Dongjin Song
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
57
Venues
20
Active years
2008–2025
Best venue rank
A*
Where they publish
Papers
57 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | CHASE | Smartphone Data Gathered Early in Depression Treatment Predicts Treatment Outcome. | Soumyashree Sahoo, Md. Zakir Hossain, Chinmaey Shende, Parit Patel, Xinyu Wang, Jinbo Bi, Jayesh Kamath, Alexander Russell, Dongjin Song, Bing Wang |
| 2025 | HCI | A Comprehensive Study of the Influence of Social Capital on the Traditional Chinese Medicine Health Literacy (TCMHL) of the Elderly in Aged Communities and the Relevant Interventions. | Dongjin Song, YingQuan Yang, Aoxue Liu, YiXi WangMu |
| 2025 | ICDM | Towards Interpretable and Trustworthy Time Series Reasoning: A BlueSky Vision. | Kanghui Ning, Zijie Pan, Yushan Jiang, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song |
| 2025 | ICLR | Learning system dynamics without forgetting. | Xikun Zhang, Dongjin Song, Yushan Jiang, Yixin Chen, Dacheng Tao |
| 2025 | ICMLA | Adaptive von Mises-Fisher Likelihood Loss for Supervised Deep Time Series Hashing. | Juan Manuel Perez, Kevin Garcia, Brooklyn Berry, Dongjin Song, Yifeng Gao |
| 2025 | IJCAI | Harnessing Vision Models for Time Series Analysis: A Survey. | Jingchao Ni, Ziming Zhao, ChengAo Shen, Hanghang Tong, Dongjin Song, Wei Cheng, Dongsheng Luo, Haifeng Chen |
| 2025 | KDD | Multi-modal Time Series Analysis: A Tutorial and Survey. | Yushan Jiang, Kanghui Ning, Zijie Pan, Xuyang Shen, Jingchao Ni, Wenchao Yu, Anderson Schneider, Haifeng Chen, Yuriy Nevmyvaka, Dongjin Song |
| 2025 | KDD | The 11th Mining and Learning from Time Series (MILETS): From Classical Methods to LLMs. | Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Yuxuan Liang, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka |
| 2025 | WWW | The Workshop of Artificial Intelligence for Web-Centric Time Series Analysis (AI4TS): Theory, Algorithms, and Applications. | Ming Jin, Mahsa Salehi, Yuxuan Liang, Dongjin Song, Flora Salim, Min Wu, Shirui Pan, Qingsong Wen |
| 2024 | CHASE | Using Mobile Daily Mood and Anxiety Self-ratings to Predict Depression Symptom Improvement. | Soumyashree Sahoo, Chinmaey Shende, Md. Zakir Hossain, Parit Patel, Xinyu Wang, Md Ishtyaq Mahmud, Jinbo Bi, Jayesh Kamath, Alexander Russell, Dongjin Song, Bing Wang |
| 2024 | CSCW | Collective Imaginaries for the Futures of Care Work. | Yiying Wu, Jung-Joo Lee, Ajit G. Pillai, Janghee Cho, Naseem Ahmadpour, Virpi Roto, Thida Sachathep, Jiashuo Liu, Mouna Sawan, Dongjin Song, Martina Caic, Lucas Cheng, Renxuan Liu, Sarah Kettley, Luis Soares, Kazjon Grace, Thomas Astell-Burt |
| 2024 | ICDM | Rank Supervised Contrastive Learning for Time Series Classification. | Qianying Ren, Dongsheng Luo, Dongjin Song |
| 2024 | ICLR | Online GNN Evaluation Under Test-time Graph Distribution Shifts. | Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan |
| 2024 | ICML | S2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting. | Zijie Pan, Yushan Jiang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song |
| 2024 | IJCAI | Empowering Time Series Analysis with Large Language Models: A Survey. | Yushan Jiang, Zijie Pan, Xikun Zhang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song |
| 2024 | KDD | Topology-aware Embedding Memory for Continual Learning on Expanding Networks. | Xikun Zhang, Dongjin Song, Yixin Chen, Dacheng Tao |
