ordinal random forests, for analyzing categorical and linguistic data.
Education
2021 – 2026Bamberg, Germany
Doctorate in Statistics
University of Bamberg
Cumulative dissertation: "Reversing the Coarse: Statistical Methods for Recovering Structure from Aggregated, Sparse, and Discretized Data".
2019 – 2021Bamberg, Germany
M.Sc. in European Economic Studies
University of Bamberg
Advanced studies in economics with focus on quantitative methods and European economic policy.
2015 – 2019Regensburg, Germany
B.A. in Business Administration
OTH Regensburg
Foundation in business administration and quantitative analysis.
Experience
08.2021 – 03.2026 Full-time · Bamberg, Germany
Scientific Research Associate
University of Bamberg
- Built end-to-end data pipelines in R for large-scale statistical analyses (survey, census, and geospatial data)
- Extended an open-source R package (fabOF) with partial dependence plots for explainable ML
- Designed and automated a reproducible analysis pipeline for district-level mobility estimation across 400 German districts
- Delivered an applied data analysis project for the City of Jena (urban safety perception study)
- Designed and taught a graduate-level Python data science course (4 semesters)
- Represented academic staff interests in institute-level governance and decision-making bodies
- Served on the examination board for M.Sc. Survey Statistics and Data Analysis
01.2020 – 06.2021 Part-time · Bamberg, Germany
Student Research Assistant
University of Bamberg — Chair of Statistics and Econometrics
- Contributed to a research project on demographic development
05.2020 – 07.2020 Part-time · Bamberg, Germany
Student Research Assistant
University of Bamberg — Chair of Economic Policy
- Developed course materials for an applied econometrics lecture
09.2018 – 02.2019 Part-time · Neutraubling, Germany
Working Student — Strategic Projects
Krones AG
- Designed and conducted a survey to identify structural issues in after-sales
- Proposed an organizational redesign to improve cross-regional coordination
- Presented findings and recommendations to senior leadership
09.2016 – 02.2017 Internship · Regensburg, Germany
Innovation Management Intern
Continental AG
- Evaluated ideas from a corporate ideation platform for innovation decision-making
- Conducted technology and patent research for senior decision-makers
- Analyzed gamification methods and recommended platform enhancements
- Processed and visualized innovation KPIs for corporate reporting
Skills
Statistical Methods
Regression & GLMsMixed-Effects ModelsBayesian MethodsLASSO / RegularizationSpatial StatisticsSurvey MethodologySmall Area EstimationKernel Density EstimationMonte Carlo SimulationExperimental Design
Programming & Tools
RPythonSQLLaTeXTypstGit / GitHubQuartoBashHigh-Performance Computing (Condor)
Machine Learning
Random ForestsNeural NetworksEnsemble MethodsOrdinal ClassificationPredictive AnalyticsCross-ValidationFeature EngineeringModel Validation
LLM & AI Engineering
Generative AIPrompt EngineeringRAGMCPAgentic AIAI Strategy & Transformation
Projects
Arboretum Beta
AI-curated research digests from OpenAlex and arXiv
A cross-platform desktop app that turns plain-language research interests into weekly Markdown newsletters, delivered to disk or email.
Arboretum sits between passive RSS feeds and active Scholar alerts. You describe what you care about once; the app converts the description into academic search keywords, queries OpenAlex and arXiv for recent papers, asks an LLM (Claude, Gemini, or a local Ollama model) to pick and summarise the ten most relevant, and writes the result as a Markdown newsletter. It can also run a multi-query conflict scan against your own research profile, flagging recent papers that overlap with your work.
Built with Rust, Tauri v2, React, TypeScript
Zotero MCP Server Released
Expose a local Zotero library to AI assistants via the Model Context Protocol
A maintained fork of an open-source MCP server that lets Claude, Cursor, and other MCP clients search, cite, and export from your personal Zotero library — including full-text PDF extraction.
Out of the box this server gives AI assistants tool calls for searching items, getting citations and bibliographies, exporting BibTeX files, adding new entries, browsing collections, and pulling full text from PDFs via the local Zotero API. My fork adds the export-BibTeX-to-disk tool, fixes intermittent partial exports, repairs add/update/delete operations against the live API, and rebuilds the PDF-extraction progress reporting around a non-blocking text UI so it works on headless boxes too.
Built with Python, MCP Python SDK, PyZotero
Publications
2025Submitted
2025Submitted
2026Submitted
Estimating Disaggregated Mobility Indicators using Area-Level Models on Survey Data
Let’s work together
Thinking about how AI changes the way your team works with data, or looking for someone who keeps the statistics honest along the way? I’m always glad to talk.