Biography
Dr. Sun is a Health Innovation Professor at the Computer Science Department and Carle's Illinois College of Medicine at University of Illinois Urbana Champaign. Before UIUC, he was an associate professor in College of Computing at Georgia Tech (GT) and the co-director of the Center for Health Analytics and Informatics (CHAI) at GT.
His research focuses on artificial intelligence (AI) for healthcare, including deep learning for drug discovery, clinical trial optimization, computational phenotyping, clinical predictive modeling, treatment recommendation, and health monitoring. He was recognized as one of the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare by Deep Knowledge Analytics.
He completed his B.S. and M.Phil. in computer science at Hong Kong University of Science and Technology in 2002 and 2003, respectively, and his Ph.D. in computer science at Carnegie Mellon University in 2007.
Research Interests
AI for healthcare
Related to neuroscience, his research is around machine learning on EEG signals, seizure phenotyping, automated sleep medicine and EEG report generation.
Education
PhD in Computer Science from Carnegie Mellon University
Courses Taught
CS598 - Deep learning for healthcare
Additional Campus Affiliations
Computer Science, Carle's Illinois College of Medicine
External Links
Highlighted Publications
Jing J*, Ge W*, Struck AF, Fernandes MB, Hong S, An S, Fatima S, Herlopian A, Karakis I, Halford JJ, Ng MC, Johnson EL, Appavu BL, Sarkis R, Osman G, Kaplan PW, Dhakar MB, Jayagopal LA, Sheikh Z, Taraschenko O, Schmitt S, Haider HA, Kim JA, Swisher CB, Gaspard N, Cervenka MC, Ruiz AAR, Lee JW, Tabaeizadeh MT, Gilmore EJ, Nordstrom K, Yoo JY, Holmes MG, Herman ST, Williams JA, Pathmanathan J, Nascimento FA, Fan Z, Nasiri S, Shafi MM, Cash SS, Hoch DB, Cole AJ, Rosenthal ES, Zafar S, Sun J, Westover MB. “Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in Electroencephalograms.”
Jing J*, Ge W*, Hong S, Fernandes MB, Lin Z, Yang C, An C, Struck AF, Herlopian A, Karakis I, Halford JJ, Ng M, Johnson EL, Appavu BL, Sarkis R, Osman G, Kaplan PK, Dhakar MB, Jayagopal LA, Sheikh Z, Taraschenko O, Schmitt S, Haider HA, Kim JA, Swisher C, Gaspard N, Cervenka MC, Ruiz AAR, Lee JW, Tabaeizadeh M, Gilmore EJ, Nordstrom K, Yoo JY, Holmes MG, Herman ST, Williams J, Pathmanathan J, Nascimento FA, Fan Z, Nasiri S, Shafi MM, Cash SS, Hoch DB, Cole Aj, Rosenthal ES, Zafar S, Sun J, Westover MB. “Development of Expert-level Classification of Seizures and Rhythmic and Periodic Patterns During EEG Interpretation.” to appear in Neurology
Siddharth Biswal, Cao Xiao, Lucas Glass, M. Brandon Westover and Jimeng Sun "Clinical Report Auto-completion."In Proceedings of WWW, 2020, 541-550
Siddharth Biswal, Cao Xiao, M. Brandon Westover and Jimeng Sun "EEGtoText: Learning to Write Medical Reports from EEG Recordings."In Proceedings of MLHC, 2019, 513-531
Recent Publications
Aljiffry, A., Xu, Y., Hong, S., Long, J. B., Sun, J., & Maher, K. O. (2023). Artificial intelligence and clinical stability after the Norwood operation. Journal of Medical Artificial Intelligence, 6. https://doi.org/10.21037/jmai-22-35
Arenson, M., Hogan, J., Xu, L., Lynch, R., Lee, Y. T. H., Choi, J. D., Sun, J., Adams, A., & Patzer, R. E. (2023). Predicting Kidney Transplant Recipient Cohorts’ 30-Day Rehospitalization Using Clinical Notes and Electronic Health Care Record Data. Kidney International Reports, 8(3), 489-498. https://doi.org/10.1016/j.ekir.2022.12.006
Das, T., Wang, Z., & Sun, J. (2023). TWIN: Personalized Clinical Trial Digital Twin Generation. In KDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 402-413). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). Association for Computing Machinery. https://doi.org/10.1145/3580305.3599534
Gao, J., Heintz, J., Mack, C., Glass, L., Cross, A., & Sun, J. (2023). Evidence-driven spatiotemporal COVID-19 hospitalization prediction with Ising dynamics. Nature communications, 14(1), Article 3093. https://doi.org/10.1038/s41467-023-38756-3
Jiang, P., Agarwal, S., Jin, B., Wang, X., Sun, J., & Han, J. (2023). Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models. In Findings of the Association for Computational Linguistics, ACL 2023 (pp. 11161-11180). (Proceedings of the Annual Meeting of the Association for Computational Linguistics). Association for Computational Linguistics (ACL).