Seongjin Choi (최성진)

Seongjin Choi (최성진)

KAIST

H-index: 8

Asia-South Korea

About Seongjin Choi (최성진)

Seongjin Choi (최성진), With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at KAIST, specializes in the field of AI for Transportation, Urban Mobility, Spatiotemporal Modeling, Traffic Simulation, ITS.

His recent articles reflect a diverse array of research interests and contributions to the field:

A Real-time Evaluation Framework for Pedestrian's Potential Risk at Non-Signalized Intersections Based on Predicted Post-Encroachment Time

Better batch for deep probabilistic time series forecasting

Framework for Connected and Automated Bus Rapid Transit with Sectionalized Speed Guidance based on deep reinforcement learning: Field test in Sejong City

Enhancing deep traffic forecasting models with dynamic regression

Evaluation of Pedestrian\s Potential Risk at Non-Signalized Intersections Based on Predicted Relative Time-To-Collision Using Deep Learning Trajectory Prediction Method

Optimal planning of parking infrastructure and fleet size for Shared Autonomous Vehicles

Safety monitoring system of CAVs considering the trade-off between sampling interval and data reliability

A framework for pedestrian sub-classification and arrival time prediction at signalized intersection using preprocessed Lidar data

Seongjin Choi (최성진) Information

University

Position

Department of Civil & Environmental Engineering

Citations(all)

300

Citations(since 2020)

295

Cited By

50

hIndex(all)

8

hIndex(since 2020)

8

i10Index(all)

6

i10Index(since 2020)

5

Email

University Profile Page

KAIST

Google Scholar

View Google Scholar Profile

Seongjin Choi (최성진) Skills & Research Interests

AI for Transportation

Urban Mobility

Spatiotemporal Modeling

Traffic Simulation

ITS

Top articles of Seongjin Choi (최성진)

Title

Journal

Author(s)

Publication Date

A Real-time Evaluation Framework for Pedestrian's Potential Risk at Non-Signalized Intersections Based on Predicted Post-Encroachment Time

arXiv preprint arXiv:2404.15635

Tengfeng Lin

Zhixiong Jin

Seongjin Choi

Hwasoo Yeo

2024/4/24

Better batch for deep probabilistic time series forecasting

Zhihao Zheng

Seongjin Choi

Lijun Sun

2024/4/18

Framework for Connected and Automated Bus Rapid Transit with Sectionalized Speed Guidance based on deep reinforcement learning: Field test in Sejong City

Transportation Research Part C: Emerging Technologies

Seongjin Choi

Donghoun Lee

Sari Kim

Sehyun Tak

2023/3/1

Enhancing deep traffic forecasting models with dynamic regression

arXiv preprint arXiv:2301.06650

Vincent Zhihao Zheng

Seongjin Choi

Lijun Sun

2023/1/17

Evaluation of Pedestrian\s Potential Risk at Non-Signalized Intersections Based on Predicted Relative Time-To-Collision Using Deep Learning Trajectory Prediction Method

대한교통학회 학술대회지

Tengfeng Lin

Zhixiong Jin

Seongjin Choi

Hwasoo Yeo

2023/10

Optimal planning of parking infrastructure and fleet size for Shared Autonomous Vehicles

Transportation Research Part E: Logistics and Transportation Review

Seongjin Choi

Jinwoo Lee

2023/8/1

Safety monitoring system of CAVs considering the trade-off between sampling interval and data reliability

Sensors

Sehyun Tak

Seongjin Choi

2022/5/10

A framework for pedestrian sub-classification and arrival time prediction at signalized intersection using preprocessed Lidar data

arXiv preprint arXiv:2201.05877

Tengfeng Lin

Zhixiong Jin

Seongjin Choi

Hwasoo Yeo

2022/1/15

Scalable Dynamic Mixture Model with Full Covariance for Probabilistic Traffic Forecasting

arXiv preprint arXiv:2212.06653

Seongjin Choi

Nicolas Saunier

Vincent Zhihao Zheng

Martin Trepanier

Lijun Sun

2022/12/10

Spatiotemporal Residual Regularization with Kronecker Product Structure for Traffic Forecasting

Seongjin Choi

Nicolas Saunier

Martin Trepanier

Lijun Sun

2022

Transformer-based map-matching model with limited labeled data using transfer-learning approach

Transportation Research Part C: Emerging Technologies

Zhixiong Jin

Jiwon Kim

Hwasoo Yeo

Seongjin Choi

2022/7/1

Deep Learning based Urban Vehicle Trajectory Analytics

arXiv preprint arXiv:2111.07489

Seongjin Choi

2021/11/15

TrajGAIL: Generating urban vehicle trajectories using generative adversarial imitation learning

Transportation Research Part C: Emerging Technologies

Seongjin Choi

Jiwon Kim

Hwasoo Yeo

2021/7/1

Extended urban cell transmission model using agent-based modeling

Procedia Computer Science

Yeeun Kim

Seongjin Choi

Hwasoo Yeo

2020/1/1

See List of Professors in Seongjin Choi (최성진) University(KAIST)

Co-Authors

H-index: 41
Nicolas Saunier

Nicolas Saunier

École Polytechnique de Montréal

H-index: 39
Martin Trépanier

Martin Trépanier

École Polytechnique de Montréal

H-index: 34
Lijun Sun (孙立君)

Lijun Sun (孙立君)

McGill University

H-index: 31
Hwasoo Yeo

Hwasoo Yeo

KAIST

H-index: 16
Jinwoo Lee

Jinwoo Lee

KAIST

H-index: 6
Vincent Z. Zheng

Vincent Z. Zheng

McGill University

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