Ilwoo Lyu

(류일우)

Computer Science and Engineering
Engineering Bldg. 106, 801-5
50 UNIST-gil, Ulsan 44919, Korea
E-mail: ilwoolyu at unist ac kr
Phone: +82-52-217-2298

Affiliations: @UNIST [CSE] [BME]
@Vanderbilt [EECS] [VISE]
[Google Scholar] [dblp] [GitHub]

Last Updated: March 2021

About Myself / Research Interests / Education / Employment / Publications / Teaching / Talks / Software / Jobs

About Myself

I am an assistant professor of Computer Science and Engineering at Ulsan National Institute of Science and Technology (UNIST) and an adjoint assistant professor of Electrical Engineering and Computer Science at Vanderbilt University. Prior to joining UNIST, I was a research assistant professor of Electrical Engineering and Computer Science at Vanderbilt University. I earned my PhD in Computer Science at The University of North Carolina at Chapel Hill. My research interest is mainly in developing novel algorithms for 3D shape analysis. My current research focuses on surface-based analysis to understand/explore highly convoluted shapes such as brain. In particular, I am working on surface registration, anatomical/geometric feature extraction/recognition, statistical shape analysis, and 3D visualization.

Research Interests


Education

The University of North Carolina at Chapel Hill
Doctor of Philosophy in Computer Science
2011 - 2017
Korea Advanced Institute of Science and Technology (KAIST)
Master of Science in Computer Science
2009 - 2011
KAIST
Bachelor of Science in Computer Science
2002 - 2009

Employment

UNIST, Ulsan, Korea
Assistant Professor
Mar 2021 - Present
Vanderbilt University, Nashville, TN, USA
Adjoint Assistant Professor
Mar 2021 - Present
MASI Lab, Vanderbilt University, Nashville, TN, USA
Research Assistant Professor
Mentor: Dr. Bennett Landman
Mar 2017 - Feb 2021
Neuro Image Research and Analysis Lab, UNC, Chapel Hill, NC, USA
Research Assistant
Advisor: Dr. Martin Styner
Dec 2011 - Feb 2017
IBM Almaden Reserach Center, San Jose, California, USA
Intern
Mentor: Dr. Tanveer F. Syeda-Mahmood and Dr. Colin B. Compas
May 2015 - Jul 2015
Computer Graphics Laboratory, KAIST, Daejeon, Korea
Research Assistant
Advisor: Dr. Sung Yong Shin and Dr. Joon-Kyung Seong
Jun 2010 - May 2011
Cognitive Robotic Vision Laboratory, KIST, Seoul, Korea
Intern
Mentor: Dr. Sung-Kee Park
Mar 2009 - May 2009

Selected Publications

[Expand] [Collapse]
Labeling Lateral Prefrontal Sulci using Spherical Data Augmentation and Context-aware Training [DOI] [PMID:33497773] [Abstract] [Software]
Ilwoo Lyu, Shunxing Bao, Lingyan Hao, Jewelia Yao, Jacob Miller, Willa Voorhies, Warren Taylor, Silvia Bunge, Kevin Weiner, Bennett Landman
NeuroImage, 229, 117758, 2021
Cortical Surface Parcellation using Spherical Convolutional Neural Networks [DOI] [PMID:31803864] [Abstract] [Software]
Prasanna Parvathaneni, Shunxing Bao, Vishwesh Nath, Neil Woodward, Daniel Claassen, Carissa Cascio, David Zald, Yuankai Huo, Bennett Landman, Ilwoo Lyu
Medical Image Computing and Computer Assisted Intervention (MICCAI) 2019, LNCS11766, 501-509, Shenzhen, China, 2019, early accept, travel award
Hierarchical Spherical Deformation for Cortical Surface Registration [DOI] [PMID:31280090] [Abstract] [Software]
Ilwoo Lyu, Hakmook Kang, Neil Woodward, Martin Styner, Bennett Landman
Medical Image Analysis, 57, 72-88, 2019
Hierarchical Spherical Deformation for Shape Correspondence [DOI] [PMID:31803863] [Abstract] [Software]
Ilwoo Lyu, Martin Styner, Bennett Landman
Medical Image Computing and Computer Assisted Intervention (MICCAI) 2018, LNCS11070, 853-861, Granada, Spain, 2018, early accept, oral presentation
A Cortical Shape-Adaptive Approach to Local Gyrification Index [DOI] [PMID:29990689] [Abstract] [Software]
Ilwoo Lyu, Sun Hyung Kim, Jessica Girault, John Gilmore, Martin Styner
Medical Image Analysis, 48, 244-258, 2018
TRACE: A Topological Graph Representation for Automatic Sulcal Curve Extraction [DOI] [PMID:29969416] [Abstract] [Software]
Ilwoo Lyu, Sun Hyung Kim, Neil Woodward, Martin Styner, Bennett Landman
IEEE Transactions on Medical Imaging, 37(7), 1653-1663, 2018
Novel Local Shape-Adaptive Gyrification Index with Application to Brain Development [DOI] [Abstract] [Software]
Ilwoo Lyu, Sun Hyung Kim, Jessica Bullins, John Gilmore, Martin Styner
Medical Image Computing and Computer Assisted Intervention (MICCAI) 2017, LNCS10433, 31-39, Quebec City, Quebec, Canada, 2017
Group-Wise Cortical Correspondence via Sulcal Curve-Constrained Entropy Minimization [DOI] [PMID:24683983] [Abstract] [Tutorial]
Ilwoo Lyu, Sun Hyung Kim, Joon-Kyung Seong, Sang Wook Yoo, Alan Evans, Yundi Shi, Mar Sanchez, Marc Niethammer, Martin Styner
Information Processing in Medical Imaging (IPMI) 2013, LNCS7917, 364-375, Asilomar, California, USA, 2013, oral presentation with open-ended discussion
Spectral-based Automatic Labeling and Refining of Human Cortical Sulcal Curves using Expert-Provided Examples [DOI] [PMID:20363334] [Abstract]
Ilwoo Lyu, Joon-Kyung Seong, Sung Yong Shin, Kiho Im, Jee Hoon Roh, Min-Jeong Kim, Geon Ha Kim, Jong Hun Kim, Alan Evans, Duk L. Na, Jong-Min Lee
NeuroImage, 52(1), 142-157, 2010
- Full List -

