Email: zongweiz@asu.edu
Tel: 1-(480)738-2575
Birthday: Dec 3rd, 1993
URL: www.zongweiz.com
Office: 13212 E Shea Blvd, Scottsdale AZ, 85259
Research overview: Zongwei Zhou received a B.Sc. degree with honors in Computer Science from Dalian University of Technology in 2016. He is currently a Ph.D. candidate in the Department of Biomedical Informatics, Arizona State University reporting to Dr. Jianming Liang. He has also spent time at Mayo Clinic, University of California, Berkeley, and Université de Montréal. Drawing upon biomedical informatics, computer vision, and deep learning, his research focuses on developing novel methodologies to minimize the annotation efforts for computer-aided diagnosis, therapy, and surgery. Zhou has published 8 peer-reviewed publications in some of the most prestigious journals and conferences in his field, such as IEEE Transactions on Medical Imaging, Journal of Digital Imaging, CVPR, ICCV, and MICCAI. Moreover, he holds 1 US patent and additional 7 patents pending. He is the recipient of the MICCAI Young Scientist Award in 2019.
Education
Ph.D. Aug.2017-now
Arizona State University
Department: Biomedical Informatics
GPA: 3.96/4.0
Advisors: Prof. Jianming Liang, Prof. Edward H. Shortliffe, and Prof. Murthy Devarakonda
B.Sc. Sep.2012-Jul.2016
Dalian University of Technology
Department: Computer Science
GPA: 86.0/100.0 (general) | 86.6/100.0 (major)
Thesis: Medical image classification based on deep learning
Advisor: Prof. Hongkai Wang
> View Dissertation > View Slides
Experience
Research Internship Jan.2018-July. 2018
Centre Hospitalier de l’Université de Montréal
Department: Laboratoire clinique de traitement de l’image (LCTI)
Projects: Predictive model of colorectal cancer liver metastases response to chemotherapy
Joint collaboration: Imagia and MILA
Research Technologist Sep.2016-Present
Arizona State University
Department: Biomedical Informatics
Projects: Colonoscopy Frame Classification, Polyp Detection, Pulmonary Embolism Detection, Carotid Intima-Media Thickness Measurement
Joint collaboration: Mayo Clinic, Arizona
Internship June.2017-Jul.2017
Mayo Clinic, Rochester MN
Department: Radiology Informatics Lab
Projects: Thyroid Ultrasound Imaging, Tumor Radiogenomics
Journal Publications
Medical Image Analysis
AFT*: Active Fine Tuning of Convolutional Neural Networks for Reducing Annotation Efforts
Authors: Zongwei Zhou, Jae Shin, Suryakanth Gurudu, Michael B. Gotway, Jianming Liang
Under Review
Transactions on Medical Imaging
UNet++: Redesigning Skip Connections to Exploit Multi-Resolution Features in Image Segmentation
Authors: Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang
> View Publication > View Code
Journal of Digital Imaging
Integrating Active Learning and Transfer Learning for Carotid Intima-Media Thickness Video Interpretation
Authors: Zongwei Zhou, Jae Shin, Ruibin Feng, R. Todd Hurst, Christopher B. Kendall, Jianming Liang
> View Publication
Journal of Zhejiang University (Engineering Science)
Evaluation of machine learning classifiers for diagnosing mediastinal lymph node metastasis of lung cancer from PET/CT images
Authors: Hongkai Wang, Zhonghua Chen, Zongwei Zhou, Yingci Li, Peiou Lu, Wenzhi Wang, Wanyu Liu, Lijuan Yu
> View Publication
EJNMMI Research
Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18F-FDG PET/CT images
Authors: Hongkai Wang, Zongwei Zhou, Yingci Li, Zhonghua Chen, Peiou Lu, Wenzhi Wang, Wanyu Liu, Lijuan Yu
> View Publication
Conference Publications
ICCV 2019
Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization
Authors: Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Ruibin Feng, Nima Tajbakhsh, Michael Gotway, Yoshua Bengio, Jianming Liang
> View Publication > View Code > View Poster
MICCAI 2019
