George Linderman

George Linderman is an Assistant Professor in the Department of Applied Mathematics at Yale University's College of Arts and Sciences. He completed his MD-PhD training at Yale, where he focused on high-dimensional data analysis. Currently, he is a General Surgery Resident at Massachusetts General Hospital, applying his computational expertise to clinical training.

• University: Yale University
• Current Role: General Surgery Resident at Massachusetts General Hospital
• Email: george.linderman@yale.edu, glinderman@mgh.harvard.edu

His research spans computational methods for data analysis, including t-SNE acceleration, low-rank matrix approximation, and concentration inequalities. He has developed software packages like FIt-SNE and ALRA, which are widely used in scRNA-seq data visualization and imputation.

The articles listed reflect his contributions to machine learning, computational biology, and clinical research. Notably, his work on t-SNE initialization and scRNA-seq dimensionality reduction has advanced data visualization techniques, while clinical studies on REBOA and laparoscopic surgery highlight his interdisciplinary impact.

He has mentored students through Yale's Directed Reading Program for High Dimensional Probability and served as a Teaching Fellow for Linear Algebra. His academic journey combines rigorous theoretical work with practical applications in both computational biology and surgery.