Prof. Dr. Alisa Rupenyan-Vasileva

Work at ZHAW

Position

Rieter Stiftungsprofessur Industrial AI

Focus

Industrial AI, Automation of manufacturing systems, robotics, process optimization, neurosymbolic AI

Teaching

• CAS Machine Intelligence - Machine learning module
• Machine Learning and Data Mining
• Artificial Intelligence I

Experience

• Senior scientist, Automatic control laboratory
  ETH Zurich
  08 / 2020 - 07 / 2023
• Group leader, Automation and control group
  inspire AG
  02 / 2018 - 07 / 2023
• Head of Application Development
  Qualysense AG
  01 / 2014 - 09 / 2017
• Postdoctoral fellow (ETH fellow on individual grant)
  ETH Zurich
  01 / 2011 - 09 / 2013
• Postdoctoral researcher
  University of Amsterdam
  01 / 2010 - 12 / 2010

Education and Continuing education

Education

• PhD / Physics
  Vrije Universiteit Amsterdam, The Netherlands
  01 / 2005 - 12 / 2009
• MSc / Laser physics and optics
  Sofia University, Bulgaria
  10 / 2004 - 12 / 2005
• BSc / Engineering Physics
  Sofia University, Bulgaria
  10 / 1999 - 12 / 2004

Network

Membership of networks

• International Federation for Automatic Control - Industry Committee
• IEEE - senior member
• Innosuisse (innovation expert)
• NCCR Automation

ORCID digital identifier

ORCID ID: 0000-0002-2170-8564

Social media

Linkedin

Projects

• Cloud-Enabled Learning Controllers for HVAC Application / Project leader / ongoing
• Robotic 3D printing toolkit / Project leader / ongoing
• Continuous optimization and control for advanced manufacturing / Project leader / ongoing
• Digital Manufacturing as a Service Technology / Project leader / ongoing
• Intelligent planning for robot-based manufacturing / Project leader / ongoing
• Smart urban green spaces / Team member / completed

Publications

Articles in scientific journal, peer-reviewed

• Rupenyan, A., Bayanduryan-Levasgani, N., & Khosravi, M. (2026). Data-driven high-performance motion system optimization in practice. Control Engineering Practice, 172(106904). https://doi.org/10.1016/j.conengprac.2026.106904
• Nobar, M., Keller, J., Forino, A., Lygeros, J., & Rupenyan, A. (2026). Guided multi-fidelity Bayesian optimization for data-driven controller tuning with digital twins. IEEE Robotics and Automation Letters, 11(5), 5294–5301. https://doi.org/10.1109/lra.2026.3671557
• Wu, M., Rupenyan, A., & Corves, B. (2025). Autogeneration and optimization of pick-and-place trajectories in robotic systems : a data-driven approach. Robotics and Computer-Integrated Manufacturing, 97(103080). https://doi.org/10.1016/j.rcim.2025.103080
• Wu, M., Rupenyan, A., & Corves, B. (2025). Iterative learning control with mismatch compensation for residual vibration suppression in delta robots. Nonlinear Dynamics, 113(16), 21631–21651. https://doi.org/10.1007/s11071-025-11299-6
• König, C., Krishnadas, R., Balta, E. C., & Rupenyan, A. (2025). Adaptive Bayesian optimization for high-precision motion systems. IEEE Transactions on Automation Science and Engineering, 22, 15627–15637. https://doi.org/10.1109/tase.2025.3565776
• Kavas, B., Balta, E. C., Tucker, M. R., Krishnadas, R., Rupenyan, A., Lygeros, J., & Bambach, M. (2025). In-situ controller autotuning by Bayesian optimization for closed-loop feedback control of laser powder bed fusion process. Additive Manufacturing, 99(104641). https://doi.org/10.1016/j.addma.2025.104641
• Zagórowska, M., König, C., Yu, H., Balta, E. C., Rupenyan, A., & Lygeros, J. (2025). Efficient safe learning for controller tuning with experimental validation. Engineering Applications of Artificial Intelligence, 143(109894). https://doi.org/10.1016/j.engappai.2024.109894
• Liao-McPherson, D., Balta, E. C., Afrasiabi, M., Rupenyan-Vasileva, A., Bambach, M., & Lygeros, J. (2024). Layer-to-layer melt pool control in laser powder bed fusion. IEEE Transactions on Control Systems Technology. https://doi.org/10.1109/TCST.2024.3464118
• Nobar, M., Keller, J., Rupenyan, A., Khosravi, M., & Lygeros, J. (2024). Guided Bayesian optimization : data-efficient controller tuning with digital twin. IEEE Transactions on Automation Science and Engineering, 22, 11304–11317. https://doi.org/10.1109/TASE.2024.3454176
• Guidetti, X., Mingard, N., Cruz-Olivera, R., Nagel, Y., Rueppel, M., Rupenyan-Vasileva, A., Balta, E. C., & Lygeros, J. (2024). Force controlled printing for material extrusion additive manufacturing. Additive Manufacturing, 89(104297). https://doi.org/10.1016/j.addma.2024.104297
• Kavas, B., Balta, E. C., Tucker, M., Rupenyan, A., Lygeros, J., & Bambach, M. (2023). Layer-to-layer closed-loop feedback control application for inter-layer temperature stabilization in laser powder bed fusion. Additive Manufacturing, 78(103847). https://doi.org/10.1016/j.addma.2023.103847
• König, C., Ozols, M., Makarova, A., Balta, E. C., Krause, A., & Rupenyan, A. (2023). Safe risk-averse bayesian optimization for controller tuning. IEEE Robotics and Automation Letters. https://doi.org/10.1109/LRA.2023.3325991

