Research

Philisophy and Mission Statement

Is it possible for a civil engineer and member of a university to pursue both, a successful teaching career and future-oriented science while serving as a link between research and practice application? And can a civil engineer make significant research contributions in other fields such as architecture or computer science? From my previous experience as a post-doctoral researcher at Stanford and ETH Zurich, I can answer this question with a bright YES.

Status Quo

CA-X

Computer-aided Design, Manufacturing and Engineering

My Envisioned Future

„AIA-X“

Artificial Intelligence-aided Design, Manufacturing and Engineering

I conduct research at the boundary of structural engineering, architecture and computer sciences with the aim of further establishing digital methods and in particular Artificial Intelligence (AI) as well as providing novel computational tools for a sustainable, appealing yet reliable design and analysis of critical structures of the built environment. As an engineer working in academia, my research follows the strictest scientific principles, research results translate into concrete and actionable recommendations for practice, in addition to professional publications.

Research Vision

I envision the transformation of how we desing, build, operate and recycle the built environment to shift from the current “computer aided” (CA-X) fashion to an “Artificial Intelligence aided” (AIA-X) way. I strongly belive, that augmenting the building design and analysis experts’ insight with AI tools will eliminate their unconscious bias and allows to combine human thinking with computational power for benefiting a more human-centred, sustainable and aesthetic yet reliable built environment.

For the civil engineering domain, this specifically comes down to AI augmented {design (AIA-D), structural and dynamic analysis (AIA-E) and checking}.

In order to find a sensible, human-centered and interpretable fashion for augmenting civil engineering design and analysis with methods and algorithms of Artificial Intelligence, two major concepts have to be understood:

  • three components are needed for creating a meaningful application of AI: access to computational hardware as well as AI software and availability of domain data (which contain the pattern of interest)
  • Scientific Machine Learning is the appropriate methodical frame instead of “black-box AI” as it is at the intersection of domain knowledge from civil engineering, computer sciences and mathematics/statistics.

For the typical reasons of data sparsity and the need of explainability and interpretability in civil engineering, my core research is driven to establish and develop methods and algorithms of Scientific Machine Learning for the civil structural engineering domain. My research consists of combining the three pillars of theory, experiment and computation at the structural engineering intersection.

Research Projects

 

Scientific Machine Learning | The Bridge-Genome-Data-Project

Conceptual structural design today relies heavily on the intuition and experience of the structural engineer, often includes an investigation of similar reference projects, and is mostly a time-consuming and demanding task that is characterized by many iteration...

All Projects

Latest Publications

 

All Publications
My Scholar Page

Peer-Reviewing and Editor Activities

For me, publishing papers in scientific as well as practice journal is at the heart of science communication for different audiences. This ensures knowledge transfer from and to industry and academia as well. The peer review process thereby is the principal mechanism by which the quality of research at the current state of knowledge is judged. I actively engage at both sides of the table of the publishing process to gain highest scientific quality for publications in my fields of expertise.

To that end, is serve as active reviewer for a number of journals:

and also as editor: