Florian Kadner

Florian Kadner M.Sc.

Psychology of Information Processing

Contact

work +49 6151 16-23366

Work S1|15 234
Alexanderstraße 10
64283 Darmstadt

Florian Kadner joined the lab as a PhD student in May 2019.

Until September 2022 he was working on the DFG project “Active vision: control of eye-movements and probabilistic planning”.

Research interests

I am interested in how humans carry out eye-movements across different tasks and how this can be understood with models of probabilistic planning. To investigate these issues, I try to examine environments and stimuli that are as natural as possible. Other areas of interest are image saliency, adaptive human-computer-interaction models and applied methods of machine learning and cognitive modeling.

Publications

Kadner, F., Willkomm, H., Ibs, I., & Rothkopf, C. (2023). Finding your Way Out: Planning Strategies in Human Maze-Solving Behavior. In Proceedings of the Annual Meeting of the Cognitive Science Society (Vol. 45, No. 45). [article]
[preprint]
Kadner, F., Thomas, T., Hoppe, D., & Rothkopf, C. A. (2023). Improving saliency models' predictions of the next fixation with humans' intrinsic cost of gaze shifts. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 2104-2114). [article]
[preprint]
Kadner, F., Keller, Y., & Rothkopf, C. (2021, May). Adaptifont: Increasing individuals’ reading speed with a generative font model and bayesian optimization. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1-11). [article]
[preprint]

Talks & Presentations

Trade-off between uncertainty reduction and reward collection
reveals intrinsic cost of gaze switches 		Talk at the annual meeting of the Vision Science Society, May 12-18, 2022, St. Pete Beach, Florida, USA [abstract]
AdaptiFont: Learning font spaces and adaptive fonts to increase individuals reading speed Guest lecture in the seminar “Screen Memories” at the HAW Hamburg
AdaptiFont: Increasing Individuals' Reading Speed with a Generative Font Model and Bayesian Optimization Talk at the CHI Conference on Human Factors in Computing Systems, 2021 [talk]

Awards

Winner of the TU Darmstadt Ideas Competition in the category “Scientists” for the project “AdaptiFont” (together with Constantin Rothkopf). October 2022

Teaching

Summer 2023 Statistical modeling for cognitive science Exercise B.Sc.
Summer 2022 Psychology Lab for Cognitive Science Practical course B.Sc.
Winter 2021 Cognitive Science II: Cognition Seminar B.Sc.
Summer 2021 Statistical modeling for cognitive science Exercise B.Sc.
Winter 2020 Advanced Module III: Applied Cognitive Science Seminar M.Sc.
Summer 2020 Statistical modeling for cognitive science Exercise B.Sc.
Specialization in cognitive psychology Seminar B.Sc.
Winter 2019 Advanced Module III: Applied Cognitive Science Seminar M.Sc.
Summer 2019 Cognitive Modeling Exercise B.Sc.

Co-supervised theses

M.Sc.
Christian Robert Bald A Partially Observable Markov Decision Process model of blinking (finished)
Marius Kleboth Comparing humans and reinforcement learning agents (finished)
Tobias Thomas The neuroeconomics of eye movements (finished)
Tabea Alina Wilke Learning temporal planning of gaze sequences under uncertainty (finished)
B.Sc.

Tobias Niehues Do humans adapt their planning horizon? (finished)
Thabo Matthies Learning generative models for font synthesis (finished)
Dinh Khanh Thi Vo Image captioning networks for saliency prediction (finished)
Trung-Hoa Ha Comparing machine learning methods for font generation (finished)
Wassim Ben Salem Fully Convolutional Network for Image Saliency (finished)