Book chapters, peer-reviewed

Rupenyan, A., & Balta, E. C. (2023). Robotics and manufacturing automation. In The impact of automatic control research on industrial innovation : enabling a sustainable future (pp. 169–189). Wiley.

Written conference contributions, peer-reviewed

• Wu, M., Rupenyan, A., & Corves, B. (2025). Singularity-avoidance control of robotic systems with model mismatch and actuator constraints [Conference paper]. 2025 European Control Conference (ECC), 2545–2550. https://doi.org/10.23919/ecc65951.2025.11187077
• Li, J., Zagorowska, M., De Pasquale, G., Rupenyan-Vasileva, A., & Lygeros, J. (2024, November 6). Safe time-varying optimization based on Gaussian processes with spatio-temporal kernel. Conference on Neural Information Processing Systems, NeurIPS 2024, Vancouver, Canada, 10-15 December 2024. https://doi.org/10.21256/zhaw-31795
• Yan, J., Chakrabarty, A., Rupenyan, A., & Lygeros, J. (2024). MPC of uncertain nonlinear systems with meta-learning for fast adaptation of neural predictive models [Conference paper]. IEEE 20th International Conference on Automation Science and Engineering (CASE), 1910–1915. https://doi.org/10.1109/CASE59546.2024.10711717
• Zagorowska, M., Ortmann, L., Rupenyan-Vasileva, A., Mercangöz, M., & Imsland, L. (2024). Tuning of Online Feedback Optimization for setpoint tracking in centrifugal compressors [Conference paper]. IFAC-PapersOnLine, 58(14), 881–886. https://doi.org/10.1016/j.ifacol.2024.08.448

Oral conference contributions and abstracts

• Rupenyan, A., & Sawicki, B. (2025). From research to practice in manufacturing : interactive session I [Conference presentation]. 2025 European Control Conference (ECC), 3013. https://doi.org/10.23919/ecc65951.2025.11187228
• Rupenyan, A. (2025). From research to practice in manufacturing [Conference presentation]. 2025 European Control Conference (ECC), 3010. https://doi.org/10.23919/ecc65951.2025.11186949

Publications before appointment at the ZHAW

An up-to-date list of publications can be found on Google Scholar.

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