Miranda Schwacke, a graduate student in the Department of Materials Science and Engineering at MIT, investigates the high energy consumption of artificial intelligence (AI) systems. Her work on neuromorphic computing aims to develop materials that mimic brain processes, potentially leading to more sustainable AI technologies. Schwacke’s approach uses electrochemical ionic synapses to create devices that can adjust conductivity, similar to how neurons operate. By decreasing energy use in AI, Schwacke seeks to create brain-inspired solutions that consume less power than traditional computing. Her advisor, Bilge Yildiz, emphasizes the significance of this research in addressing unsustainable energy demands in computing.
Schwacke’s journey into materials science began with a fascination for how materials behave at atomic levels. She studied at Caltech before joining MIT, where her focus has been on developing technologies to bridge the gaps between electrochemistry and semiconductor physics. Her current PhD project investigates how magnesium ions affect electrical resistance in tungsten oxide, which is crucial for the performance of neuromorphic devices. Schwacke’s research was recognized with a MathWorks Fellowship, supporting her data analysis efforts through advanced computational tools. With a vision for academia post-PhD, she aims to inspire future scientists through her commitment to science communication and community engagement.
👉 Pročitaj original: MIT AI News
