Dr. Lilach Goren Huber

Personal profile

Position at the ZHAW

Research associate

Expertise and research interests

Machine learning algorithms
Deep learning
Time series analysis
Condition monitoring
Condition based maintenance
Predictive maintenance
Fault detection and isolation
Maintenance scheduling optimization
Aging models

Educational background

2006-2011 PhD in physics, The Weizmann Institute of Science, Israel
2003-2005 M.Sc in physics, The Weizmann Institute of Science, Israel
1999-2002 B.Sc in physics, The Hebrew University, Jerusalem

Professional milestones

2011-2012 Physicist and Algorithm Developer, Pentalum Technologies
2004-2011 Research assistant at the Weizmann Institute of Science

Projects

• End-to-End Data Driven Design of After-Sales-Services for Digital Cutters / Team member / Project ongoing
• Intelligente Diagnostik von Leistungseinbussen in Solarkraftwerken / Project leader / Project ongoing
• Data Driven Energy Efficiency / Team member / Project completed
• Automatisierte Datenselektion für Anomalieerkennung anhand maschinellen Lernens / Project leader / Project completed
• Expert Group Smart Maintenance / Project leader / Project completed
• Convolutional Neural Network Algorithmen für Fehlererkennung bei Windturbinen / Project leader / Project completed
• Datenanalyse der potentiellen Senkung der Auslastenergie der Stadt Winterthur. / Project leader / Project completed
• Machine Learning Based Fault Detection for Wind Turbines / Project leader / Project completed
• Optimierte Entscheidungsfindung für das Asset-Management von Infrastrukturnetzen / Project leader / Project completed
• Decision Support System for Predictive Maintenance of Laser Cutting Machines / Project leader / Project completed
• Optimierung der Instandhaltungsplanung von Wasserkraftanlagen / Project leader / Project completed
• Risk Based Maintenance auf Schweizer Nationalstrassen / Team member / Project completed
• Energy Optimization for Vessel Operations / Team member / Project completed
• Entwicklung einer Methodik für optimiertes Flottenmanagement / Team member / Project completed
• RENERG2 - RENewable enERGies in future energy supply / Team member / Project completed
• Optimiertes Asset Management von Infrastrukturnetzen / Team member / Project completed

Publications

• Lehmann, Claude; Goren Huber, Lilach; Horisberger, Thomas; Scheiba, Georg; Sima, Ana-Claudia; Stockinger, Kurt,

  2020.

  Big data architecture for intelligent maintenance : a focus on query processing and machine learning algorithms.

  Journal of Big Data.

  7(1).

  Available from: https://doi.org/10.1186/s40537-020-00340-7

• Goren Huber, Lilach; Kunz, Simon; Dettling, Marcel,

  2018.

  Condition-based maintenance decision making : a practical approach for marine vessels.

  International Journal of COMADEM.

  21(3), pp. 15-20.

  Available from: https://apscience.org/comadem/index.php/comadem/article/view/93

• Zgraggen, Jannik; Guo, Yuyan; Notaristefano, Antonio; Goren Huber, Lilach,

  2022.

  Physics informed deep learning for tracker fault detection in photovoltaic power plants [paper].

  In:

  Kulkarni, Chetan; Saxena, Abhinav, eds.,

  Proceedings of the Annual Conference of the PHM Society 2022.

  14th Annual Conference of the Prognostics and Health Management Society, Nashville, USA, 1-4 November 2022.

  PHM Society.

  Available from: https://doi.org/10.36001/phmconf.2022.v14i1.3235

• Zgraggen, Jannik; Pizza, Gianmarco; Goren Huber, Lilach,

  2022.

  Uncertainty informed anomaly scores with deep learning : robust fault detection with limited data [paper].

  In:

  Do, Phuc; Michau, Gabriel; Ezhilarasu, Cordelia, eds.,

  Proceedings of the 7th European Conference of the Prognostics and Health Management Society 2022.

  7th European PHM, Turin, Italy, 6-8 July 2022.

  State College:

  PHM Society.

  pp. 530-540.

  PHM Society European Conference ; 7.

  Available from: https://doi.org/10.36001/phme.2022.v7i1.3342

• Zgraggen, Jannik; Ulmer, Markus; Jarlskog, Eskil; Pizza, Gianmarco; Goren Huber, Lilach,

  2021.

  Transfer learning approaches for wind turbine fault detection using deep learning [paper].

  In:

  Proceedings of the European Conference of the PHM Society 2021.

  6th European Conference of the Prognostics and Health Management Society, online, 28 June - 2 July 2021.

  PHM Society.

  pp. 12.

  Available from: https://doi.org/https://papers.phmsociety.org/index.php/phme/issue/archive

• Ulmer, Markus; Jarlskog, Eskil; Pizza, Gianmarco; Goren Huber, Lilach,

  2021.

  Deep learning for fault detection : the path to predictive maintenance of wind turbines [paper].

  In:

  Sammelband zu den 6. Energieforschungsgesprächen Disentis.

  Energieforschungsgespräche Disentis 2021, online, 20.-22. Januar 2021.

  Disentis:

  Stiftung Alpines Energieforschungscenter AlpEnForCe.

  pp. 24-26.

• Ulmer, Markus; Jarlskog, Eskil; Pizza, Gianmarco; Goren Huber, Lilach,

  2020.

  Cross-turbine training of convolutional neural networks for SCADA-based fault detection in wind turbines [paper].

  In:

  Proceedings of the Annual Conference of the PHM Society 2020.

  12th Annual Conference of the PHM Society, virtual, 9-13 November 2020.

  PHM Society.

