Mijung Park
Scholar

Mijung Park

Google Scholar ID: fqKsAJcAAAAJ
University of British Columbia
Machine learningBayesian statisticsdifferential privacy
Citations & Impact
All-time
Citations
835
 
H-index
14
 
i10-index
22
 
Publications
20
 
Co-authors
19
list available
Contact
No contact links provided.
Resume (English only)
Academic Achievements
  • Research projects include improving the trade-offs between privacy and accuracy, advancing differentially-private synthetic data generation techniques, and exploring the relationship between differential privacy and other characteristics.
Research Experience
  • Leading the ParkLabML lab, which is dedicated to creating and improving machine learning tools that preserve privacy for a better world.
Background
  • Research Interests: Improving and developing methods in privacy-preserving machine learning, aiming to facilitate data analyses without sacrificing privacy. Areas of expertise include improving the trade-offs between privacy and accuracy, advancing differentially-private synthetic data generation techniques, and studying the interplay between differential privacy and other emerging characteristics such as interpretability, fairness, and causality. About: Our lab focuses on enhancing and developing privacy-preserving machine learning methods, especially for applications in healthcare.
Miscellany
  • Personal interests: A wholehearted approach to life.