Susanne Trick M.Sc.
Psychologie der Informationsverarbeitung
work +49 6151 16-24171
Susanne Trick joined the lab as a PhD student in January 2019.
She is part of the research group investigating interactive AI algorithms and human-robot interaction. IKIDA
Besides the project, from 2019 to 2021 she was also working on the IKIDA project which aims to contribute to maintaining the independence of elderly people with a humanoid robot that supports everyday life activities. Kobo34
Susanne Trick’s research focuses on the understanding and prediction of human behavior, particularly in the interaction between human and robot. Her main interest is the integration of data from multiple modalities (e.g. gaze, gestures, speech). Consequently, she also works on probabilistic modeling of optimal combination of multimodal data, in particular considering their uncertainty and correlation.
Presentations and publications
- Trick, S.; Rothkopf, C.A.; Jäkel, F. (2023). Parameter Estimation for a Bivariate Beta Distribution with Arbitrary Beta Marginals and Positive Correlation. METRON.  pdf
- Trick, S.; Herbert, F.; Rothkopf, C.A.; Koert, D. (2022). Interactive Reinforcement Learning With Bayesian Fusion of Multimodal Advice, IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 7558-7565, July 2022, doi: 10.1109/LRA.2022.3182100. [ (wird in neuem Tab geöffnet) ] pdf
- Trick, S.; Rothkopf, C. (2022). Bayesian Classifier Fusion with an Explicit Model of Correlation. In International Conference on Artificial Intelligence and Statistics. [ (wird in neuem Tab geöffnet)] pdf
- Trick, S.; Koert, D.; Peters, J.; Rothkopf, C. (2019). Multimodal Uncertainty Reduction for Intention Recognition in Human-Robot Interaction, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
- Koert, D.; Trick, S., Ewerton, M.; Lutter, M.; Peters, J. (2019). Incremental Learning of an Open-Ended Collaborative Skill Library, International Journal of Humanoid Robotics.
- Koert, D.; Trick, S.; Ewerton, M.; Lutter, M.; Peters, J. (2018). Online Learning of an Open-Ended Skill Library for Collaborative Tasks, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
- Koert, D.; Pajarinen, J.; Schotschneider, A.; Trick, S., Rothkopf, C.; Peters, J. (2019). Learning Intention Aware Online Adaptation of Movement Primitives, IEEE Robotics and Automation Letters (RA-L), with presentation at the IEEE International Conference on Intelligent Robots and Systems (IROS).
- Jahn, E.; Koert, D.; Trick, S.; Müller, M.; et. al (2022). Learning from Each Other—How Roboticists Learn from Users and How Users Teach Their Robots, in Meaningful Futures with Robots—Designing a New Coexistence (pp. 217-224), Chapman and Hall/CRC.
- Winner of the German AI-Newcomer Awards 2023 which is awarded by the German Federal Ministry of Education and Research and the German Informatics Society.
|Since 2019||PhD student at the Psychology of Information Processing lab of Prof. Constantin Rothkopf, TU Darmstadt, Germany|
|2018||Student Researcher at the Psychology of Information Processing lab of Prof. Constantin Rothkopf, TU Darmstadt, Germany|
|2016 – 2018||M.Sc. Psychology in Information Technology, TU Darmstadt, Germany|
|2013 – 2016||B.Sc. Psychology in Information Technology, TU Darmstadt, Germany|
|Winter 2022/23||Advanced Cognitive Science I: Perception and Action||(Seminar)|
|Summer 2021||Cognitive Science III: Action||(Seminar)|
|Summer 2020||Cognitive Science III: Action||(Seminar)|
|Summer 2019||Application-oriented program design in Java||(Seminar)|