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Dr. Alisa Rupenyan-Vasileva

Dr. Alisa Rupenyan-Vasileva

Dr. Alisa Rupenyan-Vasileva

ZHAW School of Engineering

Technikumstrasse 71
8400 Winterthur

+41 (0) 58 934 43 92
alisa.rupenyan@zhaw.ch

Work at ZHAW

Position

Education and Continuing education

Focus

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

Experience

  • Group leader, Automation and control group
    inspire AG
    02 / 2018 - 07 / 2023
  • Senior scientist, Automatic control laboratory
    ETH Zurich
    08 / 2020 - 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

  • 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

Membership of networks

Projects

Publications

Articles in scientific journal, peer-reviewed
Book parts, peer-reviewed
  • 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.

    pp. 169-189.

Publications before appointment at the ZHAW

[1] P.R. Armstrong, F. Dell Endice, E.B. Maghirang, A. Rupenyan, Discriminating Oat and Groat Kernels from other Grains Using Near-Infrared Spectroscopy, Cereal Chemistry. (2017). [2] E.C. Balta, K. Barton, D.M. Tilbury, A. Rupenyan, J. Lygeros, Learning-based repetitive precision motion control with mismatch compensation, in: 2021 60th IEEE Conference on Decision and Control (CDC), IEEE, 2021: pp. 3605–3610. [3] E.C. Balta, M.H. Mamduhi, J. Lygeros, A. Rupenyan, Controller-aware dynamic network management for Industry 4.0, in: IECON 2022–48th Annual Conference of the IEEE Industrial Electronics Society, IEEE, 2022: pp. 1–6. [4] S. Balula, E.C. Balta, D. Liao-McPherson, A. Rupenyan, J. Lygeros, Sequential Quadratic Programming-based Iterative Learning Control for Nonlinear Systems, in: 2023 IEEE Conference on Control Technology and Applications (CCTA), IEEE, 2023: pp. 162–167. [5] S. Balula, D. Liao-McPherson, A. Rupenyan, J. Lygeros, Data-driven Reference Trajectory Optimization for P