Alex Lash, M.D.

Chief Informatics Officer, Simons Foundation


Alex Lash joined the Simons Foundation in March 2012 to lead the further development and dissemination of the foundation’s extensive scientific data assets — particularly those related to autism spectrum disorders — as well as to oversee the automation of its scientific administration infrastructure and develop metrics of funding impact.

Lash was at Memorial Sloan-Kettering Cancer Center in New York from 2003 to 2012, where he was a laboratory member in the computational biology program and scientific director of the bioinformaticscore facility. By 2012, he had overseen the growth of the bioinformatics core to include more than a dozen doctoral and masters-level personnel who provide research-support services in the areas of high throughput sequence and microarray data analysis, high performance computing, bioinformatics training and research software development.

From 1998 to 2003, at the height of the human genome sequencing initiative, Lash was a staff scientist at the National Center for Biotechnology Information (NCBI) at the National Institutes of Health in Bethesda, Maryland. At NCBI, Lash led a group that was responsible for creating the national repository for public gene expression data. Later, the scope of the repository was expanded to include the data generated from a spectrum of high throughput microarray platforms, such as array comparative genome hybridization, as well as proteomics data. While there, Lash received several awards from the National Library of Medicine and the Department of Health and Human Services.

Lash has an M.D. from Baylor College of Medicine in Houston, and completed his residency training in anatomic pathology at the National Cancer Institute in 1998, where he was recognized by the Arthur Purdy Stout Society of Surgical Pathologists. Lash also has a B.S. in biological sciences from the University of California at Irvine. He has been programming in various computer languages since his early teens and has a passion for using information technology to improve human efficiency and reduce the likelihood and impact of human error.

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