Contact
Location
108 Cresap, Rm. 104

Stephen Baek

Quantiative Foundation Associate Professor, Data Science Associate Profession, Mechanical and Aerospace Engineering, by courtesy
Contact
Location
108 Cresap, Rm. 104
Visual Intelligence Laboratory Google Scholar

About

Stephen Baek is an applied geometer, scientist, and entrepreneur. He studies the space of shapes using machine learning. Baek's educational background is in mechanical and aerospace engineering. 

Prior to joining UVA in 2021, he was an Assistant Professor at the University of Iowa, where he taught courses on deep learning. There, he also founded and directed the Visual Intelligence Laboratory, which conducts fundamental research in computational geometry, vision, and machine learning. Baek's research interests include geometric data analysis, gemetric deep learning, scientific machine learning and data-driven design.

Baek's published research is extensive, including "Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials" and "Deep segmentation networks predict survival of non-small cell lung cancer."

Baek holds a PH.D. in Mechanical and Aerospace Engineering from Seoul National University and a B.S. in Mechanical and Aerospace Engineering from Seoul National Unversity.

Education

B.S. Mechanical and Aerospace Engineering, Seoul National University, 2009

Ph.D. Mechanical and Aerospace Engineering, Seoul National University, 2013

President’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."

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 SCIENCE ADVANCES, 9(17): EADD6868. (2023)
ABS
Body shape matters: Evidence from machine learning on body shape-income relationship PLOS ONE, 16(7): E0254785. (2021)
ABS
Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials
ABS
ZerNet: Convolutional Neural Networks on Arbitrary Surfaces Via Zernike Local Tangent Space Estimation COMPUTER GRAPHICS FORUM, 39(6): 204-216. (2020)
ABS

Awards

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

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