Prof Stefan Rueger

Professor of Knowledge Media

Stefan Rüger is a Professor of Knowledge Media at the Knowledge Media Institute of The Open University, a Honorary Professor (2009-2021) at the Department of Computer Science, University of Waikato, and used to be a Visiting Principal Research Fellow (2006-2009) at the Department of Computing, Imperial College London. He holds a degree in Theoretical Physics (equiv to MSc) and received his PhD in the field of computing for his work on the theory of artificial neural networks. Between 1999 and 2004 he held a prestigious EPSRC Advanced Research Fellowhip at Imperial College London, where he carved out his academic career from PostDoc (1997) to Reader in Multimedia and Information Systems (2005). His research has evolved over the years from theory of artificial neural networks over data mining and knowledge management to applications in multimedia search engines. At the Knowledge Media Institute he is

Publications

Ao, Shuang, RÃ¼ger, Stefan and Siddharthan, Advaith ,(2024). CSS: Contrastive Semantic Similarities for Uncertainty Quantification of LLMs. In: 40th Conference on Uncertainty in Artificial Intelligence (UAI 2024), 15-19 Jul 2024, Barcelona, Spain.

Ansine, Janice, Dodd, Michael, Valentine, Chris, RÃ¼ger, Stefan, Siddharthan, Advaith and Dadswell, Damian ,(2023). iSpot & AI: Integrating FASTCAT-Cloud and PI@ntNET-API in the Cos4Cloud framework. In: Computers and Learning Research Group (CALRG) Conference 2023, 27-30 Jun 2023, Online.

Sharma, Nirwan, Colucci-Gray, Laura, Lakeman-Fraser, Poppy, Robinson, Annie, Newman, Julie, Van der Wal, Rene, RÃ¼ger, Stefan and Siddharthan, Advaith ,(2024). Image Recognition as a âDialogic AI Partnerâ within Biodiversity Citizen Science - an empirical investigation. Citizen Science: Theory and Practice, 9(1),

Colucci-Gray, Laura, Hancock, Jonathan, Islam, Riasat, Sharma, Nirwan, Manches, Andrew, Bowers, Lisa, Lakeman-Fraser, Poppy, Mozier, Stephen, Newman, Julie, Reuger, Stefan and Siddharthan, Advaith ,(2024). Seeing with hands and touching with eyes: recovering sensorial attention to nature in primary schools. In: First International Conference on Embodied Education, 15-17 May 2024, Danish School of Education (DPU), Tuborgvej 164, 2400 Copenhagen, Denmark.

Hancock, Jonathan, Colucci-Gray, Laura, Siddharthan, Advaith, Manches, Andrew, Sharma, Nirwan, Islam, Riasat, Bowers, Lisa, Reuger, Stefan, Lakeman-Fraser, Poppy, Newman, Julie, Mozier, Stephen and Barry, Richard ,(2023). âWe felt the textures from nature and it gave us new ideasâ: Investigating sustainability education through primary school childrenâs natural and digital haptic touch explorations. In: SERA Conference 2023, Wednesday 22 - Friday 24 Nov 2023, Queen Margaret University, Musselburgh, United Kingdom.

Ao, Shuang, Rueger, Stefan and Siddharthan, Advaith ,(2023). Two Sides of Miscalibration: Identifying Over and Under-Confidence Prediction for Network Calibration. In: Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence, 31 Jul - 4 Aug 2023, Pittsburgh, PA, USA.

Ao, Shuang, RÃ¼ger, Stefan and Siddharthan, Advaith ,(2023). Empirical Optimal Risk to Quantify Model Trustworthiness for Failure Detection. In: 2023 IJCAI Joint Workshop on Artificial Intelligence Safety and Safe Reinforcement Learning, AISafety-SafeRL, 21-22 Aug 2023, Macau, China.

Ao, Shuang, RÃ¼ger, Stefan and Siddharthan, Advaith ,(2022). Confidence-Aware Calibration and Scoring Functions for Curriculum Learning. In: 2022 15th International Conference on Machine Vision., 18-20 Nov 2022, Rome, Italy.

Lakeman Fraser, Poppy, Colluci-Gray, Laura, Robinson, Annie, Sforzi, Andrea, Staples-Rolf, Ruth, Newman, Julie, Gill, Richard, Sharma, Nirwan, RÃ¼ger, Stefan and Siddharthan, Advaith ,(2023). X-Polli:Nation: Contributing towards sustainable development goals through school-based pollinator citizen science. Citizen Science: Theory and Practice, 8(1),

Riechmann, Miklas, Gardiner, Ross, Waddington, Kai, Rueger, Ryan, Fol Leymarie, Frederic and Rueger, Stefan ,(2022). Motion vectors and deep neural networks for video camera traps. Ecological Informatics, 69

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