Miranda Schwacke is a PhD candidate whose research is focused on developing energy-efficient hardware for machine learning and brain-inspired computing, with the broader goal of reducing the fast-growing energy demands of computing (and associated CO2 emissions) while nurturing technological innovation. Specifically, Miranda is designing and testing electrochemical ionic synapses (EIS), an emerging technology for analog resistive switching in which electrochemically controlled intercalation of ions into and out of a channel allows for dynamic doping of the channel, tuning its resistance. Supported by a MathWorks Fellowship, she aims to expand the types of working ions that can be used in EIS. She also seeks to better understand how channel microstructure impacts device performance, enabling the design of novel, all-solid-state, scalable, fast, energy-efficient, and non-volatile EIS for neuromorphic computing. MATLAB has been instrumental in writing custom scripts for device testing and data analysis. Miranda’s research, integrating materials science and engineering, electrochemistry, and device fabrication and characterization, has the potential to yield important contributions to energy-efficient, brain- inspired computing.