Dr. Kevin Van Den Eynde

Assistant Professor

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Biography

Kevin Van Den Eynde is a researcher at KU Leuven. His academic work primarily focuses on machine learning and artificial intelligence applications in healthcare. With a strong background in computer science, he has published numerous papers contributing to the understanding of automated decision support systems. Kevin actively collaborates with healthcare professionals to design systems that improve patient outcomes through predictive modeling and data analysis. His research interests also encompass issues related to ethical AI deployment, ensuring that technology is used responsibly in sensitive sectors such as medicine. Kevin actively participates in conferences and workshops, sharing insights and findings from his research with the broader academic community. He is committed to fostering innovation within interdisciplinary teams, leveraging computational techniques to tackle real-world healthcare challenges.

Research Interests

Experience

Researcher

2011-01-01 — Present

KU Leuven • Leuven

Conducting research in machine learning applications for healthcare.

Awards

#

Research Excellence Award

2020-06-01

Requirements for KU Leuven

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:7
TOEFL
Listening
Required:22
Reading
Required:22
Writing
Required:22
Speaking
Required:22
Total
Required:94
GRE General
Verbal
Required:154
Quantitative
Required:166
Overall
Required:154
Prerequisites
Academic Bachelor's programme in Engineering Science with strong components in computer science and mathematics Bachelor's degree in Informatics or Computer Science with a strong component of mathematics
Application Checklist
  • Official transcripts
  • Summary of Key Application Data
  • Selftest
  • Statement of motivation
  • GRE Score Report (unless EEA/UK/CH degree)
  • CV
Specialization Notes

Master of Engineering: Computer Science. Admission is at the discretion of the Faculty of Engineering Science.