About
Hi, I am an AI researcher passionate about solving various practical challenges encountered when deploying AI models in real-world settings. I've been working at the Korea Electronics Technology Institute (KETI), focusing on designing multimodal fusion frameworks that perform robustly under incomplete and noisy data. I received a B.S. and an M.S. in Computer and Communication Engineering from Kangwon National University, advised by Prof. Sang-Ki Ko.
Email : hanjun_c@naver.com
Github : Link
LinkedIn : Link
Portfolio : Link
Research Interests
Multimodal Fusion
Multi-agent Trajectory prediction & imputation
Industrial Anomaly Detection
News
2025. 08 : I am really excited to share that our short paper "Imputing Multi-Agent Trajectories from Event and Snapshot Data in Soccer (participated as a co-author)" is accepted to CIKM (BK21 Top Conference).
2025. 06 : The paper "Multimodal Sentiment Aanlysis under Incomplete Modalities with Missing Text Localization and Confidence-Aware Fusion" is accepted at KIBME and received the Best Paper Award!
2025. 05 : The paper "Trajectory Imputation in Multi-Agent Sports with Derivative-Accumulating Self-Ensemble" is accepted at ECML PKDD (BK21 Top Conference).
2024. 09 : The paper "Analysis of Missing Modality Problems with Korean Multimodal Sentiment Data" is accepted at HCLT.
2024. 02 : The paper "Transformer-Based Multi-Agent Trajectory Imputation Model using Permutation Equivariance" is published at KCTP.
2024. 01 : I’ve started a contract position in the AI Research Center at KETI!
2023. 06 : The paper "Deep-learning-based Multi-Agent Trajectory Imputation" is accepted at KCC., Excellent paper award
2023. 05 : Our paper "Ball trajectory inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM" is accepted at KDD (BK21 Top Conference). This is my first international publication!
2022. 12 : The paper "Optimal Data Generation Strategy for Training RNN-based Time-series Data Imputation Models" is published at KSC.
2022. 06 : The paper "Comparison Study of Deep Learning-based Spatiotemporal Data Imputation Algorithms" is published at KCC.
2022. 02 : The paper "Deep learning-based workout classification and repetition counting using IMU sensor data" is published at ICTC.
2021. 12 : The paper "Deep learning-based coordinate tracking algorithm for automated soccer video analysis" is accepted at KSC., , Excellent paper award
2021.06 : My first paper "Deep learning-based time-series wind speed data imputation algorithm using temperature data" is accepted at KCC!