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Research visit to NYU

Reference number
Coordinator RISE Research Institutes of Sweden AB - RISE AB - Digitala System
Funding from Vinnova SEK 335 624
Project duration December 2022 - May 2023
Status Completed
Venture AI - Competence, ability and application
Call Staff exchange for applied AI, automation and data sharing - spring 2022

Important results from the project

The purpose of this project was to facilitate a research exchange between the Deep Learning research group at RISE and CILVR at New York University (NYU). Specifically, doctoral student Edvin Listo Zec visited Prof Kyunghyun Cho at NYU, a highly esteemed researcher in the field of deep learning. The project was successful, and the goals have been achieved with a substantial margin. Continued collaboration is planned, and new project proposals have been submitted based on the results from this project. The knowledge gained from this project will benefit Swedish industry and the public.

Expected long term effects

In this project, in addition to establishing a long-term collaboration between the research group at RISE and the research group at NYU, we have made substantial progress in formulating and addressing the concept of continual learning in a federated setting. We will continue to work along this path and develop technology based on these findings, while pushing the research frontier forward.

Approach and implementation

This project has been carried out with the funding provided by Vinnova and the generous hosting by NYU. When such conditions are in place, it becomes easy to conduct excellent research. The guidance from Professor Cho has greatly propelled Edvin´s work, and we were told that Edvin brought fresh ideas and air to the CILVR group at NYU, which is also very gratifying to hear. Everyone involved has done a remarkable job, and as a result, the outcomes have been successful.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 12 June 2023

Reference number 2022-02822