Open AI Days
Inspirational Days & Master Thesis Awards
Open AI Days
Since its establishment in 2017, NAIL has organized several Open AI Days and Inspirational Days. These are dissemination events that aim to spread knowledge about AI and inspire businesses and public sector organisations to explore the potential of AI.
These events take place twice a year; in spring and autumn. In the spring semester, companies and organizations can pitch potential master's thesis topics for cooperation with students. In autumn, we organize the best AI Master's Thesis Awards.
An important objective for hosting these events is to provide an arena for connecting researchers, partners, students and other AI enthusiasts, in order to exchange ideas and experiences regarding the many potential applications of AI.
2021 AI Masters thesis awards
The top AI theses of 2021 awarded
Artificial Intelligence is a popular topic among students at NTNU. In recent years, around 200 master’s theses in which AI plays a substantial part have been submitted yearly. On December 3rd, we celebrated the top AI theses of 2021 in an awards ceremony at Gløshaugen.
Sindre Stenen Blakseth, a 2021 graduate from the Department of Physics, was the lucky winner of the 2021 AI Master’s thesis awards.
Learn more about this year's AI Master's thesis awards by reading this article.
Inspirational Day October 24
Inspirational Day and Master Thesis Awards, fall 2019
The 2019 AI Inspirational Day and Master Thesis Awards took place in Trondheim, October 24th.
The program included short AI talks - both on theory and application, given by researchers and industry. Three talented, former NTNU students (that you can see in the photo above) were awarded for the best master theses of 2019. You can find more photos from the event here.
Master Thesis Award 2018
Winners of the Master's Thesis Awards 2018
The winner of best master thesis in the category application, was Andreas Bell Martinsen, with the thesis End-to-end training for path following and control of marine vehicles, supervised by Anastasios Lekkas. In the photo above, you can see Andreas, together with Kerstin Bach and Massimiliano Ruocco.
The winners of best thesis in the category theoretical, were Are Haartveit and Harald Musum. Their thesis Learning event-driven time series with phased recurrent neural networks was supervised by Keith Downing.
masters thesis awards 2020
Master's thesis awards 2020
Artificial Intelligence is a popular topic among students at NTNU. In fact, more than 200 master's students who graduated from the Faculty of Information Technology and Electrical Engineering last year submitted a thesis in which AI plays a substantial part. On December 15th, we celebrated the top AI theses of 2020 in a digital event.
Out of the 10 nominations, the evaluation committee selected the top three theses. The authors of these theses: Eivind Meyer, Herman Dieset and Amund Tenstad, were invited to present their work during the awards event, December 15. Eivind Meyer, a graduate from Department of Engineering Cybernetics, was the lucky winner. You can learn more about the event by reading this article.
Inspirational Day Spring 2019 Pre Event
In the evening of March 21, we organized a pre event where a few graduate students presented their master thesis work. The presentations had different topics, focusing on both theoretical and applied AI. All students did an impressive job and were able to engage the audience into lively discussions.
After the presentations, the discussions continued during a networking dinner, where researchers, participants from different companies and organizations, and the students were able to get to know each other.
Master Thesis Award 2018
Inspirational Day and Master's Thesis Awards, fall 2018
The Inspirational Day fall 2018, took place November 15 had two parts; the first part included presentations about AI research and on how to apply AI in industry and business. The second part was the Master Thesis Award, awarding the best AI master theses written at NTNU that year.
The event also provided great networking opportunities between students, researchers and others interested in AI.