Zongwei Zhou is an assistant research professor in the Department of Computer Science and a member of both the Johns Hopkins Malone Center for Engineering in Healthcare and Data Science and AI Institute. His research focuses on medical computer vision, language, and graphics for early cancer detection and diagnosis.
Zhou is best known for developing UNet++, a widely adopted segmentation architecture ranked among the most popular articles in IEEE Transactions on Medical Imaging. He currently serves as a principal investigator on a $2.8 million R01 grant from the National Institute of Biomedical Imaging and Bioengineering. Zhou has received a 2022 Doctoral Dissertation Award from the American Medical Informatics Association, a 2020 Elsevier Medical Image Analysis Best Paper Award, and a 2019 Young Scientist Award from the Medical Image Computing and Computer Assisted Intervention Society. He has additionally been named in Stanford University’s list of “World’s Top 2%” scientists every year since 2022.
Zhou received his PhD in biomedical informatics from Arizona State University in 2021, where he was also honored with the university’s President’s Award for Innovation.
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NeurIPS is an interdisciplinary annual event that highlights advancements in machine learning, artificial intelligence, and computational neuroscience through talks, demonstrations, symposia, and oral and poster presentations.
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Developed by a Johns Hopkins-led research team, the Pancreatic Tumor Segmentation Dataset may be the key for training AI models to detect pancreatic cancer early enough to make a difference in patients' survival.