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 is currently a Ph.D. candidate in the Department of Biomedical Informatics at Arizona State University (ASU) supervised by Dr. Jianming Liang, and he will join CCVL as a post-doc at Johns Hopkins University supervised by Dr. Alan Yuille. He has also spent time at Mayo Clinic, University of California, Berkeley, and Université de Montréal. Zongwei holds a perfect GPA (4.0/4.0) and receives the University Graduate Fellowship from ASU. Drawing upon the realms of biomedical informatics, computer vision, and deep learning, his research focuses on developing novel methodologies to minimize the annotation efforts for computer-aided diagnosis and medical imaging. In addition to 11 U.S. patents pending, Zongwei has published 4 peer-reviewed clinical abstracts and over 10 peer-reviewed journal/conference articles, two of which have received the MICCAI Young Scientist Award and Elsevier-MedIA Best Paper Award. Two of his journal publications have been ranked among the most popular articles in IEEE TMI and the highest-cited article in EJNMMI Research, respectively. Furthermore, Zongwei has been awarded as the co-PI of the Bridges AI program from XSEDE. Zongwei also plays an active role in the leading societies of the computer vision and medical imaging field. He serves as a reviewer of IEEE TPAMI, MedIA, IEEE TMI, etc. and he was on the program committee for MICCAI in 2020, 2021; AAAI in 2020, 2021; ICCV in 2021.
Education
Ph.D. Aug.2017-now
Arizona State University
Department: Biomedical Informatics
GPA: 4.0/4.0
Thesis: Towards Annotation-Efficient Deep Learning in Computer-Aided Diagnosis
Advisors: Prof. Jianming Liang
> View Talk > View Slides > View Poster
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 Assistant Sep.2016-Present
Arizona State University
Department: Biomedical Informatics
Projects: Colonoscopy Frame Classification, Polyp Detection, Pulmonary Embolism Detection, and 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
Awards and Honors
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MedIA Best Paper Award
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University Graduate Fellowship, Arizona State University
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MICCAI Young Scientist Award
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MICCAI Best Presentation Award Finalist
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MICCAI Graduate Student Travel Award
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First place for Extraordinary Research and Scholarship in Imaging Informatics, Mayo Clinic
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Outstanding Graduate, Dalian University of Technology
Journal Publications
Medical Image Analysis
Models Genesis
Authors: Zongwei Zhou, Vatsal Sodha, Jiaxuan Pang, Michael B. Gotway, Jianming Liang
MedIA Best Paper Award
> View Publication > View Code > View Slides
Active, Continual Fine Tuning of Convolutional Neural Networks for Reducing Annotation Efforts
Authors: Zongwei Zhou, Jae Shin, Suryakanth Gurudu, Michael B. Gotway, Jianming Liang
> View Publication > View Code
Transactions on Medical Imaging
Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-supervised Learning
Authors: Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou, Michael Gotway, Jianming Liang
> View Publication > View Code
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
DART 2020
Parts2Whole: Self-supervised Contrastive Learning via Reconstruction
Authors: Ruibin Feng, Zongwei Zhou, Michael Gotway, Jianming Liang
> View Publication > View Code > View Poster
MICCAI 2020
Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration
Authors: Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou, Michael Gotway, Jianming Liang
> View Publication > View Code > View Slides > View Poster > View Talk
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
Methods, systems, and media for discriminating and generating translated images
Inventors: Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Ruibin Feng, Nima Tajbakhsh, Jianming Liang
US Provisional: 16/875,680, 11/19/2020
Systems, methods, and apparatuses for implementing a multi-resolution neural network for use with imaging intensive applications including medical imaging
Inventors: Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang
US Provisional: 16/556,130, 3/5/2020
Methods, systems, and media for selecting candidates for annotation for use in training classifiers
Inventors: Zongwei Zhou, Jae Shin, Jianming Liang
US Provisional: 16/397,990, 10/31/2019
Systems, methods, and/or media, for selecting candidates for annotation for use in training a classifier
Inventors: Zongwei Zhou, Jae Shin, Jianming Liang
US Provisional: 15/965,691, 11/1/2018
Invited Talks and Blogs
Invited Talks
The Will of Computer Vision
Venue: VALSE Student Webinar @ Jan 28, 2021
View Blog > View Slides > View Talk
Computer-aided Diagnosis and Therapy in Medical Imaging
Venue: BMI Seminar @ Sep 4, 2020
> View Slides
Cost-Effective Computer-Aided Diagnosis of Lung Cancer in Chest Computed Tomography
Venue: Phoenix Symposium on Data Analytics in Healthcare @ Aug 13, 2020
> View Slides > View Talk
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
Venue: AI Journal club @ Feb 29, 2020
> View Slides
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
Venue: Mila – Quebec Artificial Intelligence Institute @ Nov 11, 2019
> View Slides
3D Transfer Learning in Medical Image Analysis
Venue: AI Research Club @ Oct 24, 2019
> View Blog > View Slides > View Talk
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
Venue: MICS Webinar @ Sep 24, 2019
> View Slides > View Talk
从人工到智能
Venue: 我武生物科技 @ Dec 26, 2018
> View Blog > View Slides
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
Venue: AI Research Club @ 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
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