Kate Fischl

Principal Machine Learning Engineer at Analog Devices

Kate Fischl is an accomplished professional in the field of machine learning and research engineering, currently serving as a Principal Machine Learning Engineer and Principal Research Scientist at Analog Devices. Kate has previously held positions as a Research Engineer at both Analog Devices and MIT Lincoln Laboratory. As a PhD Candidate in Electrical and Computer Engineering at Johns Hopkins University, Kate has further advanced expertise in research and engineering. Additional experience includes a role as an NSF Summer Intern at the University of Maryland and an Undergraduate Researcher at Princeton University.

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