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职业迁徙
个人简介
I am a machine learning researcher at EY LLP and University of Maryland focused primarily on deep learning. Update: I will be joining Google AI as a research scientist in April 2020. My research approaches machine learning from an adversarial perspective. In particular, I’ve worked on poison attacks, adversarial examples, learning from noisy labels, and generalization phenomena.
Previously I worked for 8 years in optical physics, where I built laser-driven particle accelerators, ultrafast electron guns, ground- and space-based lidars, terahertz lasers, and frequency combs. I’ve worked at MIT, NASA, German Electron Synchrotron, and MIT Lincoln Lab.
My pivot to machine learning grew out of a fascination with the remarkable results of deep learning and curiosity about the inner workings of intelligence. I’ve since been on a mission to build robust, interpretable, and generalizable machines that can make sense of our complex, noisy, and (sometimes) adversarial world
Previously I worked for 8 years in optical physics, where I built laser-driven particle accelerators, ultrafast electron guns, ground- and space-based lidars, terahertz lasers, and frequency combs. I’ve worked at MIT, NASA, German Electron Synchrotron, and MIT Lincoln Lab.
My pivot to machine learning grew out of a fascination with the remarkable results of deep learning and curiosity about the inner workings of intelligence. I’ve since been on a mission to build robust, interpretable, and generalizable machines that can make sense of our complex, noisy, and (sometimes) adversarial world
研究兴趣
论文共 63 篇作者统计合作学者相似作者
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CoRR (2023): 1-5
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2022 IEEE Spoken Language Technology Workshop (SLT)pp.245-251, (2023)
2022 IEEE Spoken Language Technology Workshop (SLT)pp.197-204, (2023)
Conference of the International Speech Communication Association (INTERSPEECH) (2022): 4995-4999
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