Robert Lange
Photo: SCIoI
Robert Tjarko Lange works at the intersection of machine learning and behavioural biology. His research combines tools from top-down optimisation (e.g. Reinforcement Learning) with bottom-up phenomenological modelling. Thereby, nature and nurture are analysed from a complementary perspective and not as forces that trade-off. Before joining SCIoI, he obtained a MSc in Computing from Imperial College London and conducted research within the Einstein Center for Neurosciences Berlin.
Projects
Robert Lange is member of:
Publications +
2756394
Lange
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50
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year
19921
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%22firstName%22%3A%22Murat%22%2C%22lastName%22%3A%22Kirtay%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olga%20A.%22%2C%22lastName%22%3A%22Wudarczyk%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rasha%22%2C%22lastName%22%3A%22Abdel%20Rahman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Verena%20V.%22%2C%22lastName%22%3A%22Hafner%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anna%20K.%22%2C%22lastName%22%3A%22Kuhlen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John-Dylan%22%2C%22lastName%22%3A%22Haynes%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222021%22%2C%22language%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222025-09-26T13%3A16%3A12Z%22%7D%7D%5D%7D
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(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. https://doi.org/10.1038/s41567-022-01916-1
Vischer, M., Lange, R., & Sprekeler, H. (2022). On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning. ICLR 2022. https://doi.org/10.48550/arXiv.2105.01648
Lange, R., & Sprekeler, H. (2022). Learning not to learn: Nature versus Nurture in Silico. AAAI 2022. https://doi.org/10.48550/arXiv.2010.04466
Pischedda, D., Lange, A., Kirtay, M., Wudarczyk, O. A., 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. 5th Virtual Social Interactions (VSI) Conference.
Pischedda, D., Lange, A., Kirtay, M., Wudarczyk, O. A., 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. Neuroscience 2021.
Google Cloud Research Credit Grant
G-Research Grant for PhD Students in a Quantitative Field
Student Travel Award (CECCO 2023 Conference)
