Yuyol Shin

Postdoctoral Researcher (NYUAD) 2024.10. ~ present

Postdoctoral Researcher (KAIST) 2022.09 ~ 2024.05.

Visiting Scholar (UC Berkeley) 2022.10 ~ 2023.06.

New York University, Abu Dhabi (NYUAD)

E-mail: ys6812@nyu.edu

Research Interests

Traffic Forecasting
Graph Neural Networks
Transportation Network Analysis
Spatial-Temporal Data Mining

Bio:

My research interests are spatial-temporal data mining, artificial intelligence in the field of transportation engineering, and transportation network analysis. My recent works have focused on developing models for traffic forecasting in urban areas using Graph Neural Networks and time-series models such as LSTM and causal convolution. Recently, I have been investigating the field of AI-based maritime transportation, including vessel intention prediction, weather routing, and smart port operation.

I am currently a postdoc at KAIST (Korea Advanced Institute of Science and Technology, Daejeon, South Korea) TRUE Lab. I received my Ph.D. from KAIST Civil and Environmental Engineering advised by Yoonjin Yoon. I also received my Bachelor's degree from KAIST. I am more than open to any discussions and/or collaboration opportunities, and please feel free to contact me!

Please take a look at the research page and Google Scholar for more.

Highlights

KAIST Urban X Seminar: Short-term Traffic Forecasting in Urban Areas - Element-wise Performance Evaluation in Diverse Study Sites

Deep Learning Framework for Vessel Trajectory Prediction Using Auxiliary Tasks and Convolutional Networks

Reflecting Time-Varying Spatial Correlation Using Dynamic Graphs for Traffic Forecasting

Performance Evaluation of Basic Elements of Deep Neural Network Models for Traffic Forecasting

GNN-based Traffic Forecasting Using Various Structural Characteristics

Publications

Y. Shin, N. Kim, H. Lee, S.Y. In, M. Hansen, and Y. Yoon*, "Deep Learning Framework for Vessel Trajectory Prediction Using Auxiliary Tasks and Convolutional Networks" Engineering Applications of Artificial Intelligence, 2024.
Y. Shin, Y. Yoon*, "PGCN: Progressive Graph Convolutional Networks for Traffic Forecasting", IEEE Transactions on Intelligent Transportation Systems, 2024. (early access)
Y. Shin, Y. Yoon*, "Performance Evaluation of Building Blocks of Spatial-Temporal Deep Learning Models for Traffic Forecasting", IEEE Access, 11, 136478-136495, 2023.
Y. Shin, Y. Yoon*, "Incorporating Dynamicity of Transportation Network With Multi-Weight Traffic Graph Convolutional Network for Traffic Forecasting", IEEE Transactions on Intelligent Transportation Systems, 23(3), 2082-2092, 2022.

Conferences

Y. Shin, G. Seong, N. Kim, S. Kim, Y. Yoon, "Understanding Urban Economics Status through GNN-based Urban Representation Learning Using Mobility Data," 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI (UrbanAI 2023), 2023.
Y. Shin, Y. Yoon, "A Comparative Study on Basic Elements of Deep Learning Models for Spatial-Temporal Traffic Forecasting", AAAI-22 workshop: AI for Transportation, 2022.
Y. Shin, S. Kim, and Y. Yoon, "How COVID-19 Reshaped the Logistics Industry - Analysis of Large-Scale Parcel Delivery Data in Seoul, South Korea," The AOTULE 2021 Student Conference, 2021. (Best presentation award)
S. Kim, Y. Shin, Y. Yoon*, "Topological Data Analysis on the Northeast Asian Air Route Network", 9th International Conference for Research in Air Transportation (ICRAT 2020), 2020.
Y. Shin, Y. Yoon. "Reflecting Structural Dynamicity of Traffic Networks to Graph Convolution Modules: A Deep Learning Approach to Traffic Forecasting," The 32nd KKHTCNN Symposium on Civil Engineering, 2019.
Y. Shin, J. Cho, N. Kim, Y. Yoon*, "Predicting Seoul Subway Hourly Passenger Demand Using Neural Network Models", The 2nd Asian Conference on Railway Engineering and Transportation (ART 2018), 2018. (Best paper award)
Y. Shin, Y. Yoon. "Data-Driven Approach to Urban Transportation Road Network Analysis USing Topological Data Analysis - Case Study on Gangnam District, Seoul," The 31st KKHTCNN Symposium on Civil Engineering, 2018.

Educations

Ph.D., Dept. of Civil and Environmental Engineering [2016.09 – 2022.06]
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
B.S., Dept. of Civil and Environmental Engineering [2011.09 – 2016.06]
Minor in Intellectual Property Minor Program
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea