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Personal background
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Academic Journey
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Math is a human endeavor
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Math & Data
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Our Perspective on Data Science
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DSI Research Initiatives
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DSI - Education
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One example: DS Preceptorship. UChicago and CCC
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Topological Data Analysis
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What is Epistasis?
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Types of Epistasis?
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Algebra? Fourier Analysis - Brief refresher
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Fourier analysis as a feature extractor
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Fourier analysis - transform
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Fourier transform summary
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Processing data
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Non-abelian harmonic analysis
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Orthogonal Decomposition
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Our Results: detecting higher order interaction
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Summary and directions
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Challenge #1 - Good, annotated, multi-class data set
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Expert annotation agreement is challenging
Description:
Explore a comprehensive lecture from the LatMath 2022 conference, where David Uminsky shares his academic journey and insights on mathematics and data science. Delve into topics such as the human aspect of mathematics, data science perspectives, and research initiatives at the Data Science Institute. Discover the innovative DS Preceptorship program, a collaboration between UChicago and CCC. Gain knowledge about topological data analysis and epistasis, followed by a refresher on Fourier analysis and its applications in feature extraction. Learn about non-abelian harmonic analysis and orthogonal decomposition, and understand their role in detecting higher-order interactions. Conclude with a summary of current challenges in the field, including the need for good, annotated multi-class datasets and the complexities of expert annotation agreement.

David Uminsky - LatMath 2022 - IPAM's Latinx in the Mathematical Sciences Conference

Institute for Pure & Applied Mathematics (IPAM)
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