Dr. Juan Nieves Sanchez

Associate Professor

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Biography

Juan Carlos Nieves Sanchez is an Associate Professor at Umeå University, specialized in Artificial Intelligence. He serves as the Programme Director for the MSc programme in AI and is a member of the council for Doctoral Education in Computer Science. With extensive research qualifications as a Docent, he is recognized for his contributions to the international scientific community, particularly in the areas of human decision-making and the theoretical foundations of AI. His work includes participation in significant research projects funded by the EU, where he has played a pivotal role as an external advisor and reviewer. He organizes international workshops and tutorials, contributes to various journals, and serves as a guest editor for themed issues. His research focuses on developing trustworthy AI models for diverse applications such as energy management and personalized healthcare. In addition to his academic responsibilities, he is an advocate for integrating ethical considerations into AI education and a leader in research on responsible AI.

Research Interests

Experience

Associate Professor

2018-09-01 — Present

Umeå University • Umeå

Teaching and conducting research in Artificial Intelligence, leading projects on trustworthy AI.

Requirements for Umeå University

Master Program
Requirements
GPA Requirement
Required:2.5
IELTS
Listening
Required:5.5
Reading
Required:5.5
Writing
Required:5.5
Speaking
Required:5.5
Overall
Required:6.5
TOEFL
Writing
Required:20
Total
Required:90
PTE
Overall
Required:62
Prerequisites
Bachelor's degree (180 ECTS) in relevant field At least 90 ECTS in the main subject area
Application Checklist
  • Bachelor's degree certificate
  • Transcripts of records
  • Proof of English proficiency
  • Copy of passport
  • Letter of Motivation (certain programs)
  • CV (certain programs)
Specialization Notes

Requirements are standard for Master's programs across Social Sciences and Humanities at Umeå. English 6 proficiency is the general rule.