Research Interests

  • Video and Audio Understanding
  • Recommendation Systems
  • Collaborative Filtering
  • Statistical Machine Learning

Publications

Google Scholar | DBLP | Semantic Scholar
  • Book Chapters
    1. Joonseok Lee. Recommendation Systems: An Industrial Application of Network Big Data for Computational Intelligence, Big Data and Computational Intelligence in Networking, Yulei Wu, Fei Hu, Geyong Min, Albert Y. Zomaya (ed.), CRC Press, ISBN: 9781498784863, Chapter 11, 2017. [link]
  • Referred Journals
    1. Sangho Suh, Sungbok Shin, Joonseok Lee, Chandan K. Reddy, Jaegul Choo. Localized User-Driven Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization, Knowledge and Information Systems (KAIS), 2018. [pdf]
    2. Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer, Samy Bengio. LLORMA: Local Low-Rank Matrix Approximation, Journal of Machine Learning Research (JMLR) 17(15):1-24, 2016. [pdf] [talk by Lebanon]
    3. Joonseok Lee, Hanggjun Cho, Robert Ian (Bob) McKay. A Rapid Screening and Testing Protocol for Keyboard Layout Speed Comparison, IEEE Transactions on Human-Machine Systems, vol.PP, no.99, pp.1-14, 2014. [pdf]
    4. Joonseok Lee, Mingxuan Sun, Guy Lebanon. PREA: Personalized Recommendation Algorithms Toolkit, Journal of Machine Learning Research (JMLR) 13:2699-2703, 2012. [pdf] [code]
  • Referred Conferences
    1. Minjin Choi, Jinhong Kim, Joonseok Lee, Hyunjung Shim, Jongwuk Lee. Session-aware Linear Item-Item Models for Session-based Recommendation, Proceedings of the 31st ACM Web Conference (WWW), 2021. [pdf]
    2. Minjin Choi, Yoonki Jeong, Joonseok Lee, Jongwuk Lee. Local Collaborative Autoencoders, Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM), 2021. [pdf]
    3. Sunghyun Park, Kangyeol Kim, Junsoo Lee, Jaegul Choo, Joonseok Lee, Sookyung Kim, Edward Choi. Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation, Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021. [pdf]
    4. Hyodong Lee, Joonseok Lee, Joe Ng, Paul Natsev. Large Scale Video Representation Learning via Relational Graph Clustering, Proceedings of the 36th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. [pdf] [video]
    5. Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini, Joonseok Lee, Emily Denton. Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing, Proceedings of the 3rd AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES), 2020. [pdf]
    6. Sookyung Kim, Sunghyun Park, Sunghyo Chung, Joonseok Lee, Yunsung Lee, Hyojin Kim, Mr Prabhat, Jaegul Choo. Learning to Focus and Track Extreme Climate Events, Proceedings of the 30th British Machine Vision Conference (BMVC), 2019. [pdf] [supplementary]
    7. Seong Jae Hwang, Joonseok Lee, Balakrishnan Varadarajan, Ariel Gordon, Zheng Xu, Paul Natsev. Large-Scale Training Framework for Video Annotation, Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019. [pdf] [talk] [video]
    8. Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee. N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification, Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI), 2019. [pdf] [talk]
    9. Sookyung Kim, Hyojin Kim, Joonseok Lee, Sangwoong Yoon, Samira Ebrahimi Kahou, Karthik Kashinath, Mr. Prabhat. Deep-Hurricane-Tracker: Tracking and Forecasting Extreme Climate Events, IEEE Winter Conference on Applications of Computer Vision (WACV), 2019. [pdf]
    10. Sookyung Kim, Sangwoong Yoon, Joonseok Lee, Samira Ebrahimi Kahou, Hyojin Kim, Karthik Kashinath, Mr. Prabhat. Deep-Hurricane-Tracker: Tracking Extreme Climate Events, Climate Informatics, 2018. [pdf]
    11. Joonseok Lee, Sami Abu-El-Haija, Balakrishnan Varadarajan, Paul Natsev. Collaborative Deep Metric Learning for Video Understanding, Proceedings of the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018. [pdf] [video]
    12. Joonseok Lee, Sami Abu-El-Haija. Large-Scale Content-Only Video Recommendation, Proceedings of the IEEE International Conference on Computer Vision (ICCV), CEFRL Workshop, pp.987-995, 2017. [pdf]
    13. Sangho Suh, Jaegul Choo, Joonseok Lee, Chandan Reddy. Local Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization, Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Sister Conferences track, 2017. [pdf]
    14. Sangho Suh, Jaegul Choo, Joonseok Lee, Chandan Reddy. Boosted L-EnsNMF: Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization, Proceedings of the IEEE International Conference on Data Mining (ICDM), 2016. Best Student Paper Award [pdf]
    15. Joonseok Lee, Ariel Fuxman, Bo Zhao, Yuanhua Lv. Leveraging Knowledge Bases for Contextual Entity Exploration, Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015. [pdf] [talk]
    16. Joonseok Lee, Kisung Lee, Jennifer G. Kim, Sookyung Kim. Personalized Academic Research Paper Recommendation System, Proceedings of the 6th International Workshop on Social Recommender Systems (SRS), 2015. [pdf]
    17. Seungyeon Kim, Joonseok Lee, Guy Lebanon, Haesun Park. Local Context Sparse Coding, Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015. [pdf]
