Dr. Ignasi Ventura Nadal

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Biography

Ignasi Ventura Nadal is a PhD student at the Technical University of Denmark (DTU). His research primarily focuses on physics-informed neural networks and trustworthy artificial intelligence in power systems. Ignasi is involved in various projects, including the VeriPhIED project, which aims to optimize non-linear power system stability through verified physics-aware machine learning. His collaboration with notable supervisors and participants highlights his commitment to advancing the field of machine learning in energy systems. Ignasi is actively engaged in research that aligns with the UN Sustainable Development Goals, emphasizing poverty alleviation, environmental protection, and sustainable prosperity.

Research Interests

Physics-Informed Neural Networks Trustworthy AI Non-linear Power System Stability Optimization Machine Learning in Energy Systems

Experience

PhD Student

2023-09-01 — 2026-08-31

Technical University of Denmark • Kgs. Lyngby, Denmark

Engaged in research on verified physics-aware machine learning for non-linear power system stability optimization.

Requirements for Technical University of Denmark

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Listening
Required:6.5
Reading
Required:6.5
Writing
Required:6.5
Speaking
Required:6.5
Overall
Required:6.5
TOEFL
Listening
Required:20
Reading
Required:20
Writing
Required:20
Speaking
Required:20
Total
Required:88
Prerequisites
Bachelor of Science in Engineering or equivalent Strong background in Mathematics and Physics
Application Checklist
  • Official Bachelor's degree diploma
  • Official transcripts of records
  • Statement of purpose
  • Curriculum Vitae (CV)
  • Documentation of English proficiency
  • Copy of passport
Specialization Notes

This requirement applies generally across Technical University of Denmark (DTU) MSc programs including Computer Science, Applied Mathematics, and Engineering disciplines. Specific prerequisites vary by department/curriculum.