89 citations · 354 across the 44 of their papers we have counts for
45 papers
A Modified Moving Reference Frame Method for Propeller Resolution
Denis Andreev, Georgios Bletsos, Antonios Kritikos +2
Accurate resolution of propeller-hull interaction is essential for predicting the self-propulsion point in ship CFD, yet motion-resolving methods such as sliding interfaces (SI) ar…
How Reliable Is the Multi-Input Heuristic for Bitcoin Address Clustering in Law Enforcement Contexts?
Leopold Müller, Jana Elsner, Thomas Niedermayer +4
Address clustering is an important technique in blockchain forensics, widely employed by law enforcement to trace illicit crypto asset flows. The multi-input heuristic (MIH), which…
Reading Between the Tokens: Improving Preference Predictions through Mechanistic Forecasting
Sarah Ball, Simeon Allmendinger, Frauke Kreuter +1
Large language models are increasingly used to predict human preferences in both scientific and business endeavors, yet current approaches rely exclusively on analyzing model outpu…
Rapid Aerodynamic Assessment of Flettner Rotor Installations Using an Inviscid CFD Approach
Niklas Kühl
This paper introduces an inviscid Computational Fluid Dynamics (CFD) approach for the rapid aerodynamic assessment of Flettner rotor systems on ships. The method relies on the Eule…
Identification of Beneficial and Detrimental Structure Locations Around Flettner Rotors Using Topology-Optimization-Inspired Sensitivity Fields
Niklas Kühl
Flettner rotors are highly sensitive to their surrounding flow field and may be significantly affected by nearby ship structures, deck cargo, and superstructures. Assessing the aer…
A Multivocal Literature Review on Privacy and Fairness in Federated Learning
Beatrice Balbierer, Lukas Heinlein, Domenique Zipperling +1
Federated Learning presents a way to revolutionize AI applications by eliminating the necessity for data sharing. Yet, research has shown that information can still be extracted du…
Incremental Singular Value Decomposition Based Model Order Reduction of Scale Resolving Fluid Dynamic Simulations
Niklas Kühl
Scale-resolving flow simulations often feature several million [thousand] spatial [temporal] discrete degrees of freedom. When storing or re-using these data, e.g., to subsequently…
Investigating the Role of Explainability and AI Literacy in User Compliance
Niklas Kühl, Christian Meske, Maximilian Nitsche +1
AI is becoming increasingly common across different domains. However, as sophisticated AI-based systems are often black-boxed, rendering the decision-making logic opaque, users fin…
Transferring Domain Knowledge with (X)AI-Based Learning Systems
Philipp Spitzer, Niklas Kühl, Marc Goutier +2
In numerous high-stakes domains, training novices via conventional learning systems does not suffice. To impart tacit knowledge, experts' hands-on guidance is imperative. However,…
Interactive Generation of Laparoscopic Videos with Diffusion Models
Ivan Iliash, Simeon Allmendinger, Felix Meissen +2
Generative AI, in general, and synthetic visual data generation, in specific, hold much promise for benefiting surgical training by providing photorealism to simulation environment…
Understanding Data Understanding: A Framework to Navigate the Intricacies of Data Analytics
Joshua Holstein, Philipp Spitzer, Marieke Hoell +2
As organizations face the challenges of processing exponentially growing data volumes, their reliance on analytics to unlock value from this data has intensified. However, the intr…
Complementarity in Human-AI Collaboration: Concept, Sources, and Evidence
Patrick Hemmer, Max Schemmer, Niklas Kühl +2
Artificial intelligence (AI) has the potential to significantly enhance human performance across various domains. Ideally, collaboration between humans and AI should result in comp…
Implications of the AI Act for Non-Discrimination Law and Algorithmic Fairness
Luca Deck, Jan-Laurin Müller, Conradin Braun +2
The topic of fairness in AI, as debated in the FATE (Fairness, Accountability, Transparency, and Ethics in AI) communities, has sparked meaningful discussions in the past years. Ho…
CollaFuse: Navigating Limited Resources and Privacy in Collaborative Generative AI
Domenique Zipperling, Simeon Allmendinger, Lukas Struppek +1
In the landscape of generative artificial intelligence, diffusion-based models present challenges for socio-technical systems in data requirements and privacy. Traditional approach…
Human Delegation Behavior in Human-AI Collaboration: The Effect of Contextual Information
Philipp Spitzer, Joshua Holstein, Patrick Hemmer +4
The integration of artificial intelligence (AI) into human decision-making processes at the workplace presents both opportunities and challenges. One promising approach to leverage…
Navigating the Synthetic Realm: Harnessing Diffusion-based Models for Laparoscopic Text-to-Image Generation
Simeon Allmendinger, Patrick Hemmer, Moritz Queisner +5
Recent advances in synthetic imaging open up opportunities for obtaining additional data in the field of surgical imaging. This data can provide reliable supplements supporting sur…
Redefining the Laparoscopic Spatial Sense: AI-based Intra- and Postoperative Measurement from Stereoimages
Leopold Müller, Patrick Hemmer, Moritz Queisner +5
A significant challenge in image-guided surgery is the accurate measurement task of relevant structures such as vessel segments, resection margins, or bowel lengths. While this tas…
Towards Effective Human-AI Decision-Making: The Role of Human Learning in Appropriate Reliance on AI Advice
Max Schemmer, Andrea Bartos, Philipp Spitzer +4
The true potential of human-AI collaboration lies in exploiting the complementary capabilities of humans and AI to achieve a joint performance superior to that of the individual AI…
AB2CD: AI for Building Climate Damage Classification and Detection
Maximilian Nitsche, S. Karthik Mukkavilli, Niklas Kühl +1
We explore the implementation of deep learning techniques for precise building damage assessment in the context of natural hazards, utilizing remote sensing data. The xBD dataset,…
The Impact of Imperfect XAI on Human-AI Decision-Making
Katelyn Morrison, Philipp Spitzer, Violet Turri +3
Explainability techniques are rapidly being developed to improve human-AI decision-making across various cooperative work settings. Consequently, previous research has evaluated ho…
Conceptualizing A Multi-Sided Platform For Cloud Computing Resource Trading
Franziska Haller, Max Schemmer, Niklas Kühl +1
Cost-effective and responsible use of cloud computing resources (CCR) is on the business agenda of many companies. Despite this strategic goal, two geopolitical strategy decisions…
On the Perception of Difficulty: Differences between Humans and AI
Philipp Spitzer, Joshua Holstein, Michael Vössing +1
With the increased adoption of artificial intelligence (AI) in industry and society, effective human-AI interaction systems are becoming increasingly important. A central challenge…
Learning to Defer with Limited Expert Predictions
Patrick Hemmer, Lukas Thede, Michael Vössing +2
Recent research suggests that combining AI models with a human expert can exceed the performance of either alone. The combination of their capabilities is often realized by learnin…
Parameter-free shape optimization: various shape updates for engineering applications
Lars Radtke, Georgios Bletsos, Niklas Kühl +4
In the last decade, parameter-free approaches to shape optimization problems have matured to a state where they provide a versatile tool for complex engineering applications. Howev…