DAFYDD COTOARBĂ
I am a Researcher at the Georg Nemetschek Institute - Artificial Intelligence for the Built World, Technical University of Munich.
My work centers on uncertainty quantification, data-driven methods, and optimization in geotechnical engineering applications. I am passionate about transferring research to industry and bridging the gap between academic innovation and real-world impact.
As a Venture Scout at First Momentum Ventures, I identify and support promising Deep Tech and Industry Tech startups across Europe, connecting cutting-edge research with entrepreneurial opportunities.
My research focuses on uncertainty quantification, data-driven methods, and optimization in geotechnical engineering applications.
I work on probabilistic digital twins for the built environment, particularly in geotechnical design and construction. My work explores how to optimally use data and models to reduce uncertainty and improve decision-making in civil engineering projects.
Research Interests: Bayesian inference, model updating, adaptive decision rules, geotechnical engineering, digital twins, uncertainty reduction.
Journal Papers
Probabilistic digital twins for geotechnical design and construction
Data-Centric Engineering 6, e30, 2025
Optimal adaptive decision rules in geotechnical construction considering uncertainty
Géotechnique 74(13), 2024, pp. 1622-1633
Conference Papers
Leveraging probabilistic machine learning for subsoil modelling to estimate excavated material volumes
EG-ICE 2025: International Workshop on Intelligent Computing in Engineering, 2025
Data-driven uncertainty reduction in geotechnical engineering: Optimal preloading of a road embankment
14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), 2023
Model Updating for Geotechnical Design and Assessment
30th International Conference on Intelligent Computing in Engineering (EG-ICE), 2023
Conference Presentations & Posters
Presentation
3rd IACM Digital Twins in Engineering Conference (DTE 2025) & 1st ECCOMAS AICOMAS 2025, Paris, France, February 2025
Poster
2024 ASCE International Conference on Computing in Civil Engineering (I3CE), Pittsburgh, USA, July 2024
Poster
The Future of Construction 2023 Symposium, Munich, Germany, September 2023
Current Teaching
Seminar on Elements of Machine Learning - Teaching Assistant (Tutorials)
Winter semester 2024/25, Winter semester 2025/26
Previous Teaching Experience
Foundations in Data Engineering - Teaching Assistant
Chair of Database Systems, TUM | Oct 2021 - Mar 2022
Computational Linear Algebra - Teaching Assistant
Chair of Computational Modeling and Simulation, TUM | Nov 2020 - Feb 2021
Structural Analysis 1 & 2 - Teaching Assistant
Chair of Structural Analysis, TUM | Apr 2018 - Aug 2018
Student Supervision
I supervise student projects and master's theses on topics related to uncertainty quantification, probabilistic modeling, and machine learning applications in civil and geotechnical engineering.
Education
PhD Candidate | Technical University of Munich
Georg Nemetschek Institute - Artificial Intelligence for the Built World
July 2022 - Present
Master's degree, Civil Engineering | Technical University of Munich
Honours Track: Bavarian Graduate School of Computational Engineering (BGCE)
2019 - March 2022
Bachelor of Engineering, Civil Engineering | Technical University of Munich
2015 - 2019
Civil Engineering | Technical University of Cluj Napoca
September 2014 - August 2015
Professional Experience
Venture Scout | First Momentum Ventures
May 2025 - Present
Identifying promising startups and founders in Deep Tech, Industry Tech, and B2B SaaS across Europe
Visiting Researcher | Deltares
Delft, Netherlands | April 2025 - June 2025
Researcher | Georg Nemetschek Institute - Artificial Intelligence for the Built World, TUM
July 2022 - Present
Research on uncertainty quantification, data-driven methods, and optimization in geotechnical engineering
Research Assistant | Chair of Computational Modeling and Simulation, TUM
April 2018 - June 2020
Honors & Awards
MSc. Honors Track
Bavarian Graduate School of Computational Engineering - Elite Network of Bayern, 2022
Hackathon Winner
[Hackathon Name], [Year]
Merit Scholarship
Konrad-Adenauer-Stiftung, 2016