International Mobility for PhD Students: Key Learnings
We report on a trans-Atlantic PhD student mobility program that connects two graduate research training initiatives in the US and Ireland, centered on developing future researchers in artificial intelligence (AI) and machine learning (ML). We discuss both the structure of the student exchange experiences and share key learnings from this international collaboration. The most important lesson learned is that providing a structured mobility program and matched visiting pairs is a highly effective way to improve learning outcomes compared to more typical ad-hoc individual visits.
Authors
- Ferat Sahin (ORCID: https://orcid.org/0000-0002-9813-7165)
- Reynold Bailey (ORCID: https://orcid.org/0000-0001-8964-9663)
- Georgiana Ifrim (ORCID: https://orcid.org/0000-0002-8400-2972)
- Sarah Jane Delany (ORCID: https://orcid.org/0000-0002-2062-7439)
- Cecilia Ovesdotter Alm (ORCID: https://orcid.org/0000-0002-8730-0916)
- Esa M. Rantanen (ORCID: https://orcid.org/0000-0001-9666-4458)
- Brian Mac Namee (ORCID: https://orcid.org/0000-0003-2518-0274)
Institutions
- University College Dublin (IE)
- Rochester Institute of Technology (US)
- Technological University Dublin (IE)
Publication Details
- Published
- 2025-02-18
- DOI
- https://doi.org/10.1145/3641555.3705204
- Primary Topic
- Migration and Labor Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.00