I’m a final year Ph.D. candidate and research associate in the Interaction Lab at the University of Stuttgart. My research is grounded in the domain of Human-Computer Interaction and applies Machine Learning techniques to improve and extend interaction on mobile devices.
Most recently, I am working on new touch-based interaction techniques driven by capacitive sensing processing with deep learning. Model-based input processing enables new application scenarios such as finger-aware input, grip sensing, and the inference of further input properties to solve the current limitations of touch input. I am also interested in modeling hand ergonomics and touch interaction in general to find new ways for improving interaction with mobile devices.
Prior to my Ph.D. work starting in late 2015, I completed a Bachelor’s and Master’s degree in Software Engineering at the University of Stuttgart. Moreover, I worked as a software engineering intern at Daimler TSS and as a visiting researcher at the School of Computing and Communications at the Lancaster University. Don’t hesitate to contact me in case of any questions!
Latest Updates
- 10/2018
- Presented a paper about deep learning for finger-aware interaction on fully touch sensitive smartphones at UIST ’18 in Berlin, Germany.
- 09/2018
- Co-organized a tutorial on Machine Learning For Intelligent Mobile User Interfaces using Keras and presented a demo at MobileHCI ’18 in Barcelona, Spain.
- 04/2018
- Presented two papers (1, 2) and my PhD work at the Doctoral Consortium at CHI ’18 in Montréal, Canada.
- 03/2018
- Gave a public talk of my Milestone Presentation about Hand-and-Finger-Aware Touch Interaction on Mobile Devices at the University of Stuttgart.
- 11/2017
- Co-organized a tutorial on Machine Learning with Tensorflow for Mobile and Ubiquitous Interaction at MUM ’17 in Stuttgart, Germany.
- 10/2017
- Presented a paper about reducing touchscreen latency using neural networks and IMUs at ISS ’17 in Brighton, England.
- 09/2017
- Co-organized a tutorial on Machine Learning for Intelligent Mobile User Interfaces Using TensorFlow at MobileHCI ’17 in Vienna, Austria, and at Mensch & Computer 2017 at Regensburg, Germany.
Teaching
- WS18/19
- Machine Learning and Computer Vision for HCI (Lab Course)
- SS18
- Machine Learning for Human-Computer Interaction (Lab Course)
- WS17/18
- Machine Learning for Intelligent Mobile User Interfaces using TensorFlow (Lab Course)
- WS17/18
- Media Informatics (Lecture)
- SS17
- Physical Computing (Lab Course)
- WS16/17
- Multimodal Interaction for Ubiquitous Computers (Lecture)
- SS16
- Mobile Multi-Device Interaction (Lab Course)
Academic Service
- Selected as Reviewer for CHI, UIST, MobileHCI, ISS, NordiCHI, TEI, AH, MUM, Multimedia
- Worked as student volunteer for MobileHCI ’16, NordiCHI ’16, MUM ’17, NordiCHI ’18
- Co-organized tutorials at MobileHCI ’17, Mensch und Computer ’17, MUM ’17, PerDis ’18, and MobileHCI ’18