
About
Geoffrey Schiebinger is an Associate Professor of Mathematics at the University of British Columbia. His work bridges theoretical mathematics and experimental biology, focusing on optimal transport theory applied to high-dimensional gene expression data. He leads a research group developing mathematical tools for analyzing single-cell RNA sequencing and spatial omics data.
Education:
- PhD in Statistics, UC Berkeley (2016), advised by Benjamin Recht
- M.S. in Electrical Engineering, Stanford University (2011)
- B.S. in Mathematics (minor in Physics), Stanford University
Research interests center on understanding cellular differentiation processes, such as how stem cells transform into specialized cell types. His group applies optimal transport theory to model transcriptional landscapes and lineage trajectories, with applications in immunology, developmental biology, and cancer research. Key projects include the Waddington-OT framework for trajectory inference and DNA-GPS spatial genomics methodology.
Notable awards include the 2022 Michael Smith Health Research BC Scholar Award and 2021 Maud Menten Prize. His grants include top rankings in Canadian genomics funding (CIHR Project Grant 1st place, 2021) and support from the Chan Zuckerberg Initiative.
Advising: Supervises postdocs (Matthieu Heitz, Andrew Warren) and graduate students (e.g., Cole Boyle). Alumni include faculty at Wake Forest and Chinese University of Hong Kong. Active hiring: Postdoctoral and graduate positions available in mathematical biology and statistical genomics.
Labs/Teams: Leads the Schiebinger Lab at UBC, collaborating with Philippe Rigollet (MIT) on Human Cell Atlas projects. Active in developing open-source tools for single-cell analysis.
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