Current Research
I work on refining the design and fabrication method of the Leafout origami structure in the Laboratory for Engineered Materials and Structures (LEMS) at the University of Washington. I help gather empirical results to substantiate the findings from my lab mentor's simulation testing. By creating prototype Leafout structures that replicate our simulation results, we can validate the accuracy of the data we collect on the Project Chrono physics engine. This has allowed us to apply various machine learning techniques to the Leafout in order to determine optimized folding patterns. This research aims to prove the impact that structurally efficient designs can have on energy efficiency in the field of robotics through a utilization of rigid origami structures.
Photographed above is myself and Hiromi Yasuda in the UW's LEMS
Research Interests
Many research labs are funded for being at the forefront of creating and supplying new technologies, with research that is often focused
on making devices more small, efficient, or economical. To better assimilate myself into all
three of these innovative spheres, I honed my research interests on creating more energy
efficient robotics by utilizing more structurally efficient systems that take advantage of
kinematic properties. I am interested in pursuing nanoscale actuators tailored to initiate small amplitude stimuli on bi-stable structures
with maximized energy wells. To do this I hope
to accumulate technical training from multiple fields in order to bolster my interdisciplinary
understanding of robotics, a skillset that will help me bridge interconnected postulates in the field of energy efficiency into a single, innovative system.
Photographed above is myself and Rajesh Chaunsali in the Launchpad at QUT, Australia
EDUCATION
RESEARCH INTERESTS
Energy Efficient Robotic Structures
2017 - Current
University of Washington
Electrical Engineering, Concentration: controls
Minor: Mathematics
Bio-inspired Origami with Micro-
electromechanical Actuators
http://mechanicaldesign.asmedigitalcollection.asme.org/article.aspx?articleid=2464662
DeepQ Machine Learning
Summer 2018
Queensland University of Technology
Aeronautics & Astronautics Design of Novel Materials and Structures
2016 - 2017
University of Utah