Teaching

CS760 — Machine Learning

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Graduate-level class covering the theoretical foundations of core machine learning algorithms — from logistic regression to SVMs and neural networks. Students should have a background in linear algebra, probability, and coding.

STAT 479 — AI for Sciences and Humanities

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Open to graduate and senior undergraduate students in all non-mathematical majors. A high-level overview of the inner workings of AI without the need for a mathematical background. Hands-on experience without the need for programming experience. Exposure to broader considerations such as ethics, interpretability, and societal impact.

BMI 567 — Medical Image Processing

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Open to graduate and senior undergraduate students. Hands-on introduction to medical image analysis techniques — formating, segmentation, registration, quantifcation, and classifcation. Students should have prior exposure to basic statistics and coding.