Artificial intelligence (AI) is all around us. It powers virtual assistants, smartwatches, map apps, and more. Advances in AI also benefit a range of industries from communications, to agriculture, to healthcare. But AI has an efficiency problem. When IBM’s Watson computer competed on Jeopardy!, it required approximately 200,000 watts of energy, while the human brain, a powerful computational tool in its own right, uses just twenty.
Youngeun Kim ’26 PhD wants to build more efficient AI. Studying under Priyadarshini Panda, an assistant professor of electrical engineering, Kim uses the human brain as inspiration. “Neurons transmit information in a particular way, through electrical activity called action potentials,” says Kim. “I’m building algorithms that work in a similar manner to neurons.” Kim is a graduate student in the School of Engineering & Applied Science (SEAS). And while the pandemic has led to a non-traditional first-year experience for him, it hasn’t held him back. “Along with my research, I’m training undergraduates, taking courses, writing papers, and attending conferences, though all of this has been done virtually this year,” says Kim.
Doctoral students receive a funding package that covers tuition and provides a living stipend. At SEAS, students are typically funded by the university their first year and through their advisors’ grants in subsequent years. But grant funding can be uncertain, often changing year to year. Endowed fellowships, on the other hand, funded by donors to Yale, provide reliable funding and more flexibility, allowing students like Kim and researchers like Panda to be more creative and ambitious in their work and research.
Kim is just getting started, and he has big goals for the years ahead. “I’m so excited to see what the lab achieves together in the coming years.”