Welcome to Ziyuan (Jacob) ZHAO’s homepage (赵子源)

I am currently a senior research engineer at Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore 🇸🇬. I am also a 2nd year Ph.D. student at the School of Computer Science and Engineering (SCSE), Nanyang Technological Unversity (NTU), supervised by Prof. Cuntai Guan. Previously, I received the M.Tech degree, National University of Singapore in 2019 and the B.Eng degree, Yunnan University in 2017.

My research interest lies in the interdisciplinary field of biomedical image analysis, artificial intelligence and healthcare. I am dedicated to designing machine learning algorithms for biomedical image analysis and automatic medical diagnosis, promoting wider AI-powered healthcare in the real world. Specifically, I focus on (1) developing annotation-efficient learning algorithms to minimize the annotation cost; (2) developing cross-domain learning algorithms to integrate different biomedical data; and (3) building reliable, generalizable, and practical AI healthcare systems from imperfect biomedical data. I have published more than 30 papers at the top international AI conferences and journals.

Openings: We have multiple openings for Interns/Visiting Ph.D. sudents (all-year-round) to work on research projects related to medical image analysis and 3D vision. Students with strong self-motivation and publication record are preferred. Welcome to drop me an email with your CV. Remote collaboration is also welcome!

A*STAR Research Internship Award (ARIA) : “184 - Label-Efficient Learning for Medical Image Analysis” and “245 - Transfer Learning for Medical Image Analysis” For local undergrates

Singapore International Pre-Graduate Award (SIPGA) For overseas undergraduate students in their third or fourth year, or master students.

Chinese Scholarship Council (CSC) Scholarship For Chinese master or PhD students for visiting exchange.

🔥 News

• 2023.08：Our paper on distribution learning has been reported on A*STAR Research Highlights link.
• 2023.07: Our paper “Modal-aware Visual Prompting for Incomplete Multi-modal Brain Tumor Segmentation “ was accepted by ACM MM 2023, thanks to all co-authors.
• 2023.05: Happy to receive the A*STAR Sponsorship Award (Formerly known as A*STAR Scientific Staff Development Award (SSDA)).
• 2023.04: Our paper “SemiGNN-PPI: Self-Ensembling Multi-Graph Neural Network for Efficient and Generalizable Protein–Protein Interaction Prediction” was accepted by IJCAI 2023 (acceptance rate: 15%), thanks to all co-authors. paper is avaliable.
• 2023.04: Our team achieved 3rd place in the Valence-Arousal Estimation Challenge of the 5th Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW), IEEE Computer Vision and Pattern Recognition Conference (CVPR), 2023. The results are out here. Technical report is avaliable.
• 2023.03: Our team achieved 5th place in Cross-Modality Domain Adaptation for Medical Image Segmentation(crossMoDA) 2022 challenge. The results are out here. Technical report is avaliable.
• 2023.01:👲 Happy 🧧 Chunjie 🧨 Chinese New Year 🐰 Rabbit Year 🐇 Spring Festival 🏮 Lunar New Year! 🥟
• 2022.12: Happy to receive the A*STAR AI3 HTCO Seed Fund [PI, SG$300,000]. More details about AI3 HTCO can be found here.
• 2022.11: Our paper “Efficient Perturbation Inference and Expandable Network for Continual Learning” was accepted by Neural networks, thanks to all co-authors. paper is avaliable.
• 2022.10: Our paper “LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation” was accepted by IEEE Transactions on Medical Imaging, thanks to all co-authors. paper is avaliable.
• 2022.09: Our paper “DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection” was accepted by BMVC 2022 for spotlight presentation (30/770 submissions), thanks to all co-authors. paper is avaliable.
• 2022.06: Three papers (MMGL, ACT-Net, and OASSMLL) were accepted by ICIP 2022, thanks to all co-authors.
• 2022.05: Our paper “Meta-hallucinator: Towards few-shot cross-modality cardiac image segmentation” was provisionally accepted by MICCAI 2022 (top 13% in total 1825 submissions), thanks to all co-authors. paper is avaliable.
• 2022.05: Our paper “CoIn: Correlation Induced Clustering for Cognition of High Dimensional Bioinformatics Data” was accepted by IEEE Journal of Biomedical And Health Informatics, thanks to all co-authors. paper is avaliable.

