???global.info.a_carregar???
Identification

Personal identification

Full name
Rodrigo Farate Laia

Citation names

  • Laia, Rodrigo

Author identifiers

Ciência ID
2A13-D505-7FB8
ORCID iD
0009-0003-6730-9985

Websites

  • linkedin.com/in/rodrigo-laia (Social media)
  • laiarodrigo.github.io/ (Scholar)

Languages

Language Speaking Reading Writing Listening Peer-review
Portuguese (Mother tongue)
English Advanced (C1) Advanced (C1) Advanced (C1) Advanced (C1)
Education
Degree Classification
2024/10 - 2026/10
Ongoing
Computer Science and Engineering (Mestrado)
Major in Artificial Intelligence
Universidade de Lisboa Instituto Superior Técnico, Portugal
"Recognizing and Translating Between Portuguese Varieties with Fine-tuned Language Models" (THESIS/DISSERTATION)
18/20
2021/10 - 2024/09
Concluded
Physics and Technological Engineering (Licenciatura)
Universidade de Lisboa Instituto Superior Técnico, Portugal
"Machine Learning as a Tool to Improve Nuclear Fusion Experiments" (THESIS/DISSERTATION)
16/20
2023/11 - 2023/11
Concluded
Introduction to Lean Six Sigma Management (Outros)
Ceské vysoké uceni technické v Praze, Czech Republic
20/20
Affiliation

Science

Category
Host institution
Employer
2025/09 - Current Research Assistant (Research) Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa, Portugal
Universidade de Lisboa Instituto Superior Técnico, Portugal
2024/01 - 2025/12 Research Assistant (Research) University of Wisconsin-Madison, United States
University of Wisconsin-Madison, United States
2024/11 - 2025/03 Researcher (Research) Diffusion Dynamics, Portugal
Diffusion Dynamics, Portugal
2022/06 - 2022/09 Research Trainee (Research) Laboratório de Instrumentação e Física Experimental de Partículas, Portugal
Laboratório de Instrumentação e Física Experimental de Partículas, Portugal
Outputs

Publications

Journal article
  1. R. Laia; R. Jorge; G. Abreu. "Data-driven approach to model the influence of magnetic geometry in the confinement of fusion devices". Nuclear Fusion (2026): https://doi.org/10.1088/1741-4326/ae1e12.
    10.1088/1741-4326/ae1e12

Other

Software
  1. Laia, Rodrigo. "QCD Jets Visualization". Demo: https://wminho.lip.pt/qcd/. Laboratório de Instrumentação e Física Experimental de Partículas. Unity. 2023.
Activities

Oral presentation

Presentation title Event name
Host (Event location)
2024/09 Machine Learning as a Tool to Improve Nuclear Fusion Experiments FÍSICA 2024 (24th National Physics Conference & 34th Iberian Meeting for Physics Education)
Portuguese Physical Society (Coimbra, Portugal)
Distinctions

Award

2024 Academic Merit Award (2024/2025)
Universidade de Lisboa Instituto Superior Técnico, Portugal