Thesis Talks 2019 (part 1)

Hear 14 excellent students present their thesis projects in a TED-talk inspired format open to everyone interested.

Can games help us protect the ocean from pollution? How will machine learning turn medical data into a goldmine? Are laptops our school children's friend or foe? And how will digital healthcare solutions empower patients and relatives in the future?

These questions and many others will be answered at Thesis Talks 2019, September 12 and 19, at ITU.

A thesis is the result of months of hard work. Unfortunately, the new knowledge often stays between the student and the supervisor. This is why we at ITU are proud to present Thesis Talks where 14 excellent former students will present their research and results over two days.

Thesis Talks are presentations inspired by TED-talks, where each project will be presented in ten minutes.

The event is open for everyone, in English and it’s free of charge. Just remember to sign up here.

We’re looking forward to see you!
 
NB. This is the first of two events. The other one is on September 19.

 

Programme

16.00-16.05: Welcome by ITU Alumni
16.05-16.50: Talks – round 1 (4 presentations)
16.50-17.20: Open Space: questions, networking and light refreshments
17.20-18.00 Talks – round 2 (3 presentations)
18.00-18.30: Open Space: questions, networking and light refreshments
 

Speaker list: September 12

Anna Danielsen & Frederikke Sommer Jagd (DDK): "Designing the Future of Healthcare - Bridging the Gap Between Relatives and Hospital Staff"

Emil Sunesen (DIM): "Re-organize to succeed with technology innovation"

Sebastian Baunsgaard & Sebastian B. Wrede (CS): "Speech Recognition: For Everyone or Only Big Companies?"

 
Sarah Grossi (Games): "An error occurred: failed to play with conventions"
 
Anne Louise Slott Thorborg (DDK): "Laptops and school children: Friends or foes?"
 
Karolina F. Oppheim & Roosa K. Murto (DIM): "Exploring the transition to green and efficient Energy"
 
Nicola Zaltron & Luisa Zurlo (Games): "Interactive Evolutionary GAN: A novel GAN-based approach for facial composite generation in criminal investigation"

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