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Ian Quah

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About

Ian Quah is a Ph.D. student at the University of Washington focusing on the intersection of Neuroscience and Machine Learning. His research investigates the robustness of large-scale neural circuits and aims to design advanced deep learning algorithms that are sample-efficient, power-efficient, and interpretable. Ian is also interested in deep reinforcement learning, privacy-preserving machine learning, and contributes to the OpenFHE project. Originally from Malaysia, he previously worked in various tech industry roles and returned to academia in 2023.

Platform
Web
Keywords
machine learningresearchdeep learningneuroscienceph.d.
Task
research focus
Features

• investigation of large-scale neural circuits

• development of interpretable deep learning algorithms

• contributions to privacy-preserving machine learning

• advising junior ml engineers

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