Name: Bernard

Surname: ZENKO

Section: Department of Knowledge Technologies Jožef Stefan Institute

Qualification: Finished
• The Human Brain Project – Specific Grant Agreement 1, EU H2020 FET Flagships, 2016–2018. (co-PI)
• MAESTRA – Learning from Massive, Incompletely annotated, and Structured Data, EU FP7, 2014–2017.
• The Human Brain Project – Rump-Up Phase, EU FP7 FET Flagships, 2014–2016.
• REWIRE – Rehabilitative Wayout In Responsive home Environments, EU FP7, 2011–2014. (co-PI)
• EET-Pipeline – European Embryonal Tumor Pipeline, EU FP6, 2007–2009.
• IQ – Inductive Queries for Mining Patterns and Models, EU FP6, 2005–2008.
• EMECAP – European Mercury Emission from Chlor-Alkali Plants, EU FP5, 2003–2004.
• MetaL – A Meta-Learning Assistant for Providing User Support in Machine Learning Mining, ESPRIT IV, EU FP4, 2000–2002.

Education and career

Bernard Ženko Department of Knowledge Technologies Jožef Stefan Institute About Me I am a research associate at Department of Knowledge Technologies at the Jožef Stefan Institute. My interests are related to artificial intelligence, machine learning and their application to practical problems including ambient assisted living and environmental and life sciences. My work includes methods for combining multiple classifiers, learning rule-based models for predicting structured variables and network reconstruction.
Interests
• Artificial Intelligence
• Machine Learning
• Data Mining
Education
• PhD in Computer Science, 2007 University of Ljubljana
• MSc in Computer Science, 2003 University of Ljubljana
• BSc in Electrical Engineering, 2000 University of Ljubljana
Projects
Ongoing
• KET4CP-MPT – Machine vision quality control of molded plastic parts, MPT, since 2019.
• TOPP – Transparent design of optimal underground connections for smart cities using artificial intelligence technologies, Elea iC, since 2019. (co-PI)
• SAAM – Supporting Active Ageing through Multimodal coaching, EU H2020, since 2017. (co-PI, Technical Manager)
• F4F – Food for Future (Funkcionalna živila prihodnosti), Smart specialisation, EU and RS, since 2017. (PI)
Finished
• The Human Brain Project – Specific Grant Agreement 1, EU H2020 FET Flagships, 2016–2018. (co-PI)
• MAESTRA – Learning from Massive, Incompletely annotated, and Structured Data, EU FP7, 2014–2017.
• The Human Brain Project – Rump-Up Phase, EU FP7 FET Flagships, 2014–2016.
• REWIRE – Rehabilitative Wayout In Responsive home Environments, EU FP7, 2011–2014. (co-PI)
• EET-Pipeline – European Embryonal Tumor Pipeline, EU FP6, 2007–2009.
• IQ – Inductive Queries for Mining Patterns and Models, EU FP6, 2005–2008.
• EMECAP – European Mercury Emission from Chlor-Alkali Plants, EU FP5, 2003–2004.
• MetaL – A Meta-Learning Assistant for Providing User Support in Machine Learning Mining, ESPRIT IV, EU FP4, 2000–2002.
Publications
Latest
Miha Hafner, David Rajšter, Marko Žibert, Tea Tušar, Bernard Ženko, Martin Žnidaršič, Flavio Fuart, Daniel Vladušič (2019). Artificial intelligence support for tunnel design in urban areas. Tunnels and Underground Cities. Engineering and Innovation Meet Archaeology, Architecture and Art. World Tunnel Congress. Lidija Strojnik, Matej Stopar, Emil Zlatič, Doris Kokalj, Mateja Naglič Gril, Bernard Ženko, Martin Žnidaršič, Marko Bohanec, Biljana Mileva Boshkovska, Mitja Luštrek, Anton Gradišek, Doris Potočnik, Nives Ogrinc (2019). Authentication of key aroma compounds in apple using stable isotope approach. Food chemistry. Matej Petković, Redouane Boumghar, Martin Breskvar, Sašo Džeroski, Dragi Kocev, Jurica Levatić, Luke Lucas, Aljaž Osojnik, Bernard Ženko, Nikola Simidjievski (2019). Machine learning for predicting thermal power consumption of the Mars Express spacecraft. IEEE Aerospace and Electronic Systems Magazine. Martin Žnidaršič, Bernard Ženko, Aljaž Osojnik, Marko Bohanec, Panče Panov, Helena Burger, Zlatko Matjačić, Mojca Debeljak (2019). Multi-criteria modelling approach for ambient assisted coaching of senior adults. International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. Marc Grau Leguia, Zoran Levnajić, Ljupčo Todorovski, Bernard Ženko (2019). Reconstructing dynamical networks via feature ranking. Chaos.
Contact
• bernard.zenko@ijs.si
• +386 (0)1 477 3160
• +386 (0)1 477 3315
• Jamova cesta 39, Ljubljana, SI-1000
• Main Building, Second Floor, Office S18
• Skype Me