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Recent graduate with a doctorate from the Nueromechanics Lab at University of Colorado, Boulder under Alaa Ahmed. Our lab focuses on determining how effort and reward can impact motor decisions in arm reaching.
I’m interested in applying statistical and machine learning techniques to answer research questions about human health and movement from a data science perspective. We analyze large biomedical data sets to find significant factors influencing movement. Specifically training machine learning methods to predict the cost of a movement.
My research focuses on evaluating effort in these movements. Using a robotic arm manipulandum specifally designed for these tasks, we can alter the effort of reaching by adding inertial or resistive forces as subjects make reaching movements. I use objective measures of effort via metabolic cost and computational modeling techniques to evaluate how effort is represented in arm reaching movements.
My main research projects are determining the effects of mass on the metabolic cost of reaching and how this affects preferred reachign decisions, how we can use a utility model to predict these changes, and then creating a biomechanical model of the arm to estimate these effort costs using common neuromechanical proxies.
As an undergrad I spent two summers working at NIST. I worked on developing a method to accurately measure flow of liquid within an MRI system and developing a microfluidic AC Susceptometer for mangetic nanoparticle solutions. Both project were funded by the NIST SURF fellowship.