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Welcome! I am a PhD candidate at the statistics department in University of Illinois, Urbana Champaign. I am advised by Dr. Joshua Agterberg. I am interested in the intersection of optimization, high dimensional statistics and machine learning. In particular, optimization on manifolds, low rank models and optimal transport. I am also fascinated by application in genomics and spatial statistics. I spent my undergraduate years in Kunshan, China and Durham, North Carolina, where I recieved my data science degree and graduated with distinction at Duke Kunshan University and Duke University. In my undergraduate years, I worked with Dr. Dongmian Zou and Dr. Ivan Mura on geometric machine learning and stochastic modeling. Email / Google Scholar / Github / |
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The following is a list of past research projects: |
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Zhexu Jin, Mario Andrés Velásquez Angel, Ivan Mura, Juan Felipe Franco Front. Environ. Sci., 2022 [doi] [bibtex] [code] We used spatial temporal kriging to identify a highly polluted cluster located in the south-west cluster in the city of Bogotá. Within this cluster, we observe a disproportionate representation of people from several vulnerable groups. |
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Zhexu Jin, Gaoyang Li, Huansheng Cao, and Dongmian Zou Neurips 2022 Workshop: Medical Imaging Meets Nuerips [doi] [abstract] [poster] Proposed to perserve geometry of the instance segmentation for medical imaging using losses inspired by persistent homology. We sped up the loss computation via a 1-dimensional simplification and implemented the new loss based on lower star filtration. Benchmarked the proposed method against other commonly used instance segmentation methods |
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Lab/Discussion Teaching Assistant:
Grading Teaching Assistant:
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Blog Posts |
More to come! |
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This guy makes an awesome website. |