Academic Credentials
  • Ph.D., Physics, University of Connecticut, 2021
  • M.S., Theoretical Physics, University of Tehran, 2013
  • B.S., Physics, University of Tabriz, Iran, 2010
Professional Honors
  • Rising Researcher, Penn State Institute for Computational and Data Sciences, 2025
  • Future Leader, Association of Universities for Research in Astronomy, 2024
  • Member of American Astronomical Society (AAS), 2018 -2024

Yasmin Homayouni, Ph.D., is a Physicist and Applied Data Scientist at Exponent with more than 8 years of experience designing and executing complex experiments, conducting advanced statistical and time-series analysis on large-scale datasets.

Dr. Homayouni has led several projects analyzing time-series data to study variability in complex systems, quantifying trends, applying statistical analysis and modeling to extract meaningful signals and interpret system behavior. She has also built Python-based pipelines to automate data preparation and analysis across large datasets, including data cleaning, integration, time-series calibration, and model validation.

Dr. Homayouni has also served as the Principal Investigator on federally funded observing programs with the Hubble Space Telescope, leading the scientific strategy, execution, and reporting of complex observational research programs. In this role, she oversaw all phases of the projects, from observation planning and data acquisition to analysis and reporting to NASA.

Prior to joining Exponent, Dr. Homayouni was an Eberly Postdoctoral Fellow at Penn State University, where she analyzed multi-year data from the Sloan Digital Sky Survey (SDSS) to identify factors influencing measurement success in time-domain studies and assess the impact of data quality, uncertainty, and methodological choices on survey design and scientific decision-making.

Before joining Penn State University, Dr. Homayouni was a postdoctoral researcher at the Space Telescope Science Institute (STScI), where she contributed to the calibration and processing of Hubble data, assessed data quality to improve the reliability of downstream analyses, and collaborated with instrument scientists to enhance a Python-based data reduction pipeline supporting high-resolution observations with the Cosmic Origins Spectrograph. She also served as Executive Officer for an international collaboration of 70 researchers, coordinating scientific priorities, communications, and schedules across the team to ensure timely achievement of project milestones.

Dr. Homayouni's Ph.D. thesis focused on using time-series analysis to study the inner environments of supermassive black holes.