A. Norcliffe, C. Lee, F. Imrie, M. van der Schaar, P. Lio, "Stochastic Encodings for Active Feature Acquisition," accepted to International Conference on Machine Learning (ICML), 2025.
D. Lee*, H. Park*, C. Lee, "Toward a Better Discrimination and Calibration via Survival Outcome-Aware Contrastive Learning," Conference on Neural Information Processing Systems (NeurIPS), 2024. [Link]
H. Kim, C. Lee, "Enhancing Anomaly Detection via Generating Diversified and Hard-to-distinguish Synthetic Anomalies," International Conference on Information and Knowledge Management (CIKM), 2024. [Link]
C. Kim, M. van der Schaar, C. Lee, "Discovering Features with Synergistic Interactions in Multiple Views," International Conference on Machine Learning (ICML), 2024. [Link]
M. Choi, C. Lee, "Conditional Information Bottleneck Approach for Time Series Imputation," International Conference on Learning Representations (ICLR), 2024. [Link]
Y. Qin, M. van der Schaar, C. Lee, "Risk-Averse Active Sensing for Timely Outcome Prediction under Cost Pressure," Conference on Neural Information Processing Systems (NeurIPS), 2023. [Link]
S. Park*, B. Park*, M. Lee, C. Lee, “Neural Stochastic Differential Games for Time-series Analysis,” International Conference on Machine Learning (ICML), 2023. [Link]
Y. Qin, M. van der Schaar, C. Lee, "T-Phenotype: Discovering Phenotypes of Predictive Temporal Patterns in Disease Progression," International Conference on Artificial Intelligence and Statistics (AISTATS), 2023. [Link]
C. Lee*, F. Imrie*, M. van der Schaar, “Self-Supervision Enhanced Feature Selection with Correlated Gates,” International Conference on Learning Representations (ICLR), 2022. [Link] (spotlight)
A. Curth*, C. Lee*, M. van der Schaar, “SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data,” Conference on Neural Information Processing Systems (NeurIPS), 2021. [Link]
C. Lee, M. van der Schaar, “A Variational Information Bottleneck Approach to Multi-Omics Data Integration,” International Conference on Artificial Intelligence and Statistics (AISTATS), 2021. [Link] (oral presentation)
C. Lee, M. van der Schaar, “Temporal Phenotyping using Deep Predictive Clustering of Disease Progression,” International Conference on Machine Learning (ICML), 2020. [Link]
C. Lee, W. R. Zame, A. M. Alaa, M. van der Schaar, “Temporal Quilting for Survival Analysis,” International Conference on Artificial Intelligence and Statistics (AISTATS), 2019. [Link]
C. Lee, W. R. Zame, J. Yoon, M. van der Schaar, “DeepHit: A Deep Learning Approach to Survival Analysis with Competing Risks,” AAAI Conference on Artificial Intelligence (AAAI), 2018. [Link] (spotlight)
* Equal contribution
A. Shah, B. Zukotynski, C. Kim, B. Shi, C. Lee, S. Devana, A. Upfill-Brown, E. Mayer, N. SooHoo, C. Lee, "Predicting Discharge Destination and Length of Stay after Open Reduction Internal Fixation of Distal Femur Fractures," OTA International, Jun. 2025. [Link]
A. Choi*, C. Kim*, J. Jeon, S. Cho, D. Lee, J. Kim, C. Lee**, W. Bae**, "A Pediatric Emergency Prediction Model using Natural Language Process in the Pediatric Emergency Department," Scientific Reports, Jan. 2025. [Link]
MARS Group, K. Vasavada, V. Vasavada, J. Moran, S. Devana, C. Lee, et al., "A Novel Machine Learning Model to Predict Revision ACL Reconstruction Failure in the MARS Cohort," Orthopaedic Journal of Sports Medicine, Nov. 2024. [Link]
J. Jeon, S. Cho, D. Lee, C. Lee, J. Kim, "BioBridge: Unified Bio-Embedding with Bridging Modality in Code-Switched EMR," IEEE Access, Sep. 2024. [Link]
K. M. Park, S. E. Lee, C. Lee, H. D. Hwang, D. H. Yoon, E. Choi, and E. Lee, "Predicting Sleep Based on Physical Activity, Light Exposure, and Heart Rate Variability Data Using Wearable Devices," Annals of Medicine, Sep. 2024. [Link]
S. Cho, J. Jeon, D. Lee, C. Lee, J. Kim, "DSG-KD: Knowledge Distillation from Domain-Specific to General Language Models," IEEE Access, Sep. 2024. [Link]
