Learning Cell-Aware Hierarchical Multi-Modal Representations for Robust Molecular Modeling
Zelin Zang, et al. (2026). "Learning Cell-Aware Hierarchical Multi-Modal Representations for Robust Molecular Modeling." AAAI 2026.
CV
Work Experience
- Postdoctoral Researcher (Jul 2024 - Present)
- Hong Kong Institute of Innovation, Chinese Academy of Sciences (HKII-CAS)
- Supervisors: Prof. Zhen Lei and Prof. Jiebo Luo
- Research Focus: AI Foundation Models, AI for Science (Life Science), and Medical AI.
- Visiting Scholar (Nov 2023 - May 2024)
- National University of Singapore (NUS)
- Advisor: Prof. Yang You
- Research Focus: Large scale optimization and foundation models.
Education
- Ph.D. in Electronic Science and Technology (Sept 2020 - Jun 2024)
- Zhejiang University (Jointly trained with Westlake University)
- Advisor: Prof. Stan Z. Li (IEEE Fellow)
- Thesis: Deep Manifold Learning and its Applications in Bioinformatics.
- M.S. in Computer Science (Sept 2017 - Jun 2020)
- Zhejiang University of Technology - Computer Science and Technology College
- Honor: Outstanding Graduate, National Scholarship.
- B.E. in Automation (Sept 2013 - Jun 2017)
- Zhejiang University - City College
- Honor: Outstanding Graduate, National Scholarship.
Research Interests
- AI for Life Science: Single-cell analysis, Spatial transcriptomics, Molecular modeling, Phylogenetic inference.
- Medical AI: LLM agents for medical reasoning, Multi-modal clinical diagnosis.
- Fundamental AI: Manifold learning, Geometric deep learning, Trustworthy AI.
Skills
- Programming: Python, C/C++, MATLAB, Shell.
- Frameworks: PyTorch, TensorFlow, Scanpy, HuggingFace.
- Tools: Git, Docker, LaTeX, Linux.
- Languages: English (Professional), Mandarin (Native).
Academic Service
- Journal Reviewer:
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
- IEEE Transactions on Visualization and Computer Graphics (TVCG)
- Briefings in Bioinformatics (BIB)
- Nature Communications
- Conference Reviewer:
- CVPR, ICCV, ECCV
- NeurIPS, ICML, ICLR, AAAI, IJCAI
Publications
MedLA: A Logic-Driven Multi-Agent Framework for Complex Medical Reasoning with Large Language Models
Zelin Zang, et al. (2026). "MedLA: A Logic-Driven Multi-Agent Framework for Complex Medical Reasoning with Large Language Models." AAAI Conference on Artificial Intelligence (AAAI).
CellScout: Visual Analytics for Mining Biomarkers in Cell State Discovery
Zelin Zang, et al. (2026). "CellScout: Visual Analytics for Mining Biomarkers in Cell State Discovery." IEEE Transactions on Visualization and Computer Graphics (TVCG).
Hierarchical Quantized Diffusion Based Tree Generation Method for Hierarchical Representation and Lineage Analysis
Zelin Zang, et al. (2026). "Hierarchical Quantized Diffusion Based Tree Generation Method for Hierarchical Representation and Lineage Analysis." Under Review at ICLR 2026.
Expanding the RNA Virus Universe by Deep Learning Discovery with Rider
Gaoyang Luo*, Zelin Zang*, et al. (2026). "Expanding the RNA Virus Universe by Deep Learning Discovery with Rider." Under Review at Nature Methods.
Single Cell Lineage Foundation Model
Zelin Zang, et al. (2026). "Single Cell Lineage Foundation Model." Under Review at Nature Machine Intelligence.
Multi-center multi-omics integration predicts individualized prognosis in medullary thyroid carcinoma
Yaoting Sun*, Zelin Zang*, et al. (2026). "Multi-center multi-omics integration predicts individualized prognosis in medullary thyroid carcinoma." Nature Communications.
