Ali Shojaie

Ali Shojaie is a Professor of Biostatistics & Statistics at the University of Washington, currently serving as Interim Chair of Biostatistics. His research bridges statistical learning, network analysis, and high-dimensional data modeling with applications in biological and health sciences.

Research Focus: Shojaie develops advanced methodologies for causal inference, spatial statistics, and semi-supervised learning. His recent work includes network-based gene set analysis, Granger causality estimation, and regularization techniques for complex data structures.

Scientific Contributions:

• Received the 2022 Leo Breiman Award for innovative statistical learning research
• Elected as Fellow of the Institute for Mathematical Statistics (IMS) and American Statistical Association (ASA)
• Secured major NIH grants for projects on gene-phenotype associations and explainable AI in neuroscience

Advising & Leadership: His students have won multiple awards at ASA and AISTAT conferences. He co-developed the netgsa and spacejam R packages for network-based analysis and spatial modeling.

Current Projects: Shojaie leads NIH-funded research on prefrontal brain stimulation and gene knockout studies, combining statistical theory with interdisciplinary applications in biology and bioengineering.