Dr. Alisa Rupenyan-Vasileva

Arbeit an der ZHAW

Tätigkeit

Rieter Stiftungsprofessur Industrial AI

Arbeits- und Forschungsschwerpunkte

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

Lehrtätigkeit

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

Berufserfahrung

• 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

Aus- und Weiterbildung

Ausbildung

• 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

Netzwerk

Mitglied in Netzwerken

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

ORCID digital identifier

ORCID ID: 0000-0002-2170-8564

Projekte

• Continuous optimization and control for advanced manufacturing / Projektleiter:in / laufend
• Digital Manufacturing as a Service Technology / Projektleiter:in / laufend
• Smarte Grünanlagen / Teammitglied / laufend
• Intelligent planning for robot-based manufacturing / Projektleiter:in / laufend

Publikationen

• Liao-McPherson, Dominic; Balta, Efe C.; Afrasiabi, Mohamadreza; Rupenyan-Vasileva, Alisa; Bambach, Markus; Lygeros, John,

  2024.

  Layer-to-layer melt pool control in laser powder bed fusion.

  IEEE Transactions on Control Systems Technology.

  Verfügbar unter: https://doi.org/10.1109/TCST.2024.3464118

• Nobar, Mahdi; Keller, Jürg; Rupenyan, Alisa; Khosravi, Mohammad; Lygeros, John,

  2024.

  Guided Bayesian optimization : data-efficient controller tuning with digital twin.

  IEEE Transactions on Automation Science and Engineering.

  Verfügbar unter: https://doi.org/10.1109/TASE.2024.3454176

• Guidetti, Xavier; Mingard, Nathan; Cruz-Olivera, Raul; Nagel, Yannick; Rueppel, Marvin; Rupenyan-Vasileva, Alisa; Balta, Efe C.; Lygeros, John,

  2024.

  Force controlled printing for material extrusion additive manufacturing.

  Additive Manufacturing.

  89(104297).

  Verfügbar unter: https://doi.org/10.1016/j.addma.2024.104297

• König, Christopher; Ozols, Miks; Makarova, Anastasia; Balta, Efe C.; Krause, Andreas; Rupenyan, Alisa,

  2023.

  Safe risk-averse bayesian optimization for controller tuning.

  IEEE Robotics and Automation Letters.

  Verfügbar unter: https://doi.org/10.1109/LRA.2023.3325991

• Kavas, Barış; Balta, Efe C.; Tucker, Michael; Rupenyan, Alisa; Lygeros, John; Bambach, Markus,

  2023.

  Layer-to-layer closed-loop feedback control application for inter-layer temperature stabilization in laser powder bed fusion.

  Additive Manufacturing.

  78(103847).

  Verfügbar unter: https://doi.org/10.1016/j.addma.2023.103847

• Rupenyan, Alisa; Balta, Efe C.,

  2023.

  Robotics and manufacturing automation

  .

  In:

  The impact of automatic control research on industrial innovation : enabling a sustainable future.

  Wiley.

  S. 169-189.

• Li, Jialin; Zagorowska, Marta; De Pasquale, Giulia; Rupenyan-Vasileva, Alisa; Lygeros, John,

  2024.

  Safe time-varying optimization based on Gaussian processes with spatio-temporal kernel [Paper].

  In:

  Conference on Neural Information Processing Systems, NeurIPS 2024, Vancouver, Canada, 10-15 December 2024.

  Vancouver:

  NeurIPS.

  Verfügbar unter: https://doi.org/10.21256/zhaw-31795

• Yan, Jiaqi; Chakrabarty, Ankush; Rupenyan, Alisa; Lygeros, John,

  2024.

  MPC of uncertain nonlinear systems with meta-learning for fast adaptation of neural predictive models [Paper].

  In:

  IEEE 20th International Conference on Automation Science and Engineering (CASE).

  IEEE 20th International Conference on Automation Science and Engineering (CASE), Bari, Italy, 28 August - 1 September 2024.

  IEEE.

  S. 1910-1915.

  Verfügbar unter: https://doi.org/10.1109/CASE59546.2024.10711717

• Zagorowska, Marta; Ortmann, Lukas; Rupenyan-Vasileva, Alisa; Mercangöz, Mehmet; Imsland, Lars,

  2024.

  Tuning of Online Feedback Optimization for setpoint tracking in centrifugal compressors [Paper].

  In:

  12th IFAC Symposium on Advanced Control of Chemical Processes (ADCHEM), Toronto, Canada, 14-17 July 2024.

  Elsevier.

  S. 881-886.

  Verfügbar unter: https://doi.org/10.1016/j.ifacol.2024.08.448

Publikationen vor Tätigkeit an der ZHAW

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

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