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
Authors: Zongwei Zhou, Vatsal Sodha, Md Mahfuzur Rahman Siddiquee, Ruibin Feng, Nima Tajbakhsh, Michael Gotway, Jianming Liang
Young Scientist Award
> View Publication > View Code > View Slides > View Poster > View Talk
DLMIA 2018
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
Authors: Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang
> View Publication > View Code > View Slides > View Poster > View Talk
CVPR 2017
Fine-tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally
Authors: Zongwei Zhou, Jae Shin, Lei Zhang, Suryakanth Gurudu, Michael Gotway, Jianming Liang
> View Publication > View Code > View Slides > View Poster
arXiv Preprints & Abstracts
arXiv Preprints
Frequency of Rational Fractions on [0, 1]
Authors: Zongwei Zhou, Dawei Lu
> View Publication
SIIM C-MIMI 2017
A Preliminary Study of Using Machine Learning to Reduce Biopsies of Thyroid Nodules Based on Ultrasound Images
Authors: Zongwei Zhou, Zeynettin Akkus, Mellissa S. Warner, Marius N. Stan, Jianming Liang, Bradley J. Erickson
> View Publication
Integrating Active Learning and Transfer Learning for Carotid Intima-Media Thickness Video Interpretation
Authors: Zongwei Zhou, Jae Shin, R. Todd Hurst, Christopher B. Kendall, Jianming Liang
> View Publication
Fully Automated IDH Mutation Prediction in MRI Utilizing Deep Learning
Authors: Panagiotis D. Korfiatis, Zongwei Zhou, Jianming Liang, Bradley J. Erickson
> View Publication
WCOG 2017
Gastroenterology Fellow-Level Performance on Colonoscopy
Frame Classification with Deep Neural Networks
Authors: Lei Zhang, Zongwei Zhou, Hassan Siddiki, Naveen Sai Madiraju, Francisco C Ramirez, Suryakanth R. Gurudu, Jianming Liang
> View Publication
US Patents
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
Inventors: Zongwei Zhou, Vatsal Sodha, Md Mahfuzur Rahman Siddiquee, Ruibin Feng, Nima Tajbakhsh, Michael Gotway, Jianming Liang
Tech Id: M19-252LC
Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization
Inventors: Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Ruibin Feng, Nima Tajbakhsh, Michael Gotway, Yoshua Bengio, Jianming Liang
Tech Id: M19-117L
UNet++: Redesigning Skip Connections to Exploit Multi-Resolution Features in Image Segmentation
Inventors: Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang
Tech Id: M19-189LC
Nested Ensemble of Convolutional Neural Nets for Medical Image Segmentation
Inventors: Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang
Tech Id: M18-196L
AFT*: Active Fine Tuning of Convolutional Neural Networks for Reducing Annotation Efforts
Inventors: Zongwei Zhou, Jae Shin, Suryakanth Gurudu, Michael B. Gotway, Jianming Liang
Tech Id: M19-194L
Integrating active learning and transfer learning for cutting annotation cost
Inventors: Zongwei Zhou, Jae Shin, Suryakanth Gurudu, Michael B. Gotway, Jianming Liang
Tech Id: M17-151L
Fine-tuning convolutional neural networks for biomedical image analysis: Actively and incrementally
Inventors: Zongwei Zhou, Jae Shin, Suryakanth Gurudu, Michael B. Gotway, Jianming Liang
US Provisional 62/491,069, 4/27/2017. Tech Id: M17-129L
Invited Talks and Blogs
Invited Talks
三维迁移学习
Venue: AI 研习社 @ Oct 24, 2019
> View Blog > View Slides > View Talk
Models Genesis
Venue: MICS Webinar @ Sep 24, 2019
> View Slides > View Talk
从人工到智能
Host: 我武生物科技 @ Dec 26, 2018
> View Blog > View Slides
研习U-Net
Venue: AI 研习社 @ Sep 18, 2018
> View Blog > View Slides > View Talk
How to Cut Annotation Cost in Biomedical Imaging
Venue: Centre Hospitalier de l’Université de Montréal @ May 22, 2018
> View Slides
Hot Posts
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> View Blog
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Travel
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