Mahnaz Maddah
About Mahnaz Maddah
Mahnaz Maddah serves as the Director of Machine Learning at the Broad Institute of MIT and Harvard, a position she has held since 2022. With a background in electrical and electronics engineering, she has extensive experience in AI applications, particularly in drug efficacy and safety testing.
Work at Broad Institute
Mahnaz Maddah serves as the Director of Machine Learning at the Broad Institute of MIT and Harvard. She has held this position since 2022, contributing to the institute's research and development in machine learning applications within the biomedical field. The Broad Institute is known for its collaborative approach to scientific research, and Maddah's role involves leveraging machine learning techniques to enhance data analysis and interpretation in various projects.
Education and Expertise
Mahnaz Maddah earned her Ph.D. in Electrical Engineering and Computer Science (EECS) from the Massachusetts Institute of Technology, where she studied from 2004 to 2008. Prior to that, she obtained her M.Sc. in Electrical and Electronics Engineering from the University of Tehran, completing her studies there from 2000 to 2002. Her educational background provides a strong foundation in both theoretical and practical aspects of machine learning and computer vision.
Professional Background
Mahnaz Maddah has a diverse professional background that includes significant roles in various organizations. She worked as a Managing Partner at Dana Solutions from 2015 to 2020, where she co-founded the company before its acquisition by Curi Bio. Prior to that, she held positions as a Research Scientist at SRI International and as a Lead Computer Vision Scientist at Progyny, Inc. Her experience spans research, development, and leadership in machine learning and computer vision.
Achievements in Machine Learning and AI
Mahnaz Maddah has made notable contributions to the field of machine learning and artificial intelligence. She developed an AI-based cell counting software for infertility medical devices and created an AI-based phenotypic drug screening platform. Additionally, she invented Pulse, a pioneering computer vision product for the non-invasive characterization of stem-cell derived cardiomyocytes. Her work has included collaboration with the FDA to develop deep learning methods for in-vitro drug toxicity testing.
Speaking Engagements and Collaborations
Mahnaz Maddah has been an invited speaker at various events that focus on the applications of AI in drug efficacy and safety testing. Her expertise in machine learning has led to collaborations with regulatory bodies and contributions to significant advancements in the field. These engagements highlight her commitment to advancing the understanding and application of AI technologies in healthcare and biomedical research.