About

Bio.

I am a Research Associate (Postdoctoral Researcher) at the Technical University Dortmund and the Research Center Trustworthy Data Science and Security (RC Trust) in the Human-AI Interaction Group led by Prof. Dr. Sven Mayer.

Previously, I was a researcher at the University of Duisburg-Essen in the Human-Computer Interaction Group led by Prof. Dr. Stefan Schneegass, where I completed my doctorate (Dr. rer. nat.). There, I completed my dissertation titled “Behavioral Biometrics in Extended Reality: Implicit User Authentication through Artificial Intelligence” with summa cum laude. In my research, I have explored a novel biometric authentication modality that uses peoples’ behavioral and spatiotemporal data in Extended Reality (XR) environments to perform implicit user authentication. Thereby, my work contributes to relieve people of the burdens associated with today’s security measures, such as frequently entering passwords.

Besides, I hold a Master’s and Bachelor’s degree in Applied Computer Science - Systems Engineering, from the University of Duisburg-Essen. In parallel to my Master studies, I was an IT-Specialist introducing and operating the central e-learning at Ruhr West University of Applied Sciences, developed software as a freelancer, and worked in STEM outreach.

Research.

My research lies at the intersection of usable, human-centered security, Artificial Intelligence (AI), and XR. Specifically, I aim to contribute security solutions for intelligent systems that put the human back in focus.

My approach starts by exploring novel biometric methods that enable implicit user authentication, relieving people of the burden associated with traditional authentication. During my doctorate, I built approaches utilizing behavioral biometrics in XR devices for implicit user identification, established a novel class of biometrics named Functional Biometrics for wearable computing, and published multiple behavioral biometric data sets to support open science.

Besides this, I investigate methods for ahead-of-time predictions of users’ intent and behavior for security applications, and explore the capabilities that agentic AI offers for security-related tasks to ensure robust, privacy-preserving interactions.