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SnT Researcher Wins Tech Transfer Award

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Published on Tuesday, 06 June 2017

Patrick Glauner snatched the best overall project prize at the Bridging the GAP research fair for his on-going PhD project on the detection of non-technical losses using artificial intelligence. About 20 University of Luxembourg students from diverse backgrounds and degrees presented their projects on 20 may 2017. These ranged from ongoing research to case studies or entrepreneurship initiatives. Higher Education Minister Marc Hansen attended the event and listened to each project pitch. Ultimately, attendees could cast their votes in three categories: best overall project, most creative presentation and best poster.

Funded by the Fonds National de la Recherche (FNR), Glauner’s project "Spatio-Temporal Processes for Electricty Theft Detection" puts non-technical-losses (NTL) like electricity theft, faulty meters or billings errors under the microscope. These are common anomalies and make up about 40% of the total electricity distributed in some developing and emerging countries, thus harming a fragile economy. Using a machine learning model, the PhD student strives to predict whether a household causes these losses. A partnership with CHOICE Technologies Holding allows him to work with real data sets from Brazil to evaluate his models.

For most students at the Bridging the Gap fair, a challenge in itself was upholding scientific excellence while turning a convoluted concept into a palatable pitch. Patrick Glauner mastered this challenge and was able to sway attendees’ votes in his favour.

The native German is thrilled about this award: "This award represents a major recognition of my work. It is also another example of the scientific excellence within SnT thanks to the extensive collaboration with industry partners." Patrick Glauner’s current work scope aligns with his interests: "I have been in and around Big Data and machine learning for a number of years. I really enjoy my on-going PhD project because it allows us to push the boundaries of the detection of electricity theft. The main advantage of this project is that our industry partner provides us with real data. As a result, we not only publish papers, but produce outcomes that work in practice."

Patrick Glauner graduated as valedictorian from Karlsruhe University of Applied Sciences with a BSc in computer science, then went on to work at the European Organization for Nuclear Research (CERN) for three years. After graduating from Imperial College London with a MSc in machine learning, he joined SnT in late 2015.

Learn more about Glauner's research project here.