H. Park, C. Lee, "Feature Selection with Group-Sparse Stochastic Gates," IEEE Access, July 2024. [Link]
H.-J. Choi, C. Lee, J. Chun, R. Seol, Y. Lee, Y.-J. Son, "Development of a Predictive Model for Survival over Time in Patients with Out-of-Hospital Cardiac Arrest using Ensemble-based Machine Learning," Computers, Informatics, Nursing, May 2024. [Link]
H. Park, H. Kim, C. Lee, H. Lee, "Mobility Management Paradigm Shift: from Reactive to Proactive Handover using AI/ML," IEEE Network, Mar. 2024. [Link]
A. Shah, S. Devana, C. Lee, N. SooHoo, "A Predictive Algorithm for Perioperative Complications and Readmission after Ankle Arthrodesis," European Journal of Orthopaedic Surgery and Traumatology, Jan. 2024. [Link]
A. Shah, S. Devana, C. Lee, T. Olson, A. Upfill-Brown, W. Sheppard, E. Lord, A. Shamie, M. van der Schaar, N. SooHoo, D. Park, "Development and External Validation of a Risk Calculator for Prediction of Major Complications and Readmission after Anterior Cervical Discectomy and Fusion," Spine, Apr. 2023. [Link]
C. Lee*, A. Light*, E. Saveliev*, M. van der Schaar, V. J. Gnanapragasam, “Development and Clinical Utility of Machine Learning Algorithms for Dynamic Longitudinal Real-Time Estimation of Progression Risks in Active Surveillance of Early Prostate Cancer,” npj Digital Medicine, Aug. 2022. (Impact Factor: 15.357) [Link]
A. Shah, S. Devana, C. Lee, A. Bugarin, E. L. Lord, A. N.Shamie D. Y. Park, M. van der Schaar, N. SooHoo, “Machine Learning-Driven Identification of Novel Patient Factors for Prediction of Major Complications after Posterior Cervical Spinal Fusion,” European Spine Journal, Aug. 2022. [Link]
A. Shah, S. Devana, C. Lee, A. Bugarin, M. Hong, A. Upfill-Brown, G. Blumstein, E. Lord, A. Shamie, M. van der Schaar, N. SooHoo, D. Park, “A Risk Calculator for Prediction of C5 Nerve Root Palsy after Instrumented Cervical Fusion,” World Neurosurgery, July, 2022. [Link]
S. Devana, A. Shah, C. Lee, A. Jensen, E. Cheung, M. van der Schaar, N. SooHoo, “Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission Following Primary Anatomic Total Shoulder Replacements,” Journal of Shoulder and Elbow Arthroplasty, Apr. 2022. [Link]
K. M. Park, S. E. Lee, C. Lee, H. D. Hwang, D. H. Yoon, E. Choi, and E. Lee, "Prediction Of Good Sleep With Physical Activity and Light Exposure: A Preliminary Study," Journal of Clinical Sleep Medicine, Jan. 2022. [Link]
S. Devana, A. Shah, C. Lee, V. Gudapati, A. Jensen, E. Cheung, C. Solorzano, M. van der Schaar, N. SooHoo, “Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission following Reverse Total Shoulder Arthroplasty,” Journal of Shoulder and Elbow Arthroplasty, Oct. 2021. [Link]
C. Lee, J. Rashbass, M. van der Schaar, “Outcome-Oriented Deep Temporal Phenotyping of Disease Progression,” IEEE Transactions on Biomedical Engineering, Aug. 2021. [Link]
S. Devana, A. Shah, C. Lee, A. Roney, M. van der Schaar, N. SooHoo, “A Novel, Potentially Universal Machine-Learning Algorithm to Predict Complications in Total Knee Arthroplasty,” Arthroplasty Today, Aug. 2021. [Link]
A. Shah, S. Devana, C. Lee, A. Bugarin, E. L. Lord A. N.Shamie D. Y. Park, M. van der Schaar, N. SooHoo, “Prediction of Major Complications and Readmission after Lumbar Spinal Fusion: A Machine Learning-Driven Approach,” World Neurosurgery, Aug. 2021. [Link]
A. Shah, S. Devana, C. Lee, R. Kianian, M. van der Schaar, N. SooHoo, “Development of a Novel, Potentially Universal Machine Learning Algorithm for Prediction of Complications After Total Hip Arthroplasty,” The Journal of Arthroplasty, May. 2021. [Link]
C. Lee*, A. Light*, A. Alaa, D. Thurtle, M. van der Schaar, V. J. Gnanapragasam, “Application of a Novel Machine Learning Framework for Predicting Cancer-Specific Mortality: Analysis of 171,942 Men with Non-Metastatic Prostate Cancer from the Surveillance, Epidemiology, and End Results Dataset,” The Lancet Digital Health, Feb. 2021. [Link] (Impact Factor: 36.615)
