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Hi there! I am a second-year PhD student in the Computer Science & Engineering (CSE) department at the University of Michigan, advised by Prof. Stella X. Yu. Before my Ph.D., I earned an M.S. in CSE from the University of Michigan, focusing on medical image segmentation with Dr. Sandaresh Ram and Dr. Craig Galban at Michigan Medicine and during an internship at Genentech with Dr. Acner Camino. I earned my B.S. in CSE from the Ohio State University, Summa Cum Laude. I am broadly interested in computer vision and deep learning, particularly in addressing the challenges of applying these techniques to real-world problems. |
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Research |
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Open Ad-Hoc Categorization with Contextualized Feature Learning
Zilin Wang*, Sangwoo Mo*, Stella X. Yu, Sima Behpour, Liu Ren CVPR, 2025 paper / slides / poster / code (coming soon) Ad-hoc categories are created dynamically to achieve specific tasks, such as things to sell at a garage sale. Novel concepts can be discovered semantically by expanding contextual cues or visually by clustering similar patterns. |
Applied Research |
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Deep Learning Segmentation of Foveal Avascular Zone in Optical Coherence Tomography Angiography of Nonproliferative Diabetic Retinopathy
Acner Camino Benech*, Zilin Wang*, Aditi Basu Bal, Fethallah Benmansour, Richard Carano, Daniela Ferrara ARVO, 2023; EURETINA, 2023 paper / slides / poster Foveal Avascular Zone (FAZ) segmentation can be improved by incorporating auxiliary tasks like FAZ boundary segmentation and using weak supervision from vessel segmentation. This helps the model learn finer details and contextual cues, leading to SOTA results. |
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Pulmonary Artery-Vein Segmentation in 3D Computed Tomography Images
Zilin Wang, Sandaresh Ram, Craig Galban We present iSparseUnet, a segmentation model for 3D Computed Tomography (CT) images that leverages data sparsity, octree structure, and invertible layers for optimal efficiency. Unlike patch-based methods, it processes the entire volume at once, producing hierarchical outputs that preserve global context and maintain the connectivity of lung structures, essential for precise medical segmentation. |
TeachingUM EECS442: Computer Vision
UM EECS542: Advanced Topics in Computer Vision
UM EECS598: Action & Perception
UM SI670: Applied Machine Learning
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Academic Service & Outreach
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Design and template code from Jon Barron |