SCIENCE AI Centre

Previous Events

11 Nov. 2022, 9:30-17:00

Learning through XR

Hear cases and exchange best practice on how we can create the best learning experiences in Virtual Reality, Augmented Reality or Mixed Reality – the world of XR.

7 Nov. - 8 Nov. 2022

DDSA Conference: Danish Data Science 2022

4 Nov. 2022, 15:00-16:00

Pioneer Centre for AI Talk: Dr. Enzo Ferrante

Pioneer Centre for AI talk by Enzo Ferrante: Fairness of machine learning in medical image analysis

31 Oct. - 2 Nov. 2022

Nordic Conference on Law and Information Technology 2022

The 37th Nordic Conference on Law and Information Technology on "Humans, data and law: tectonic plates in motion" will take place from the 31.10.2022-2.11.2022.

25 Oct. - 26 Oct. 2022

Digital Tech Summit 2022

KU er stærkt repræsenteret med talere til dette års Digital Tech Summit konference 25. og 26. oktober i Bella Center

13 Oct. 2022, 13:00-14:30

Pioneer Centre for AI Talk: Fisher Yu

Pioneer Centre for AI Talk by Fisher Yu: Towards Complete 4D Scene Understanding

10 Oct. 2022, 10:00-11:00

DeLTA seminar by Yi-Shan Wu

The DeLTA Lab from the Department of Computer Science, University of Copenhagen, holds another seminar titled 'Split-kl and PAC-Bayes-split-kl Inequalities ' by Yi-Shan Wu.

7 Oct. 2022, 13:00

AI Seminar: Human-Centered Natural Language Processing

On 7 October 2022, Andrew Schwartz, Associate Professor at Department of Computer Science, Stony Brook University, will give a talk titled 'Human-Centered Natural Language Processing'.

3 Oct. 2022, 10:00-11:00

DeLTA seminar by Saeed Masoudian

On 3 October the DeLTA Lab from the Department of Computer Science, University of Copenhagen, holds a seminar titled 'A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback' by Saeed Masoudian.

30 Sept. 2022, 13:00

AI Seminar: Big data for predicting student success - limits and policy potential

On 30 September 2022, Andreas Bjerre-Nielsen, Associate Professor at Department of Economics and member of SODAS, University of Copenhagen, will give a talk titled 'Big data for predicting student success - limits and policy potential'.