Anna Lange
Photo: SCIoI
Anna Lange has a diverse academic background spanning mathematics, psychology, computational neuroscience, and human-robot interaction.
She joined SCIoI as a doctoral researcher in June 2023.
Anna obtained her Bachelor of Science degree in Mathematics with Psychology from Queen Mary University of London and completed a Master of Science degree in Computational Neuroscience at the Bernstein Center for Computational Neuroscience Berlin. During her Master’s program, Anna actively engaged in research at Charité – Universitätsmedizin Berlin, where her work revolved around investigating Human-Robot Interactions using functional Magnetic Resonance Imaging (fMRI). In parallel, she contributed to the development of neural networks inspired by human psychology for Robot-Robot Interactions at Humboldt-Universität zu Berlin. Both of these positions were part of her involvement in SCIoI Project 09.
At SCIoI, Anna in involved in Project 50 as part of the Adaptive Systems group at Humboldt-Universität zu Berlin under the supervision of Prof. Verena Hafner. Her current research revolves around enhancing adaptive learning and teaching strategies in robots during social interactions. She achieves this by creating adaptive neural networks grounded in the principles of human psychology.
Projects
Anna Lange is member of:
Publications +
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50
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19923
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Lange, A. L., Ackermann, H., Lazarides, R., & Hafner, V. V. (2027). A Robot-LLM Integration Framework for Social Learning Interactions. In O. Brock, J. Krichmar, & V. Mengers (Eds.), From Animals to Animats 18 (Vol. 16965, pp. 180–191). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-39953-3_15
Ackermann, H., Lange, A. L., Dumont, H., Hafner, V. V., & Lazarides, R. (2026). Real-time cognitive-affective dynamics of failure feedback in a technology-based learning task. Communications Psychology, 4(1), 95. https://doi.org/10.1038/s44271-026-00487-8
Ackermann, H., Lange, A. L., Hafner, V. V., & Lazarides, R. (2025). How adaptive social robots influence cognitive, emotional, and self-regulated learning. Scientific Reports, 15(1), 6581. https://doi.org/10.1038/s41598-025-91236-0
Taliaronak, V., Lange, A. L., Kirtay, M., Oztop, E., & Hafner, V. V. (2023). Advancing Humanoid Robots for Social Integration: Evaluating Trustworthiness Through a Social Cognitive Framework. 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2112–2119. https://doi.org/10.1109/RO-MAN57019.2023.10309519
Gómez-Nava, L., Lange, R. T., Klamser, P. P., Lukas, J., Arias-Rodriguez, L., Bierbach, D., Krause, J., Sprekeler, H., & Romanczuk, P. (2023). Fish shoals resemble a stochastic excitable system driven by environmental perturbations. Nature Physics, 19(5), 663–669. https://doi.org/10.1038/s41567-022-01916-1
Lange, R. T., & Sprekeler, H. (2022). Learning Not to Learn: Nature versus Nurture In Silico. Proceedings of the AAAI Conference on Artificial Intelligence, 36(7), 7290–7299. https://doi.org/10.1609/aaai.v36i7.20691
Vischer, M., Lange, R. T., & Sprekeler, H. (2022). On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning. International Conference on Learning Representations (ICLR). https://doi.org/10.48550/arXiv.2105.01648
Pischedda, D., Lange, A., Kirtay, M., Wudarczyk, O., Abdel Rahman, R., Hafner, V. V., Kuhlen, A. K., & Haynes, J.-D. (2021). Who is my interlocutor? Partner-specific neural representations during communicative interactions with human or artificial task partners. [Poster]. 5th Virtual Social Interactions (VSI) Conference.
Pischedda, D., Lange, A., Kirtay, M., Wudarczyk, O., Abdel Rahman, R., Hafner, V. V., Kuhlen, A. K., & Haynes, J.-D. (2021). Am I speaking to a human, a robot, or a computer? Neural representations of task partners in communicative interactions with humans or artificial agents [Poster]. Annual Meeting of the Society for Neuroscience (SfN).
For the Public -
Girls’ Day 2024
For the Public -
Science of Intelligence Fair 2023