Teaching

Spring 2021: CSE61301 3D Shape Analysis in Neuroimaging, UNIST, Korea
Instructor
Mar 2021 - Present
Fall 2020: CS8395 Open Source Programming for Medical Image Analysis - Surface-based Cortical Shape Analysis, Vanderbilt University, USA
Guest Lecturer
Oct 2020
Fall 2019: CS8395 Open Source Programming for Medical Image Analysis - Cortical Surface Reconstruction and Shape Analysis, Vanderbilt University, USA
Guest Lecturer
Oct 2019
Fall 2019: CS4262 Foundations of Machine Learning - Machine Learning for Brain Image Analysis, Vanderbilt University, USA
Guest Lecturer
Sep 2019
Fall 2017, Fall 2019: SC3250 Scientific Computing - Introduction to Copmuter Vision with Applications, Vanderbilt University, USA
Guest Lecturer
Sep 2017, Sep 2019
Summer 2019: Vanderbilt Data Science Institute Summer Research Program (DSI-SRP) , Vanderbilt University, USA
Mentor
May 2019 - Jul 2019
Spring 2014: COMP915 Technical Communication in Computer Science, UNC, USA
Trainee
Jan 2014 - May 2014
Fall 2010: CS300 Introduction to Algorithms, KAIST, Korea
Teaching Assistant
Sep 2010 - Dec 2010
Fall 2009: CS202 Problem Solving, KAIST, Korea
Teaching Assistant
Sep 2009 - Dec 2009
Tutoring Program for Freshman: JAVA language, KAIST, Korea
Private Tutor
Feb 2008 - Dec 2008

Podium Talks

Hierarchical Spherical Deformation for Shape Correspondence, MICCAI 2018, Granada, Spain
Sep 2018
Sulcal Depth-based Cortical Shape Analysis in Normal Healthy Control and Schizophrenia Groups, SPIE Medical Imaging 2018, Houston, Texas, USA
Feb 2018
Cortical Surface Registration and Shape Analysis, VISE Summer Seminar 2017, Vanderbilt University, Nashville, Tennessee, USA
Jul 2017
Cortical Surface Shape Assessment via Sulcal/Gyral Curve-based Gyrification Index, ISBI 2016, Prague, Czech Republic
Apr 2016
Group-wise Cortical Correspondence via Sulcal Curve-Constrained Entropy Minimization, IPMI 2013, Asilomar, California, USA
Jun 2013

Software

The source codes in my publications are publicly available under the MIT license. The software package imaged by Docker is distributed through my Docker repository or as Singularity images. In the Docker (or Singularity) environment, no package build/installation is required; everything is fully containerized in the Docker (Singularity) images. All my tools can be run with a single command line after pulling the images from the Docker repository or Singularity distributions below. See more details about implementation, installation, usage, etc. at my GitHub profile.

Containerized images (standalone applications) Github repositories

Job Openings: Research Assistant

We are actively looking for highly motivated undergraduate/graduate co-investigators. The new member will closely work with Dr. Ilwoo Lyu, Principal Investigator (PI), to develop cutting-edge techniques for image/surface processing on 3D shapes. Our team's mission is to offer quantitative interpretation that can help better understand 3D nature around the world from a geometry perspective.

Introduction to 3D shape analysis
The world we live in consists of various 3D objects with their own shape characteristics. With advances in computational power, it becomes natural to understand our world in a 3D manner rather than 2D projection that limits full encoding of 3D objects. In this context, 3D shape analysis aims at the automatic analysis of 3D objects that can be naturally represented by 3D geometry. This field of research intersects subfields of computer science across computer vision, computer graphics, machine learning, and computational geometry. The applications in 3D shape analysis cover multidisciplinary areas such as medical imaging, biology, ergonomics, robotics, material/chemical engineering, etc. The main research projects include Research team
Our team is in active collaboration with multiple PIs at Vanderbilt University Medical Center, UC-Berkeley Helen Wills Neuroscience Institute, and UNC-Chapel Hill Psychiatry for structural brain image research. Although the research projects will seek generic shape analysis techniques (i.e., not solely limited to brain applications), the new member interested in brain shape analysis will have an opportunity to work with our collaborators.

Requirements
Successful applicants (are expected to) hold a BS/MS degree in Computer Science, Biomedical Engineering, Electrical Engineering, Neuroscience or a related field with a background in computational research. Excellent communication skills and willingness to learn new theories and techniques are a must. Previous experience in image/surface processing is highly desirable but not required. Experience in mathematical modeling, biomedical image analysis, statistical analysis, big data analysis is a plus. As a core of computation-oriented research, extensive programming skills are mandatory in at least one of programming languages including C++, MATLAB, Python, etc.

Please feel free to email Dr. Lyu for job inquiries if interested.