  Available from: https://doi.org/10.36001/phmconf.2020.v12i1.1205

• Ulmer, Markus; Jarlskog, Eskil; Pizza, Gianmarco; Manninen, Jaakko; Goren Huber, Lilach,

  2020.

  Early fault detection based on wind turbine SCADA data using convolutional neural networks [paper].

  In:

  PHME 2020 : Proceedings of the 5th European Conference of the PHM Society.

  5th European Conference of the Prognostics and Health Management Society, Virtual Conference, 27-31 July 2020.

  PHM Society.

  Available from: https://doi.org/10.21256/zhaw-20433

• Pizza, Gianmarco; Notaristefano, Antonio; Fabbri, Gregory Sean; Goren Huber, Lilach,

  2020.

  An AI-based fault detection model using alarms and warnings from the SCADA system [poster].

  In:

  Proceedings of the WindEurope Technology Workshop 2020.

  WindEurope Technology Workshop 2020 : Resource Assessment & Analysis of Operating Wind Farms, online, 8-11 June 2020.

  WindEurope.

• Goren Huber, Lilach; Kunz, Simon; Dettling, Marcel,

  2017.

  Condition-based maintenance decision making : a practical approach for marine vessels [paper].

  In:

  30th Conference for Condition Monitoring and Diagnostic Engineering Management, Lancashire, United Kingdom, July 2017.

  Lancashire:

  Jost Institute for Tribotechnology.

  pp. 357-365.

• Heitz, Christoph; Goren, Lilach; Sigrist, Jörg,

  2016.

  Decision making in asset management : optimal allocation of resources for maximizing value realization [paper].

  In:

  Proceedings of the 10th World Congress on Engineering Asset Management (WCEAM 2015).

  WCEAM 2015, Tampere, Finland, 28-30 September 2015.

  Cham:

  Springer.

  pp. 259-268.

  Lecture Notes in Mechanical Engineering.

  Available from: https://doi.org/10.1007/978-3-319-27064-7_25

• Goren Huber, Lilach; Notaristefano, Antonio,

  2022.

  Predictive Maintenance mit Physics-Informed-Deep-Learning : Anwendungsfall Photovoltaikanlagen.

  fmpro service.

  2022(3), pp. 24-25.

  Available from: https://doi.org/10.21256/zhaw-25292

• Goren Huber, Lilach; Pizza, Gianmarco,

  2021.

  Deep Learning und Predictive Maintenance : Anwendungsfall Windturbinen.

  fmpro service.

  2021(6), pp. 6-8.

• Schtalheim, Uri; Ott, Stefan; Heitz, Christoph; Goren Huber, Lilach,

  2019.

  Risk Based Maintenance (RBM) : Minimierung der Nutzerrisiken und Betriebskosten mit einer risikobasierten Methode für den Unterhalt der BSA.

  Forschungsbericht

  ; 1648.

  Bern:

  Bundesamt für Strassen.

  Available from: https://doi.org/10.21256/zhaw-3341

• Goren Huber, Lilach; Dettling, Marcel; Kunz, Simon; Gsponer, Daniel,

  2017.

  Predictive Maintenance zum effizienten Betrieb von Hochsee-Schiffen.

  fmpro service.

  pp. 9-11.

• Goren Huber, Lilach; Heitz, Christoph; Sigrist, Jörg,

  2014.

  Anlagenbewirtschaftung und Nutzenmaximierung.

  fmpro service.

  2014(2), pp. 22-23.

  Available from: https://doi.org/10.21256/zhaw-1886

• Heitz, Christoph; Goren Huber, Lilach,

  2014.

  On the economics of asset management [paper].

  In:

  Grubbström, Robert W.; Hinterhuber, Hans H., eds.,

  Eighteenth international working seminar on production economics : pre-prints.

  18th International Working Seminar on Production Economics, Innsbruck, 24-28 February 2014.

  Innsbruck:

  Kongresszentrum IGLS.

  pp. 89-102.

  Available from: https://doi.org/10.21256/zhaw-1893

• Goren Huber, Lilach,

  2022.

  Scaling-up deep learning based predictive maintenance for commercial machine fleets : a case study.

  In:

  9th Swiss Conference on Data Science (SDS), Lucerne, Switzerland, 22.-23. Juni 2022.

• Goren Huber, Lilach; Acquaviva, Michele; Pizza, Gianmarco,

  2021.

  Implementing AI-based innovation in industry.

  In:

  Live-Case-Workshop for EMBA Digital Transformation, University Zurich, 6 July 2021.

• Goren Huber, Lilach,

  2021.

  Implementing smart maintenance in industry : deep learning for wind turbine fault detection.

  In:

  Expert Group "Smart Maintenance" Meeting, online, 18 March 2021.

• Goren Huber, Lilach,

  2020.

  Intelligente Instandhaltung : Chancen und Herausförderungen für die Umsetzung in der Praxis.

  In:

  Smart Maintenance Konferenz, Maintenance Messe, Zürich Oerlikon, 12. - 13. Februar 2020.

  Available from: https://www.maintenance-schweiz.ch/en/smart-maintenance-conference/

Publications before appointment at the ZHAW

Lilach Goren and Ehud Altman, "Enhancement of the critical temperature in cuprate superconductors by inhomogeneous doping." Physical Review B 84, 094508 (2011).

Lilach Goren and Ehud Altman, "Quenching the Superconducting State of Cuprate Compounds with Electric Currents: A Variational Study." Physical review letters 104, 257002 (2010).

Lilach Goren and Ehud Altman, "Enhancement of the superconducting transition temperature in cuprate heterostructures." Physical Review B 79, 174509 (2009).

Lilach Goren, Eros Mariani, and Ady Stern, "Probing the superfluid–Mott-insulating shell structure of cold atoms by parametric excitations." Physical Review A 75,063612 (2007).

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