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AI/Deep Learning Engineer, Researcher and Enthusiast
Deep Learning for Real Life
Senior Algorithm Engineer, Alibaba Group (U.S.) - DAMO Academy
Ph.D. in Computer Science, University at Buffalo, SUNY
Email: zhanghex (at) buffalo.edu
Research interests in label efficient learning, continual learning, multi-modality learning and transfer learning/adaptation, with applications in real-world computer vision and medical image analysis.
Short Bio
Short Bio
I received my Ph.D. in Computer Science at University at Buffalo (UB), SUNY, advised by Prof. Mingchen Gao. Before that, I have completed my M.S. and B.E. degrees in Biomedical Engineering at Northwestern University in 2018 and Chien-shiung Wu College (Honors Program), Southeast University, Nanjing, China in 2016, respectively.
My research interest mainly spans over deep learning and its applications in computer vision and medical imaging. Specific deep learning methods cover self-/weakly/semi-supervised learning, continual learning, multi-modality learning and transfer learning. Applications include 3D segmentation, interactive segmentation, continual segmentation and vision-language representation.
News
News
Our paper Low-Rank Continual PVT for Whole-body Organ Segmentation is accepted to MICCAI 2024!
Our paper Continual Domain Adversarial Adaptation via Double-Head Discriminators is accepted to AISTATS 2024!
Our paper Continual Segmentation of 143 Whole-body Organs in CT Scans is accepted to ICCV 2023!
Our paper Memory-Free Class Incremental Learning (iVoro) is accepted to ICLR 2023!
Our paper Federated Adversarial Domain Adaptation (FedMM) is accepted to AAMAS 2023!
Professional Experiences
Professional Experiences
Senior Algorithm Engineer, Alibaba Group (U.S.) - DAMO Academy - Medical AI Lab, Washington, DC
Jan 2024 - Present. Work with Dr. Dazhou Guo, Dr. Dakai Jin and Dr. Le Lu.
Main focus: Medical AI, Computer Vision, Radiology
R&D Intern, Johnson & Johnson MedTech - LCI/WWDA, Raritan, NJ
Project: Intra-Tumor Segmentation using Imperfect Partial Annotations
Jan - Dec, 2023. Work with Dr. Aakanksha Rana and Dr. Tian Hao.
Research Intern, Alibaba Group (U.S.) - DAMO Academy - Medical AI Lab, New York, NY
Project: Continual Multi-Organ Segmentation over Multi-Site CT Scans
May - Nov, 2022. Work with Dr. Dazhou Guo, Dr. Dakai Jin and Dr. Le Lu.
Research Intern, PAII Inc. R&D Lab, Bethesda, MD
Project: Semi-Supervised Interactive Segmentation of Pathological Organs
May - August, 2019. Work with Dr. Ashwin Raju, Dr. Adam P Harrison and Dr. Le Lu.
ICCV Continual Segment: Towards a Single, Unified and Accessible Continual Segmentation Model of 143 Whole-body Organs in CT Scans (iccv, arxiv)
Zhanghexuan Ji*, Dazhou Guo*, Puyang Wang, Ke Yan, Jia Ge, Xianghua Ye, Minfeng Xu, Jingren Zhou, Le Lu, Mingchen Gao, Dakai Jin
International Conference on Computer Vision, 2023.
MICCAI Low-Rank Continual Pyramid Vision Transformer: Incrementally Segment Whole-Body Organs in CT with Light-Weighted Adaptation (miccai, arxiv)
Vince Zhu, Zhanghexuan Ji, Dazhou Guo, Puyang Wang, Yingda Xia, Le Lu, Xianghua Ye, Wei Zhu, Dakai Jin
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024.
ICLR Progressive Voronoi Diagram Subdivision Enables Accurate Data-free Class-Incremental Learning (openreview, arxiv)
Chunwei Ma, Zhanghexuan Ji, Ziyun Huang, Yan Shen, Mingchen Gao, Jinhui Xu
International Conference on Learning Representations, 2023.
AISTATS Continual Domain Adversarial Adaptation via Double-Head Discriminators (arxiv)
Yan Shen, Zhanghexuan Ji, Chunwei Ma, Mingchen Gao
International Conference on Artificial Intelligence and Statistics, 2024.
MLMI Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment (arxiv, code)
Zhanghexuan Ji*, Mohammad Abuzar Shaikh*, Dana Moukheiber, Sargur N Srihari, Yifan Peng, Mingchen Gao
International Workshop on Machine Learning in Medical Imaging, 2021.
MICCAI User-Guided Domain Adaptation for Rapid Annotation from User Interactions: A Study on Pathological Liver Segmentation (arxiv)
Ashwin Raju, Zhanghexuan Ji, Chi Tung Cheng, Jinzheng Cai, Junzhou Huang, Jing Xiao, Le Lu, ChienHung Liao, Adam P Harrison
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2020.
MICCAI Scribble-based Hierarchical Weakly Supervised Learning for Brain Tumor Segmentation (arxiv)
Zhanghexuan Ji, Yan Shen, Chunwei Ma, Mingchen Gao
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019.
MICCAI Neural Style Transfer Improves 3D Cardiovascular MR Image Segmentation on Inconsistent Data (arxiv)
Chunwei Ma, Zhanghexuan Ji, Mingchen Gao
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019.
More About Z. Ji
More About Z. Ji
Professional Services
Professional Services
Journal Reviewer
npj Digital Medicine (Reviewer of the Month)
Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Conference Reviewer
MICCAI 2020/2021(Outstanding Reviewer Award – Honorable Mention)/2022/2023/2024
CVPR 2021/2022/2023
ECCV 2024
NeurIPS 2021/2022
AAAI 2024/2025
Teaching Assistant
Introduction to Discrete Structures
Introduction to Machine Learning
Introduction to Computer Vision and Image Processing
Education
Education
Ph.D in Computer Science
University at Buffalo, SUNY
2018 - 2023
M.S. in Biomedical Engineering
Northwestern University
2016 - 2018
B.E. in Biomedical Engineering
Southeast University (Chien-shiung Wu College), Nanjing, China
2012 - 2016
Skills
Skills
Technical
Python Matlab Java
Pytorch OpenCV Latex/Markdown
Git/Bash Linux HTML/JavaScript
Language
English (Professional)
Chinese (Native)
Japanese (Elementary)
Interests
Interests
Music (pop, electro, vocaloid, etc.)
Biking & Hiking
Cooking (Chinese food)
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