Professor

​Education

B.S. Mathematics, SNU

M.S. Computer Science, Stanford

M.S. Management Science and Engineering, Stanford

Ph.D. Civil and Environmental Engineering, UC Berkeley

Research Interests

Coming from Mathematics, Computer Science, Management Science, and Civil engineering background, my research focus is system-of-systems, which includes transportation system, city, logistics system, and public health system. My recent research interests include the following areas.

Computational Transportation Science: Future Mobility and AI; Graph Neural Net and Traffic Forecasting; Transportation Network Science; Safety Risk Management

Sustainable Urban Mobility: Urban Mobility Decarbonization; Mobility Accessibility and Inequality; Urban Air Mobility (UAM);

Urban Intelligence: Urban Region Representation Learning; SDG Data Science; AI and Cities; AI for Social Good

Course List

CE 252. Data Science for Civil Engineers, Fall 

Undergraduate introductory course on the probability theory and statistical inference and their applications to Civil & Environmental Engineering (CEE) dataset; data reduction and sampling; set theory; probability theory; random variables and expectation; statistical inference; supervised and unsupervised learning algorithms. Application to a CEE dataset with Python codes. Additional topics may be covered on data analysis of different domains of CEE. 

CE 452. Advanced Transportation System Analysis, Spring (co-listed in GSDS)

Focus on transportation system modeling and analysis with a multi-disciplinary approach. Topics vary by semester. Past topics include driver detection with electro-physical sensory data, 3D urban geospatial analysis, large-scale traffic safety data analytics, traffic management principles, advanced regression analysis, convex optimization, microeconomics, and decision analysis.

CE 545. AI + Transportation System, Fall (co-listed in GSDS)

Project-oriented graduate level course with emphasis on AI applications both to the traditional and emerging transportation system with spatiotemporal elements. Lectures include linear algebra, probability, algebraic topology, information theory, computational statistics, and machine learning basics. Several case studies will be explored and discussed. Students are encouraged to bring their own study cases.

External Services

Public Services  

• Presidential Advisory Council On Science & Technology, 2021~2023

• Presidential Committee on Future Smart City, 2018~2019

• National Airspace Committee,  2014~2020

• National Aviation Policy Committee, 2017~2019

• National Aviation Safety Committee, 2018~2020

• Future Land and Transport Research and Development Committee, 2013~2015

• Land and Transport Policy R&D Committee, 2013~2016

• 2018 Winter Olympic Organizing Committee, Transportation SC, 2014~2017

Industry Services

• Board of Directors, Hyundai GLOVIS, 2021.03~

• Senior Board of Directors, Korea Authority of Land and Infrastructure Safety, 2018.07~2023.05

• Industry Consulting: Samsung Electronics DS (2017, 2018); Jeju Air (2015); Hanil Express (2014); Bosch LLC (2013)

International Services

• Organizing Committee, 22nd International Federation of Operations Research,2017~2020

• Australian Government UTM Working Group, 2020~

• National Delegate, International Standardization Organization (ISO) UAV SC16, 2016~2019

• National Advisor, International Civil Aviation Organization Safety Management Panel, 2014~2016

KAIST Internal Services

• Chair, KAIST School of Engineering Committee of External Affairs (2021-2023)

• KAIST Faculty Council Steering Committee (2021-)

• Vice President, KAIST Women Faculty Council (2021-)

Urban Science Initiatives Leadership Roles

Director, HcFM (2022-)

KAIST-Berekeley Global Initiatives on Human-centered Future Mobility 

Joint efforts between KAIST, UC Berkeley and industry leaders focusing on social and human impact of future mobility including autonomous driving, urban air mobility and AI ethics 

Director, KN-C3 (2023-)

KAIST-NYU Center for Cities and Climate Change 

Joint efforts between KAIST and NYU to develop global research and education program with focus on urban sustainability

Lead, KUSI (2022-)

KAIST Urban Science Initiatives (KUSI) 

Campus-wide task force to develop cross-disciplinary research and education program on computational urban science