Dr. Florian Kern
Research Assistant
Contact Details
Dr. Florian KernHuman-Computer Interaction
Universität Würzburg
Emil-Fischer-Straße 50
D-97074 Würzburg
✆ +49 (0) 931 31 89223
✉ ed.grubzreuw-inu04%nrek.nairolf
⌂ Room 01.032, Building 50, Hubland North
About me
Florian Kern is a postdoctoral researcher in the Human-Computer Interaction Group led by Prof. Dr. Marc Erich Latoschik. He works in the AI AT WORK project within the PIIS group, where he is responsible for developing and providing an AI-infrastructure for embodied conversational AI agents in XR. He leads the Reality Stack team, which develops reusable and publicly available XR software components. Previously, he worked on the interdisciplinary ViLeArn project, where he developed and researched a social XR platform for collaborative teaching and learning.
Details
Florian obtained his PhD in Computer Science with a focus on Human-Computer Interaction. His dissertation, ‘Using Controller Styluses for Virtual Keyboards and Handwriting Text Input in XR’, investigates the feasibility and applicability of repurposing consumer-grade XR controllers as controller styluses and evaluates their impact on the performance and user experience of virtual tap and swipe keyboards and handwriting text input in XR environments.
He holds an M.Sc. in Computer Science with a focus on Human-Computer Interaction. His master’s thesis, supervised by Prof. Dr. Marc Erich Latoschik, examined how virtual reality and gamification in procedurally generated environments can improve motivation during treadmill training for gait rehabilitation.
Florian received a B.Sc. in Information Systems and Management from Technische Hochschule Nürnberg Georg Simon Ohm. His bachelor’s thesis, supervised by Prof. Dr. Ramin Tavakoli Kolagari in cooperation with Elektrobit Automotive GmbH, Tennenlohe, involved developing a simulation framework for connected car management services.
Projects
Research topics:
- Extended Reality
- Virtual Reality
- Augmented Reality
- Text Input Techniques
- Embodied Conversational Agents
- Multi-User XR Scenarios
- Gait Rehabilitation