| 2024 | KDD | Foundation Models for Time Series Analysis: A Tutorial and Survey. | Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen |
| 2024 | KDD | The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs. | Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka |
| 2024 | SDM | A Novel Hybrid Graph Learning Method for Inbound Parcel Volume Forecasting in Logistics System. | Lisha Ye, Jianfeng Zhou, Zhe Yin, Kunpeng Han, Haoyuan Hu, Dongjin Song |
| 2023 | CISS | Interpretable Skill Learning for Dynamic Treatment Regimes through Imitation. | Yushan Jiang, Wenchao Yu, Dongjin Song, Wei Cheng, Haifeng Chen |
| 2023 | ICLR | Asynchronous Distributed Bilevel Optimization. | Yang Jiao, Kai Yang, Tiancheng Wu, Dongjin Song, Chengtao Jian |
| 2023 | ICLR | HiT-MDP: Learning the SMDP option framework on MDPs with Hidden Temporal Embeddings. | Chang Li, Dongjin Song, Dacheng Tao |
| 2023 | IROS | Privacy-Preserving and Uncertainty-Aware Federated Trajectory Prediction for Connected Autonomous Vehicles. | Muzi Peng, Jiangwei Wang, Dongjin Song, Fei Miao, Lili Su |
| 2023 | KDD | FedSkill: Privacy Preserved Interpretable Skill Learning via Imitation. | Yushan Jiang, Wenchao Yu, Dongjin Song, Lu Wang, Wei Cheng, Haifeng Chen |
| 2023 | KDD | The 9th SIGKDD International Workshop on Mining and Learning from Time Series. | Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Yuriy Nevmyvaka |
| 2023 | WWW | Tutorials at The Web Conference 2023. | Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espn-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Kk-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne R. Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu |
| 2022 | ICDM | Sparsified Subgraph Memory for Continual Graph Representation Learning. | Xikun Zhang, Dongjin Song, Dacheng Tao |
| 2022 | KDD | 8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications. | Sanjay Purushotham, Jun Huan, Cong Shen, Dongjin Song, Yuyang Wang, Jan Gasthaus, Hilaf Hasson, Youngsuk Park, Sungyong Seo, Yuriy Nevmyvaka |
| 2021 | AAAI | Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series. | Yinjun Wu, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, Susan B. Davidson |
| 2021 | AAAI | Multi-Task Recurrent Modular Networks. | Dongkuan Xu, Wei Cheng, Xin Dong, Bo Zong, Wenchao Yu, Jingchao Ni, Dongjin Song, Xuchao Zhang, Haifeng Chen, Xiang Zhang |
| 2021 | CIKM | Interpreting Convolutional Sequence Model by Learning Local Prototypes with Adaptation Regularization. | Jingchao Ni, Zhengzhang Chen, Wei Cheng, Bo Zong, Dongjin Song, Yanchi Liu, Xuchao Zhang, Haifeng Chen |
| 2021 | CVPR | FaceSec: A Fine-Grained Robustness Evaluation Framework for Face Recognition Systems. | Liang Tong, Zhengzhang Chen, Jingchao Ni, Wei Cheng, Dongjin Song, Haifeng Chen, Yevgeniy Vorobeychik |
| 2021 | SDM | Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection. | Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin Song, Bo Zong, Haifeng Chen, Xiang Zhang |
| 2020 | AAAI | Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation. | Xin Dong, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Bo Zong, Dongjin Song, Yanchi Liu, Haifeng Chen, Gerard de Melo |
| 2020 | AAAI | Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series. | Dongkuan Xu, Wei Cheng, Bo Zong, Dongjin Song, Jingchao Ni, Wenchao Yu, Yanchi Liu, Haifeng Chen, Xiang Zhang |
