Academic Credentials
  • Ph.D., Mechanical Engineering, University of Texas - Austin, 2022
  • M.S., Mechanical Engineering, University of Texas - Austin, 2020
  • B.S., Mechanical Engineering, University of Texas - Austin, 2016
Professional Honors
  • 1st Place, ME Graduate Student Poster Session
  • 2nd Place, American Society of Biomechanics 3-Minute Thesis Competition
  • Honorable Mention, NSF Graduate Research Fellowship Program
  • Best Student Poster Award, CARE Research Day Poster Competition
  • College Scholar, Cockrell School of Engineering
  • Tau Beta Pi Engineering Honor Society
  • Gamma Beta Phi Honor Society
Professional Affiliations
  • American Society of Biomechanics (ASB)

Dr. Molina's expertise is in human biomechanics, including the human kinematics, dynamics and performance. She has extensive experience developing and analyzing models and simulations of human movement, applying machine learning algorithms on sensor data to classify human movement, and using kinematic and kinetic data to assess motion from healthy and clinical populations. Dr. Molina has expertise in the collection and analysis of biomechanical data using high-speed motion capture systems, inertial measurement units (IMUs), force transducers, and electromyography (EMG).

Prior to joining Exponent, Dr. Molina was a Graduate Research Assistant in the Neuromuscular Biomechanics Lab at The University of Texas at Austin. Her research focused on using machine learning to detect falls for lower limb amputees, understanding strategies used for balance recovery in healthy individuals, and analyzing the relationship between muscle coordination and turning performance in individuals post-stroke.