Published Articles, Conference Contributions and Biography


Journal Articles

Automated real estate valuation with machine learning models using property descriptions
Baur K, Rosenfelder M, Lutz B
2022 Expert Systems with Applications, Band: forthcoming

Predicting Residential Electricity Consumption Using Aerial and Street View Images
Rosenfelder M, Wussow M, Gust G, Cremades R, Neumann D
2021 Applied Energy, volume: 301, page: 117407

Conference papers

Decision Support for Real Estate Investors: Improving Real Estate Valuation with 3D City Models and Points of Interest
Rosenfelder M, Gust G, Neumann D
2019 Proceedings of the 14. Internationale Tagung Wirtschaftsinformatik, Siegen, Germany


Data-driven tools for urban transformations towards climate-resilience and sustainability: State-of-the-art and further needs
Cheval S, Hewitt R, Rosenfelder M, Cremades R
2022 Reinventing the City

Improving Urban Analytics Using 3D Geometries and Graph Convolutional Neural Networks: Evidence from Real Estate Valuation
Rosenfelder M, Gust G, Neumann D
2020 Winter Conference on Business Analytics, Snowbird, USA

Complex Systems Based Integrated Assessment of Droughts, Floods, Heat Comfort and GHG Emissions in Cities under Climate Change
Cremades R, Bahri M, Rosenfelder M, Sommer P S
2019 Conference on Complex Systems 2019, 30.09.2019 - 4.10.2019

Leveraging the Third Dimension: Opportunities and Guidelines for 3D Analytics
Gust G, Brandt T, Koppius O, Feuerriegel S, Rosenfelder M, Kaulich A, Neumann D
2019 Winter Conference on Business Analytics (WCBA 2019), Snowbird, Utah, March 07-09, 2019


01/2018 - 04/2022

  • PhD Candidate at the Chair of Information Systems, Albert-Ludwigs-Universität Freiburg
  • Dissertation: “Urban Climate Change Mitigation Strategies with Machine Learning and 3D Data: Theory, Application, Economic Assessment”

01/2020 - 02/2020

  • Research stay at the National Institute for Environmental Studies in Tsukuba, Japan

10/2015 - 05/2018

  • Master of Science in Economics, Albert-Ludwigs-Universität Freiburg
  • Thesis: “Rising High: Improving Real Estate Valuation with 3D City Models and Spatial Analytics”

10/2012 - 10/2015

  • Bachelor of Science in Economics, Albert-Ludwigs Universität Freiburg
  • Thesis: “Geo-spatial analysis of different car types in free-floating carsharing”

Additional Responsibilies at University of Freiburg

  • Management of IT support team for the Faculty of Economic Sciences

Prizes and Awards

  • Outstanding Master Thesis Award, University of Freiburg & Deutsche Immobilien-Akademie der Universität Freiburg

Supervised Thesis

  • Deep Learning in Real Estate: Using Convolutional Neural Networks to improve Real Estate Valuations
  • Machine Learning for Predictive Policing: Spatio-temporal Data Analysis of Criminal Hotspots
  • Creating knowledge by mining multi-source big data in transport. Case study in Thessaloniki
  • Creating an Edge: Predicting Stock Prices with Sentiment Analysis
  • Maschinelles Lernen: Probabilistische Methoden in der wirtschaftlichen Anwendung
  • Applied Machine Learning in Economics: Predicting Real Estate Prices in Munich
  • Spatio-temporal Modeling: Analyzing Street Crime in Detroit
  • Failed Cities: Spatial Analysis of Street Crime in Detroit
  • Data Mining: Hyperparameter Optimization for Real Estate Prediction Models
  • What determines effective political communication? An empirical analysis of language patterns on Twitter
  • Realizing the Power of Aerial Image Data through Deep Learning: A Real Estate Case Study
  • Optimizing Bug Classifications with Bidirectional Encoder Representations from Transformers
  • Machine Learning in Real Estate: Accurate Rent Price Prediction with Natural Language Processing and Gradient Boosting
  • Applied Machine Learning: Improving Real Estate Price Predictions with Natural Language Processing and Bayesian Optimization
  • Semi-Supervised Deep Learning for Real Estate Price Predictions using Image Segmentation and Convolutional Neural Networks
  • Understanding the Power of Political Communication through Machine Learning: An in-depth Sentiment Analysis of Twitter Messages of German Politicians
  • Learning from Failure: Econometric Insights into Kickstarter Crowdfunding Campaigns
  • Multi-objective Re-Ranking of Recommendations: A Machine Learning Approach
  • Understanding the Potential Influence of Socio-Demographic Data on Renewable Energy Installations in Germany through Statistical Learning
  • Climate Change Mitigation: Prediction of Energy Consumption of Buildings with Ensemble Machine Learning
  • Climate Change and AI: Prediction of Building Energy Consumption with Artificial Neural Networks
  • Real Estate Valuation and AI: Prediction of Housing Prices with Deep Neural Networks and Gradient Boosting Machines
  • Building Energy Consumption Research with Machine Learning: Analysis of Residential Housing in Florida
  • Decomposing Housing Prices in New York with Advanced Machine Learning
  • Thermal Comfort Research with Machine Learning: A Literature Review
  • What determines a valuable player? A machine learning analysis of soccer transfer data
  • What determines a MotoGP Winner? An Application of Explainable AI for Motorsport Data Analysis


Winter semester 2021/2022

  • Exercise: Optimization and Simulation

Summer semester 2021

  • Exercise: Business Intelligence

Winter semester 2020/21

  • Exercise: Optimization and Simulation

Summer semester 2020

  • Seminar: Introduction to Programming: Python Programming through practical Examples

Winter semester 2019/2020

  • Seminar: Introduction to Programming: Python Programming through practical Examples

Summer semester 2019

  • Seminar: Introduction to Programming: Python Programming through practical Examples
  • Workshop for PHDs: Web-scraping in Python
  • Lecture: Data Science (Hochschule Fresenius)

Winter semester 2018/2019

  • Exercise: Optimization and Simulation
  • Seminar: Data Analytics in R and Python

Summer semester 2018

  • Exercise: Business Intelligence
  • Seminar: Business Intelligence in R and Python