| 2020 | AAAI | Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval. | Dixian Zhu, Dongjin Song, Yuncong Chen, Cristian Lumezanu, Wei Cheng, Bo Zong, Jingchao Ni, Takehiko Mizoguchi, Tianbao Yang, Haifeng Chen |
| 2020 | ICLR | Inductive and Unsupervised Representation Learning on Graph Structured Objects. | Lichen Wang, Bo Zong, Qianqian Ma, Wei Cheng, Jingchao Ni, Wenchao Yu, Yanchi Liu, Dongjin Song, Haifeng Chen, Yun Fu |
| 2020 | ICML | Robust Graph Representation Learning via Neural Sparsification. | Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang |
| 2019 | AAAI | A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data. | Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang Feng, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, Nitesh V. Chawla |
| 2019 | KDD | Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction: Multi-task RNN and Higer-order MRFs for Stock Price Classification. | Chang Li, Dongjin Song, Dacheng Tao |
| 2019 | KDD | Heterogeneous Graph Neural Network. | Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V. Chawla |
| 2019 | SDM | Deep Co-Clustering. | Dongkuan Xu, Wei Cheng, Bo Zong, Jingchao Ni, Dongjin Song, Wenchao Yu, Yuncong Chen, Haifeng Chen, Xiang Zhang |
| 2018 | KDD | Deep r -th Root of Rank Supervised Joint Binary Embedding for Multivariate Time Series Retrieval. | Dongjin Song, Ning Xia, Wei Cheng, Haifeng Chen, Dacheng Tao |
| 2018 | KDD | Learning Deep Network Representations with Adversarially Regularized Autoencoders. | Wenchao Yu, Cheng Zheng, Wei Cheng, Charu C. Aggarwal, Dongjin Song, Bo Zong, Haifeng Chen, Wei Wang |
| 2017 | ICDM | Ranking Causal Anomalies by Modeling Local Propagations on Networked Systems. | Jingchao Ni, Wei Cheng, Kai Zhang, Dongjin Song, Tan Yan, Haifeng Chen, Xiang Zhang |
| 2017 | IJCAI | Exemplar-centered Supervised Shallow Parametric Data Embedding. | Martin Renqiang Min, Hongyu Guo, Dongjin Song |
| 2017 | IJCAI | A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction. | Yao Qin, Dongjin Song, Haifeng Chen, Wei Cheng, Guofei Jiang, Garrison W. Cottrell |
| 2016 | IJCAI | Fast Structural Binary Coding. | Dongjin Song, Wei Liu, David A. Meyer |
| 2015 | AAAI | Recommending Positive Links in Signed Social Networks by Optimizing a Generalized AUC. | Dongjin Song, David A. Meyer |
| 2015 | DCC | Rank Preserving Hashing for Rapid Image Search. | Dongjin Song, Wei Liu, David A. Meyer, Dacheng Tao, Rongrong Ji |
| 2015 | HCI | Design Process as Communication Agency for Value Co-Creation in Open Social Innovation Project: - A Case Study of QuYang Community in Shanghai. | Dongjin Song, Susu Nousala, Yongqi Lou |
| 2015 | ICCV | Top Rank Supervised Binary Coding for Visual Search. | Dongjin Song, Wei Liu, Rongrong Ji, David A. Meyer, John R. Smith |
| 2015 | ICDM | Top-k Link Recommendation in Social Networks. | Dongjin Song, David A. Meyer, Dacheng Tao |
| 2015 | KDD | Efficient Latent Link Recommendation in Signed Networks. | Dongjin Song, David A. Meyer, Dacheng Tao |
| 2014 | HCI | Design for the Public Usage of Rural Surplus Space (PURSS): The Case Study of DEISGN Harvests. | Yongqi Lou, Dongjin Song |
| 2009 | ICIP | Discrminative Geometry Preserving Projections. | Dongjin Song, Dacheng Tao |
| 2008 | ICPR | C1 units for scene classification. | Dongjin Song, Dacheng Tao |