📝 Publications

More details can be found in my Google Scholar

• SemiGNN-PPI: Self-Ensembling Multi-Graph Neural Network for Efficient and Generalizable Protein–Protein Interaction Prediction
  Ziyuan Zhao, Peisheng Qian, Xulei Yang, Zeng Zeng, Cuntai Guan, Wai Leong Tam, Xiaoli Li
  IInternational Joint Conference on Artificial Intelligence (IJCAI), 2023. (acceptance rate: 15%)

• LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation
  Ziyuan Zhao, Fangcheng Zhou, Kaixin Xu, Zeng Zeng, Cuntai Guan, S. Kevin Zhou
  IEEE Transactions on Medical Image (TMI), 2022.

• Meta-hallucinator: Towards few-shot cross-modality cardiac image segmentation
  Ziyuan Zhao, Fangcheng Zhou, Zeng Zeng, Cuntai Guan, S. Kevin Zhou
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022. (Top 13% paper, Early Accept)

• DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection
  Ziyuan Zhao, Mingxi Xu, Peisheng Qian, Ramanpreet Pahwa, Richard Chang
  British Machine Vision Conference (BMVC), 2022. (30/770 submissions, Spotlight)

• Self-supervised Assisted Active Learning for Skin Lesion Segmentation
  Ziyuan Zhao, Wenjing Lu, Zeng Zeng, Kaixin Xu, Bharadwaj Veeravalli, Cuntai Guan
  Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2022. (Oral)

• MT-UDA: Towards Unsupervised Cross-modality Medical Image Segmentation with Limited Source Labels
  Ziyuan Zhao, Kaixin Xu, Shumeng Li, Zeng Zeng, Cuntai Guan
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.

• DSAL: Deeply Supervised Active Learning from Strong and Weak Labelers for Biomedical Image Segmentation
  Ziyuan Zhao, Zeng Zeng, Kaixin Xu, Cen Chen, Cuntai Guan
  IEEE Journal of Biomedical and Health Informatics (JBHI), 2021.

• Semi-supervised self-taught deep learning for finger bones segmentation
  Ziyuan Zhao, Xiaoman Zhang, Cen Chen, Wei Li, Songyou Peng, Jie Wang, Xulei Yang, Le Zhang, Zeng Zeng
  IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2019. (Oral)

💬 Talks

• Label-efficient Deep Learning for Computer Vision
  at Institute of Systems Science (ISS), NUS, January 2023. (invited by Dr. TIAN Jing)

• Unsupervised Domain Adaptation in Medical Image Segmentation
  at IEEEDay x EMBS Chapters Torch Relay Public Webinar, October 2022. [video (YouTube)]

• Deep Learning for Label-efficient Medical Image Segmentation
  at IEEE EMBS Summer Camp 2022, September 2022. [video (YouTube)]

🎖 Honors and Awards

• 2023.5: A*STAR Sponsorship Award (Formerly known as A*STAR Scientific Staff Development Award (SSDA)).
• 2023.5 Best Poster Award (2nd Prize), IEEE EMBS-NUS iHealthtech Forum DataScience and Engineering in Healthcare, Medicine and Biology, Singapore (Awardee: Ng Zhi Qing) - Supervised student’s achievement.
• 2023.4 3rd Place Award, Valence-Arousal Estimation Challenge of the 5th ABAW competition, IEEE CVPR 2023, Vancouver, Canada.
• 2022.9 5th Place Award (Task 1), Cross-Modality Domain Adaptation for Medical Image Segmentation (crossMoDA) challenge, MICCAI 2022, Singapore.
• 2022.6 Best Trailblazer Award for AI paper innovation, Internation Student Conference On Artificial intelligence 2022 (STCAI 2022), Singapore.
• 2022.5 Second Prize Award for AI paper presentation, AI Research Student Conference 2022 (ARSC 2022), Singapore.
• 2018.9 First Prize F10 Challenge, F10 Fintech Hackathon

📖 Education

• 2021.08 - now, Ph.D. Student, Nanyang Technological University, Singapore.
• 2018.01 - 2019.07, M.Tech., National University of Singapore, Singapore.
• 2013.08 - 2017.07, B.Eng., Yunnan University, China.

💻 Experience

• 2022.07 - now, Senior Research Engineer II, I2R, A*STAR, Singapore.
• 2022.04 - 2023.06, Senior Research Engineer I, I2R, A*STAR, Singapore.
• 2019.08 - 2022.03, Research Engineer, I2R, A*STAR, Singapore.
• 2019.04 - 2019.07, Junior Research Assistant, ADSC, UIUC, Singapore.
• 2018.08 - 2019.03, Research Intern, I2R, A*STAR, Singapore.