Michael Kraus

Professor for Structural Analysis

Technische Universität Darmstadt

Germany

Research Interests

Explore related searches

Professors in Germany Professors in Deep Learning Deep Learning professors in Germany

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Michael Kraus is a Professor for Structural Analysis at the Technical University of Darmstadt, Germany. His research areas include physics-informed deep learning, fiber-reinforced concrete design, and generative design for engineering structures. Recent publications highlight advancements in limit analysis, temperature prediction, and automated quality control in structural engineering.

Articles (12)

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Year:

2021

Collaborators (2)

Jens Henrik Nielsen

Technical University of Denmark

DENMARK

View details

Siyu Tang

Tenure-track assistant professor

ETH Zurich

SWITZERLAND

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Michael Kraus

Research Interests

Explore related searches

Contact this professor

About

Articles (12)

Multi-Objective Loss Balancing for Physics-Informed Deep Learning

Limit analysis and design recommendations for fiber‐reinforced concrete subjected to shear

Design Space Exploration and Explanation via Conditional Variational Autoencoders in Meta-Model-Based Conceptual Design of Pedestrian Bridges

Parametrische Modellierung und generatives tiefes Lernen für den Brückenentwurf

Strength Lab AI: a mixture-of-experts deep learning approach for limit state analysis and design of monolithic and laminate structures made of glass

Performance-Based Generative Design for Parametric Modeling of Engineering Structures Using Deep Conditional Generative Models

Temp-AI-Estimator: Interior temperature prediction using domain-informed Deep Learning

The in-plane expansion of fractured thermally pre-stressed glass panes

Automated quality control of vacuum insulated glazing by convolutional neural network image classification

Semi‐probabilistische Bemessung tragender Silikonverklebungen mit Teilsicherheitsbeiwerten

Experimental and numerical investigations on glass fragments: shear-frame testing and calibration of Mohr–Coulomb plasticity model

The In-plane Expansion of Fractured Thermally Pre-stressed Glass Panes

Collaborators (2)

Jens Henrik Nielsen

Siyu Tang

Make your next move.