B.S. Mechanical and Aerospace Engineering, Seoul National University, 2009Ph.D. Mechanical and Aerospace Engineering, Seoul National University, 2013President’s Postdoc Fellow, Institute for Advanced Machinery Design, 2013-2015

"Geometry plays a critical role in science and engineering. Our mission is to quantify the roles played by shapes through the lenses of machine learning."

Stephen Baek is an Associate Professor of Data Science at the University of Virginia, where he also holds a courtesy appointment in the Department of Mechanical and Aerospace Engineering. Baek received his B.S. in Mechanical and Aerospace Engineering from Seoul National University (SNU), Seoul, Korea in 2009 and a Ph.D. in 2013 from the same institution for his award-winning study on the statistical space of shapes modeled on a Riemannian manifold. He was a postdoctoral researcher at the Institute for Advanced Machinery Design in SNU from 2013 to 2015 and a visiting research associate at the Ronald E. McNair Center for Aerospace Innovation and Research at the University of South Carolina in 2014. During his training, Baek received the National Science and Engineering Scholarship and the Global Ph.D. Fellowship from the Korean Ministry of Education. He was also awarded the Presidential Postdoc Fellowship from the President of the Republic of Korea. Prior to joining the University of Virginia, Baek spent 6 years as an Assistant Professor at the University of Iowa.


  • Shannon Center Mid-Career Faculty Fellow 2023
  • Associate Editor, Journal of Computational Design and Engineering 2021
  • University of Iowa Supervisor of the Year Award 2021
  • Defense Innovation Award 2021
  • University of Iowa Innovator Award 2019
  • Old Gold Summer Fellowship 2018
  • Best Paper Award, International Conference on Maintenance and Rehabilitation of Constructed Infrastructure Facilities 2017
  • Delcam Korea Best Graduate Thesis Award 2014
  • Presidential Postdoc Fellowship 2014
  • Global Ph.D. Fellowship, Korean Ministry of Education 2011
  • Bronze Medal, Korea Software Awards 2009
  • National Science and Engineering Scholarship, Korean Ministry of Education 2005

Research Interests

  • Geometric Data Analysis
  • Statistical Shape Modeling & Analysis
  • Deep Learning on Non-Euclidean Domains
  • Data-driven Design and Engineering
  • Digital Human Modeling

Selected Publications

  • PARC: Physics-aware recurrent convolutional neural networks to assimilate meso scale reactive mechanics of energetic materials ABS Science Advances, 9(17): eadd6868. (2023)
  • Body shape matters: Evidence from machine learning on body shape-income relationship ABS PLOS One, 16(7): e0254785. (2021)
  • Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials ABS Scientific Reports, 10: 13307. (2020)
  • ZerNet: Convolutional Neural Networks on Arbitrary Surfaces Via Zernike Local Tangent Space Estimation ABS Computer Graphics Forum, 39(6): 204-216. (2020)
  • Deep segmentation networks predict survival of non-small cell lung cancer ABS Scientific Reports, 9: 17286. (2019)
  • Parametric human body shape modeling framework for human-centered product design ABS Computer-Aided Design, 44(1): 56-67. (2012)