Rachel Wang

Dr. Rachel Wang is an Associate Professor in the School of Mathematics and Statistics at the University of Sydney. Her research focuses on statistical network modeling, machine learning, and applications to genomics. She holds a PhD from UC Berkeley and completed postdoctoral work at Stanford University. Previously, she was a Harrington Faculty Fellow at the University of Texas, Austin.

Education:

• PhD in Statistics, UC Berkeley
• Postdoctoral Fellowship, Department of Statistics, Stanford University

Research Interests:

• Statistical methods for biological networks
• High-dimensional data analysis
• Single-cell genomics and multimodal data integration
• Conformal prediction and robust classification

Grants and Awards:

• Harrington Faculty Fellow (2021-2022)
• Australian Research Council Discovery Early Career Researcher Award (2017)

Teaching:

• STAT3023/3923 Statistical Inference (University of Sydney)
• STAT2011 Probability and Estimation Theory (course coordinator)
• Past teaching roles at Stanford University

Research Tools: Developed scTIE and scJoint methods for single-cell data integration, and contributed to TAD boundary detection algorithms in genome analysis.