C. Lee, J. Yoon and M. van der Schaar, “Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis with Competing Risks based on Longitudinal Data,” IEEE Transactions on Biomedical Engineering, Jan. 2020. [Link]
* Equal contribution (first authors)
** Equal contribution (corresponding authors)
M. Hwang, D. Lee, C. Lee, "Deep Survival Analysis from Whole Slide Images: A Multiple Instance Learning Approach," accepted to International Conference on ICT Convergence (ICTC), 2024. [Link]
H. Kim, C. Lee, "Time-series Anomaly Detection based on Imputation in the Latent Space," International Conference on ICT Convergence (ICTC), 2024. [Link]
H. Park, E. Kim, C. Lee, "A Comprehensive Evaluation of Time-Series Forecasting Methods for Proactive Handover," accepted to International Conference on ICT Convergence (ICTC), 2024. [Link] (Best paper award)
M. Choi, C. Lee, "Clinical Time Series Imputation using Conditional Information Bottleneck," NeurIPS DGM4H (Deep Generative Models for Health) Workshop, 2023. [Link]
C. Lee, C. Lee, T. Ha, S. Cho, "Survey: Strategies for Loss-Based Discrete-Time Hazard and Survival Function Estimation, " International Conference on ICT Convergence (ICTC), 2022. [Link]
C. Lee, N. Mastronarde, M. van der Schaar, "Estimation of Individual Treatment Effect in Latent Confounder Models via Adversarial Learning," NeurIPS Machine Learning for Health (ML4H) Workshop, 2018. [Link]
International Journals
S.-M. Oh, C. Lee, J.-H. Lee, A.-S. Park, J.-S. Shin, “Efficient Interference Control Technology for Vehicular Moving Network (VMN),” ETRI Journal, Oct. 2015. [Link] (Best paper award)
S.-H. Moon, C. Lee, S.-R. Lee, I. Lee, “Joint User Scheduling and Adaptive Intercell Interference Cancelation for MISO Downlink Cellular Systems,” IEEE Transactions on Vehicular Technology, Jan. 2013. [Link]
Selected Conferences
C. Lee, S.-M. Oh, J.-S. Shin, “Resource Allocation for Device-to-Device Communications based on Graph-Coloring,” International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), 2015. [Link]
C. Lee, S.-M. Oh, A.-S. Park, “Interference Avoidance Resource Allocation for D2D Communication Based on Graph-Coloring,” International Conference on ICT Convergence (ICTC), 2014. [Link]
S.-M. Oh, H.-Y. Hwang, C. Lee, J.-S. Shin, “An Efficient Signaling Procedure for Stationary Machine Type Devices,” International Conference on ICT Convergence (ICTC), 2015. [Link]
H.-Y. Hwang, S.-M. Oh, C. Lee, J.-H. Kim and J.-S. Shin “Dynamic RACH Preamble Allocation Scheme,” International Conference on ICT Convergence (ICTC), 2015. [Link]
S.-H. Moon, C. Lee, S.-R. Lee, I. Lee, “A Joint Adaptive Beamforming and User Scheduling Algorithm for Downlink Network MIMO Systems,” IEEE International Conference on Communications (ICC), 2013. [Link]
C. Lee, S.-H. Moon, S.-R. Lee, I. Lee, “Adaptive Beamforming Selection Methods for Inter-cell Interference Cancellation in Multicell Multiuser Systems,” IEEE International Conference on Communications (ICC), 2013. [Link]
C. Lee, E. Park, I. Lee, “Antenna Placement Designs for Distributed Antenna Systems with Multiple-Antenna Ports,” IEEE Vehicular Technology Conference Fall (VTC Fall), 2012. [Link]
US Patents
O. Park, C. Kim, G. Y. Park, C. Lee, “Device and Method for Transmitting Reference Signal,” US Patent No. 10,447,445, 2019.
C. Lee, T. Kwon, J. H. Kim, J. Kim, O. Park, J. Shin, S. Oh, H. Hwang, “Method and Apparatus for Controlling Random Access Opportunity in Mobile Communication System,” US Patent No. 10,004,089, 2018.
C. Lee, W. Shin, S. Oh, A. S. Park, J. H. Lee, “Method and Apparatus for Synchronization in D2D Communication Network,” US Patent No. 9,867,156, 2018.
W. Shin, C. Lee, S. Moon, Y. J. Ko, “Method and Apparatus for Device-to-Device Communication,” US Patent No. 9,832,800, 2017.