Personal research portfolio
I am Shi-ang Qi, a Postdoctoral Fellow at the Vector Institute, with affiliations at the Institute for Clinical Evaluative Sciences and the University of Toronto, under the supervision of Dr. Rahul G. Krishnan. My research lies at the intersection of statistical machine learning and biomedical AI, with a focus on clinically meaningful prediction.
I received my Ph.D. in Computer Science from the University of Alberta in November 2025 under the supervision of Dr. Russell Greiner. Prior to that, I completed an M.Sc. in Electrical and Computer Engineering at the University of Alberta under Dr. Jie Chen, and a bachelor's degree in Biomedical Engineering from Huazhong University of Science and Technology.
My recent work includes calibrated survival prediction, Bayesian learning, methods for dependent censoring, cancer risk modeling, multimodal biomedical learning, and representation learning for heterogeneous immune responses. More broadly, I aim to develop machine learning methods that are useful, reliable, and scientifically defensible in healthcare.
Current focus
- In-context learning and foundation models for survival analysis.
- Calibration and discrimination for individualized survival distribution prediction.
- Data identification, evaluation, and model development under dependent censoring.
- Single-cell perturbation modeling and representation learning for transcriptomic prediction.
- Machine learning for cancer risk assessment and prognostic modeling.
Latest Updates
Publications
Conference papers and journal articles.
Talks
Selected talks.
Outside research
Miscellaneous Interests.
During my free time, I enjoy swimming, snowboarding, and hiking with my family. I'm also a big fan of Miami Heat basketball team and Real Madrid football club. ¡Hala Madrid!