    18. Seungyeon Kim, Joonseok Lee, Guy Lebanon, Haesun Park. Estimating Temporal Dynamics of Human Emotions, Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015. [pdf]
    19. Joonseok Lee, Samy Bengio, Seungyeon Kim, Guy Lebanon, Yoram Singer. Local Collaborative Ranking, Proceedings of the 23rd International World Wide Web Conference (WWW), 2014. Best Student Paper Award [pdf]
    20. Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer. Local Low-Rank Matrix Approximation, Proceedings of the 30th International Conference on Machine Learning (ICML), 2013. [pdf]
    21. Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer. Matrix Approximation under Local Low-Rank Assumption, The Learning Workshop in International Conference on Learning Representations (ICLR), 2013. [pdf]
    22. Mingxuan Sun, Fuxin Li, Joonseok Lee, Ke Zhou, Guy Lebanon, Hongyuan Zha. Learning Multiple-Question Decision Trees for Cold-Start Recommendation, Proceedings of the 6th ACM International Conference on Web Search and Data Mining (WSDM), 2013. [pdf]
    23. Joonseok Lee, Mingxuan Sun, Seungyeon Kim, Guy Lebanon. Automatic Feature Induction for Stagewise Collaborative Filtering, Advances in Neural Information Processing Systems (NIPS) 25, 2012. [pdf]
    24. Joonseok Lee, Hanggjun Cho, Robert Ian (Bob) McKay. Rapid Screening of Keyboard Layouts, Proceedings of IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2012. [pdf]
    25. Joonseok Lee, Robert Ian (Bob) McKay. Optimizing a Personalized Cellphone Keypad, Proceedings of the 5th International Conference on Convergence and Hybrid Information Technology (ICHIT), 2011. [pdf]
  • Non-referred Workshops, Demos, and ArXiv Preprints
    1. Bowen Zhang, Hexiang Hu, Joonseok Lee, Ming Zhao, Sheide Chammas, Vihan Jain, Eugene Ie, Fei Sha. A Hierarchical Multi-Modal Encoder for Moment Localization in Video Corpus, ArXiv:2011.09046, 2020. [pdf]
    2. Sunghyun Park, Kangyeol Kim, Sookyung Kim, Joonseok Lee, Junsoo Le, Jiwoo Lee, Jaegul Choo. Hurricane Nowcasting with Irregular Time-step using Neural-ODE and Video Prediction, Proceedings of the International Conference on Learning Representations (ICLR), Climate Change AI workshop, 2020. [pdf]
    3. Sookyung Kim, Sunghyun Park, Sunghyo Chung, Yunsung Lee, Hyojin Kim, Joonseok Lee, Jaegul Choo, Mr Prabhat. Focus and Track: Pixel-wise Spatio-temporal Hurricane Tracking, Proceedings of the International Conference on Machine Learning (ICML), Workshop on Climate Change AI, 2019. [pdf]
    4. Joonseok Lee, Paul Natsev, Walter Reade, Rahul Sukthankar, George Toderici. The 2nd YouTube-8M Large-Scale Video Understanding Challenge, Proceedings of the 15th Euoprean Conference on Computer Vision (ECCV), 2018. [pdf]
    5. Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee. N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification, Proceedings of the 14th International Workshop on Mining and Learning with Graphs (MLG), 2018. [pdf]
    6. Joonseok Lee, Nisarg Kothari, Paul Natsev. Content-based Related Video Recommendations, Advances in Neural Information Processing Systems (NIPS) Demonstration Track, 2016. [pdf]
    7. Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee, Paul Natsev, George Toderici, Balakrishnan Varadarajan, Sudheendra Vijayanarasimhan. YouTube-8M: A Large-Scale Video Classification Benchmark, ArXiv:1609.08675, 2016. [pdf] [blog post]
    8. Joonseok Lee, Mingxuan Sun, Guy Lebanon. A Comparative Study of Collaborative Filtering Algorithms, ArXiv:1205.3193, 2012. [pdf]
    9. Kiyeon Lee, Joonseok Lee, Hyunwoong Shin, Sunghwan Kim, Jungwoo Choi. Real-Time Motion Tracking System using Omni-Directional PTZ Camera, Small and Medium Business Administration of South Korea, 2006. [pdf]
  • Theses
    1. Joonseok Lee. Local Approaches for Collaborative Filtering, Georgia Institute of Technology (Ph.D. Dissertation), 2015. [pdf]
    2. Joonseok Lee. Merging Algorithm for Unified Communicator, Seoul National University (Bachelor's Thesis), 2009. [pdf]

Talks and Presentations


Academic Activities


Ongoing Projects

  • Visual-language multi-modal representation learning
  • Video generation using ODE
  • Session-based recommendations

Past Projects

  • Video contents analysis and recommendation
  • Local Collaborative Ranking
  • Local Low-Rank Matrix Approximation
  • Local Context Sparse Coding
  • Graph-based Context-aware Entity Recommendation
  • Ensembles of collaborative filtering algorithms
  • Comparative study of collaborative filtering algorithms
    • Full experimental results (to be added soon)
  • PREA (Personalized Recommendation Algorithms) Toolkit
  • Mood analysis for blog texts

Frequent Collaborators


Interns & Students

  • Joan Puigcerver, Summer Intern 2017. Currently Software Engineer at Google Research.
  • Seong Jae Hwang, Summer Intern 2018. Currently Assistant Professor at University of Pittsburgh.
  • Hyodong Lee, Summer Intern 2019. Currently Software Engineer at Google Research.
  • Inioluwa Deborah Raji, Research Mentorship 2019. Currently Technology Fellow at AI Now Institute.