René Schallner is a Senior Researcher in the Artificial Intelligence research area and Manager of the NIM Technology Lab.
His current research focus is on the interfaces between Artificial Intelligence, Machine Learning, Robotics, and Human-Machine Interaction in the context of decision-making in markets.
With his extensive software engineering experience, he shapes the challenging and exciting research projects in the Artificial Intelligence research area. For example, he develops voice assistants with synthetic emotional voice, virtual online consultations with virtual financial advisors in the form of social robots, experimental social media environments for virtual influencers, and experiments with large language models or Chat-GPT intelligence in social robots for natural human-AI interaction.
In previous projects, he collaborated with Dr. Carolin Kaiser on methods for extracting marketing knowledge from social media images. The research project Social Media Images was awarded the Innovation Prize of the BVM (Federal Association of German Market and Social Researchers) in 2016. His focus was on the development of modern technologies and methods such as deep learning in the field of computer vision and their application on mobile devices.
In the NIM Technology Lab, he advances the state of the art for experimental software with a focus on AI. He develops customized backend and frontend software for large-scale online experiments and surveys with complex user interactions. Additionally, he works on electronic systems, such as wireless synchronization of sensor data and server data.
Before working at NIM, Rene Schallner was an internationally sought-after consultant in software and firmware development, contributing to key projects in both the telecommunications and medical technology sectors.
René Schallner completed the "Higher Department for Electronics and Technical Computer Science" at the Austrian Higher Technical Federal Teaching and Research Institute in Mödling near Vienna.
- Kaiser, C., Schallner, R. (2020). Artificial Voices in Human Choices. Proceedings of the 22nd General Online Research Conference, Berlin.
- Kaiser. C., Schallner, R. (2020). Der Ton macht den Einkauf zum Erlebnis. planung&analyse 2/2020, pp. 84—86.
- Schallner, R.; Kaiser, C. (2019). Mobile Detection of Visual Brand Touchpoints. Proceedings of the 21st General Online Research Conference, Cologne.
- Kaiser, C., Schallner, R., & Manewitsch, V. (2019). Revealing Consumer-Brand-Interactions from Social Media Pictures – A Case Study from the Fast-Moving Consumer Goods Industry. Proceedings of the 21st General Online Research Conference, Cologne.
- Harzig, P., Zecha, D., Lienhart, R., Kaiser, C., & Schallner, R. (2019). Image captioning with clause-focused metrics in a multi-modal setting for marketing. 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), San Jose, CA, USA, 419–424.
- Harzig, P., Brehm, S., Lienhart, R., Kaiser, C., & Schallner, R. (2018). Multimodal image captioning for marketing analysis. Proceedings of the IEEE Conference on Multimedia Information Processing and Retrieval, FL, USA.
- Schallner, R. (2018). Einblicke ins Ungesehene. Planung&Analyse, 4, 86-87.
- Paolanti, M., Kaiser, C., Schallner, R., Frontoni, E., & Zingaretti, P. (2017). Visual and textual sentiment analysis of brand-related social media pictures using deep convolutional neural networks. In S. Battiato , G. Gallo, R. Schettini & F. Stanco (Eds.), Lecture Notes in Computer Science. Presented at the International Conference on Image Analysis and Processing (pp. 402–413). Springer.