Pascal Sager
Pascal Sager
ZHAW
School of Engineering
Machine Perception & Cognition Group
Technikumstrasse 71
8400 Winterthur
Work at ZHAW
Position
PhD Student | Head of AI Demonstrators
Focus
AI, Deep Learning, World Models, Robotics
Teaching
- Lab Assistant Artificial Intelligence 1 (BSc.)
- Lab Assistant Artificial Intelligence (MAS)
- Lead Lab Machine Learning and Data Mining (BSc.)
Experience
- Co-Founder
Binabik AI
01 / 2026 - today - Member of the Board: Sustainable Impact Program
Zurich University of Applied Sciences
08 / 2023 - today - Senior Data Scientist
AlpineAI AG
08 / 2023 - 12 / 2024 - Head of GPU Infrastructure and AI Demonstrators
Zurich University of Applied Sciences
07 / 2022 - 08 / 2023 - Scientific Assistant at Centre for AI
Zurich University of Applied Sciences
09 / 2020 - 05 / 2022 - Software Engineer
Spühl GmbH
09 / 2018 - 09 / 2020 - Software Engineer PLC
Hardinge Europe
07 / 2015 - 08 / 2017 - Hardware Design Engineer
Spühl GmbH
08 / 2013 - 07 / 2015 - Apprenticeship Automation Engineering
Spühl GmbH
08 / 2009 - 07 / 2013
Education and Continuing education
Education
- Master of Science / Data Science
Zurich University of Applied Sciences
08 / 2020 - 08 / 2023 - Bachelor of Science / Computer Science
Zurich University of Applied Sciences
08 / 2017 - 07 / 2020 - Advanced Federal Diploma of Higher Education (ISCED 6) / Electrical Engineering
ZBW - Centre for Continuing Vocational Education and Training
08 / 2013 - 07 / 2016 - Automation Engineer EFZ / Automation
GBS Vocational and Further Training Centre St. Gallen
08 / 2009 - 07 / 2013
Network
Membership of networks
- Digital Futures Lab
- CLAIRE Rising Researchers Network
- Datalab, the ZHAW Data Science Laboratory
- CLAIRE, the Confederation of Laboratories for Artificial Intelligence Research in Europe
- Data Innovation Alliance
ORCID digital identifier
Social media
Projects
- Avatar Demonstrator: VR Control for Humanoid Robots / Deputy project leader / ongoing
- Learning World Models through Actionable Representation for Next-Generation AI / Project leader / ongoing
- Talking Bots: Interactive Voice Interface for Humanoid Robots in Networking Events / Deputy project leader / completed
- Stability of self-organizing net fragments as inductive bias for next-generation deep learning / Team member / completed
- Machine Learning for Body Composition Analysis / Deputy project leader / completed
- AUTODIDACT – Automated Video Data Annotation to Empower the ICU Cockpit Platform for Clinical Decision Support / Team member / completed
- RealScore – Scanning of Real-World Sheet Music for a Digital Music Stand / Team member / completed
- Visual Food Waste Analysis for Sustainable Kitchens / Team member / completed
Publications
Articles in scientific journal, peer-reviewed
- Sager, P. J. et al. (2026) 'A comprehensive survey of agents for computer use : foundations, challenges, and future directions', Journal of Artificial Intelligence Research, 85(34). doi: 10.1613/jair.1.19490.
- Sager, P. J. et al. (2026) 'The cooperative network architecture : learning structured networks as representation of sensory patterns', Neural Computation, 38(4), pp. 538–572. doi: 10.1162/neco.a.1505.
- Tuggener, L. et al. (2024) 'Real world music object recognition', Transactions of the International Society for Music Information Retrieval, 7(1), pp. 1–14. doi: 10.5334/tismir.157.
- Sager, P. et al. (2022) 'Unsupervised domain adaptation for vertebrae detection and identification in 3D CT volumes using a domain sanity loss', Journal of Imaging, 8(8), p. 222. doi: 10.3390/jimaging8080222.
Written conference contributions, peer-reviewed
- Sager, P. et al. (2025) 'Deep retrieval at CheckThat! 2025 : identifying scientific papers from implicit social media mentions via hybrid retrieval and re-ranking', in Faggioli, G. et al. (eds) Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2025). CEUR Workshop Proceedings, pp. 1141–1155. doi: 10.21256/zhaw-33534.
- Meyer, B. et al. (2025) 'Hounsfield unit ranges as inductive bias for intra-clinical learning of data-efficient CT segmentation models', in 2025 IEEE Swiss Conference on Data Science (SDS). IEEE, pp. 1–7. doi: 10.1109/SDS66131.2025.00008.
- Saponati, M. et al. (2025) 'The underlying structures of self-attention : symmetry, directionality, and emergent dynamics in Transformer training', in Singh, A. et al. (eds) Proceedings of the 42nd International Conference on Machine Learning. Proceedings of Machine Learning Research, pp. 52958–52994. doi: 10.21256/zhaw-33652.
- Tuggener, L. et al. (2024) 'So you want your private LLM at home? : a survey and benchmark of methods for efficient GPTs', in 2024 11th IEEE Swiss Conference on Data Science (SDS). IEEE. doi: 10.1109/SDS60720.2024.00036.
- Simmler, N. et al. (2021) 'A survey of un-, weakly-, and semi-supervised learning methods for noisy, missing and partial labels in industrial vision applications', in Proceedings of the 8th SDS. IEEE, pp. 26–31. doi: 10.1109/SDS51136.2021.00012.