Scholar
Fernando E. Rosas
Google Scholar ID: OZNAs2wAAAAJ
Lecturer at University of Sussex
Citations & Impact
Citations
6,131
H-index
40
i10-index
95
Publications
20
Co-authors
107
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Insufficient information
Research Experience
- - Lecturer in Computer Science and AI, University of Sussex, UK, Sep 2022 - Present
- - Honorary Research Fellow, Department of Brain Sciences, Imperial College London, UK, 18 Sep 2022 - Present
- - Research Associate / Academic Research Fellow, Department of Brain Sciences and Data Science Institute, Imperial College London, UK, 1 May 2019 - 31 Aug 2022
- - Marie Skłodowska-Curie Research Fellow, Department of Mathematics and Department of Electrical Engineering, Imperial College London, UK, 1 May 2017 - 30 Apr 2019
- - Postdoctoral Fellow, Laboratory of Wireless Broadband Communication, National Taiwan University, Taipei, Taiwan, 7 Mar 2016 - 30 Dec 2016
- - Postdoctoral Research Assistant, MICAS, Electric Engineering Department, KU Leuven, Belgium, 3 Mar 2014 - 26 Feb 2016
Education
- - Ph.D. in Engineering Sciences, Pontificia Universidad Católica de Chile
- - Master in Engineering Sciences, Pontificia Universidad Católica de Chile
- - BSc. in Mathematics, Pontificia Universidad Católica de Chile
- - BA. in Music Composition, Pontificia Universidad Católica de Chile
- - Minor degree in Philosophy, Pontificia Universidad Católica de Chile
Background
- His work focuses on the analysis of distributed complex systems, addressing problems at the interface between computational neuroscience, artificial intelligence, and complexity science. His work aims to reveal the principles that drive the computations performed by distributed multi-agent systems, which somehow allow them to become more than the sum of their parts — performing tasks collectively that couldn't be achieved individually, and even give rise to novel features that were not predefined beforehand. The main focus of his current work is how these ideas can advance our understanding of ensuring AI alignment and safety.
Miscellany
- Insufficient information
