Danielle Pace
About Danielle Pace
Danielle Pace is a Senior Machine Learning Scientist at the Broad Institute of MIT and Harvard, specializing in machine learning solutions for medical image analysis. With a strong academic background and diverse experience in both industry and research, she has contributed significantly to advancements in medical imaging technology.
Work at Broad Institute
Danielle Pace has been serving as a Senior Machine Learning Scientist at the Broad Institute of MIT and Harvard since 2023. In this role, she focuses on developing machine learning and computer vision algorithms tailored for medical imaging applications. Her work contributes to the advancement of medical image analysis, enhancing the capabilities of healthcare technology.
Previous Experience
Before her current position, Danielle Pace worked as a Research Fellow at Massachusetts General Hospital from 2020 to 2023. She also held a Visiting Ph.D. Candidate position at Philips for two months in 2017. Her experience includes a role as a Research Specialist at the Massachusetts Institute of Technology for one month in 2020 and as a Research & Development Engineer at Kitware Inc. from 2010 to 2013.
Education and Expertise
Danielle Pace earned her Doctor of Philosophy (PhD) in Computer Science from the Massachusetts Institute of Technology, where she studied from 2013 to 2020. Prior to that, she completed her Master of Engineering Science in Biomedical Engineering at Western University from 2007 to 2010 and her Bachelor of Computing (Honours) in Biomedical Computing at Queen's University from 2003 to 2007. She also pursued part-time studies in Mathematics at the University of North Carolina at Chapel Hill from 2012 to 2013.
Background
Danielle Pace has a diverse background in both academic and industry settings. She has worked in various roles that contribute to advancements in medical imaging technology. Her experience spans multiple institutions, including significant roles at prestigious organizations such as the Broad Institute and Massachusetts General Hospital, reflecting her commitment to the field of medical image analysis.