Academic Credentials
  • Ph.D., Engineering Mechanics, Michigan State University, 2019
  • B.S., Material Science, Michigan State University, 2014

Dr. Drost's areas of expertise include biomechanics specifically with respect to the upper extremity, imaging analysis, fracture mechanics, kinematics and kinetics of human motion, and simulation of tissue mechanics and blood flow. His research and testing experience are centered around developing unique testing protocols utilizing a variety of laboratory and clinical tools to calculate biomechanical metrics.

Dr. Drost's research prior to starting at Exponent focused on identifying clinically measurable parameters that could be used for early diagnosis of conditions related to aging. While studying as a Graduate Research Assistant in the Biomechanics Design and Research Lab at Michigan State University, Dr. Drost assessed quantifiable changes in finger function due to osteoarthritis and evaluated how hand and finger function could be improved by different surgical interventions. Additionally, while researching as a Post-Doctoral Fellowship in the Bone and Joint Center at Henry Ford Hospital in Detroit, Michigan, he assessed the biomechanical loading in vertebrae at risk for osteoporotic fractures using advanced techniques for assessing medical imaging (e.g. using digital volume correlation on digital tomosynthesis images). Dr. Drost has experience collecting and analyzing kinematic and kinetic data collected from high-speed motion capture systems (Qualysis) and load cells (AMTI) using advanced computational methods (Matlab, R, Python, ImageJ). 

Since joining Exponent, Dr. Drost has utilized his experience and expertise to develop unique protocols for the testing and evaluation of biomechanical outcomes in a broad range of environments and use cases. These efforts continue to target various immersed and real-world environments, consumer products and technologies, medical devices, AI and ML algorithm characterization and benchmarking. Dr. Drost has additional expertise in designing and implementing large scale user studies to support these above capabilities, drawing on substantial knowledge of state of the art technologies and equipment and supporting data processing and analysis tools.