Stephen Fleming
About Stephen Fleming
Stephen Fleming is a Machine Learning Scientist II at the Broad Institute of MIT and Harvard, specializing in computational methods for single-cell RNA sequencing data. He has a diverse academic background, including a PhD from Harvard and experience in experimental physics, which informs his work in computational biology.
Current Role at Broad Institute
Stephen Fleming currently serves as a Machine Learning Scientist II at the Broad Institute of MIT and Harvard. He has held this position since 2021 and is based in Cambridge, MA. In this role, he focuses on developing computational methods for single-cell RNA sequencing data within the Data Sciences Platform. His work integrates machine learning techniques with genomics research, contributing to advancements in the field.
Previous Experience at Broad Institute
Prior to his current role, Stephen Fleming worked at the Broad Institute as a Machine Learning Scientist I from 2019 to 2021. His tenure at the institute began with a position as a Computational Scientist I from 2018 to 2019. During these years, he contributed to various projects that combined computational biology and machine learning, enhancing the institute's research capabilities.
Educational Background
Stephen Fleming earned his Bachelor of Science degree from Case Western Reserve University, where he studied from 2007 to 2011. He continued his education at the University of Cambridge, obtaining a Master of Philosophy in 2012. He then pursued a Doctor of Philosophy at Harvard University Graduate School of Arts and Sciences, completing his studies in 2018. His academic background includes a focus on experimental physics, which informs his work in computational biology.
Research Experience
Stephen Fleming has a diverse research background. He began his research career as an Undergraduate Researcher in Physics at Case Western Reserve University from 2007 to 2011. He also worked as an Undergraduate Researcher in Mathematical Biology at the same institution during this time. Following his undergraduate studies, he served as a Graduate Research Fellow and PhD Candidate at Harvard University from 2012 to 2018. Additionally, he was a Churchill Scholar and Graduate Researcher in the Physics of Medicine Program at the University of Cambridge for 11 months in 2011 to 2012.
Interdisciplinary Approach
Stephen Fleming combines his interests in computer programming and machine learning to advance research in genomics. His background in experimental physics provides a unique perspective that enhances his approach to computational biology. This interdisciplinary approach allows him to develop innovative solutions and methodologies, particularly in the analysis of single-cell RNA sequencing data.