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
Cao, L., Sun, J., & Cross, A. (2024). An Automatic and End-to-End System for Rare Disease Knowledge Graph Construction Based on Ontology-Enhanced Large Language Models: Development Study. JMIR Medical Informatics, 12, Article e60665. https://doi.org/10.2196/60665
Cao, L., Wang, Z., Xiao, C., & Sun, J. (2024). PILOT: Legal Case Outcome Prediction with Case Law. In K. Duh, H. Gomez, & S. Bethard (Eds.), Long Papers (pp. 609-621). (Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024; Vol. 1). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.naacl-long.34
Danek, B. P., Makarious, M. B., Dadu, A., Vitale, D., Lee, P. S., Singleton, A. B., Nalls, M. A., Sun, J., & Faghri, F. (2024). Federated learning for multi-omics: A performance evaluation in Parkinson's disease. Patterns, 5(3), Article 100945. https://doi.org/10.1016/j.patter.2024.100945
Jiang, P., Lin, J., Wang, Z., Sun, J., & Han, J. (2024). GENRES: Rethinking Evaluation for Generative Relation Extraction in the Era of Large Language Models. In K. Duh, H. Gomez, & S. Bethard (Eds.), Long Papers (pp. 2820-2837). (Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024; Vol. 1). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.naacl-long.155
Jiang, P., Xiao, C., Cross, A., & Sun, J. (2024). GRAPHCARE: ENHANCING HEALTHCARE PREDICTIONS WITH PERSONALIZED KNOWLEDGE GRAPHS. Paper presented at 12th International Conference on Learning Representations, ICLR 2024, Hybrid, Vienna, Austria.