Lee Newcomer

Lee Newcomer is an advisor at Delfi Diagnostics. Lee has over 12 years of experience in designing and implementing algorithms for interpretation of SNP microarray and high throughput sequencing measurements of human DNA. Lee has also developed and maintained production code in Matlab and Java. Their techniques include maximum likelihood estimation, hidden Markov modeling, Bayesian inference, and machine learning.

Prior to joining Delfi Diagnostics, Lee was a consulting at Natera from November 2008 to February 2021. At Natera, they designed and implemented algorithms for interpretation of SNP microarray and high throughput sequencing measurements of human DNA. Lee also developed and maintained production code in Matlab and Java.

From January 2008 to May 2008, Lee was a Graduate Student Instructor at UC Berkeley for mechanical engineering 231, a graduate-level math course for controls majors. Lee created and graded assignments and exams and taught weekly discussion sections.

From August 2003 to December 2008, Lee was a Graduate Student Researcher at the Berkeley Center for Collaborative Control of Unmanned Vehicles. There they designed algorithms for cooperative control of unmanned aircraft. Lee also conducted field testing of unmanned aircraft teams and developed user interfaces for control of aircraft teams using C++.

Lee began their career as an undergraduate intern at Lawrence Berkeley National Laboratory from June 2001 to August 2002.