MDTree: A Masked Dynamic Autoregressive Model for Phylogenetic Inference
Zelin Zang, et al. (2026). "MDTree: A Masked Dynamic Autoregressive Model for Phylogenetic Inference." Journal of Machine Learning Research.
DMT-ME: MOE-Enhanced Explanable Deep Manifold Transformation for Complex Data Embedding and Visualization
Zelin Zang, et al. (2026). "DMT-ME: MOE-Enhanced Explanable Deep Manifold Transformation for Complex Data Embedding and Visualization." IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
USD: Unsupervised Soft Contrastive Learning for Fault Detection in Multivariate Time Series
Zelin Zang, et al. (2025). "USD: Unsupervised Soft Contrastive Learning for Fault Detection in Multivariate Time Series." ICASSP 2025.
Deep Multimanifold Transformation-Based Multivariate Time Series Fault Detection
Zelin Zang, et al. (2025). "Deep Multimanifold Transformation-Based Multivariate Time Series Fault Detection." IEEE TNNLS.
MuST: Advancing Unified Spatial Transcriptomics Multitask Analysis with Multimodal Structure Transformation
Zelin Zang, et al. (2025). "MuST: Advancing Unified Spatial Transcriptomics Multitask Analysis with Multimodal Structure Transformation." Briefings in Bioinformatics.
A review of artificial intelligence based biological-tree construction: Priorities, methods, applications and trends
Zelin Zang, et al. (2025). "A review of artificial intelligence based biological-tree construction: Priorities, methods, applications and trends." Information Fusion.
PhyloGen: Language Model-Enhanced Phylogenetic Inference via Graph Structure Generation
Chenrui Duan*, Zelin Zang*, et al. (2024). "PhyloGen: Language Model-Enhanced Phylogenetic Inference via Graph Structure Generation." NeurIPS 2024.
DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation
Zelin Zang, Hao Luo, Kai Wang, Panpan Zhang, Fan Wang, Stan Li, Yang You. (2024). "DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation." International Conference on Machine Learning (ICML).
Neural network diffusion
Kai Wang, Dongwen Tang, Boya Zeng, Yida Yin, Zhaopan Xu, Yukun Zhou, Zelin Zang, Trevor Darrell, Zhuang Liu, Yang You. (2024). "Neural network diffusion." arXiv preprint arXiv:2402.13144.
The heterophilic graph learning handbook: Benchmarks, models, theoretical analysis, applications and challenges
Sitao Luan, Chenqing Hua, Qincheng Lu, Liheng Ma, Lirong Wu, Xinyu Wang, Minkai Xu, Xiao-Wen Chang, Zelin Zang, Doina Precup, et al. (2024). "The heterophilic graph learning handbook: Benchmarks, models, theoretical analysis, applications and challenges." arXiv preprint arXiv:2407.09618.
DMTEV: An Explainable Deep Network for Dimension Reduction
Zelin Zang, Shenghui Cheng, Hanchen Xia, Liangyu Li, Yaoting Sun, Yongjie Xu, Lei Shang, Baigui Sun, Stan Z. Li. (2024). "DMTEV: An Explainable Deep Network for Dimension Reduction." IEEE Transactions on Visualization and Computer Graphics (TVCG).
Boosting Novel Category Discovery Over Domains with Soft Contrastive Learning and All in One Classifier
Zelin Zang, Lei Shang, Senqiao Yang, Fei Wang, Baigui Sun, Xuansong Xie, Stan Z. Li. (2023). "Boosting Novel Category Discovery Over Domains with Soft Contrastive Learning and All in One Classifier." ICCV 2023.
UDRN: Unified Dimensional Reduction Neural Network for Feature Selection and Feature Projection
Zelin Zang, Yongjie Xu, Linyan Lu, Yulan Geng, Senqiao Yang, Stan Z. Li. (2023). "UDRN: Unified Dimensional Reduction Neural Network for Feature Selection and Feature Projection." Neural Networks.
Structure-preserving visualization for single-cell RNA-Seq profiles using deep manifold transformation with batch-correction
Yongjie Xu*, Zelin Zang*, et al. (2023). "Structure-preserving visualization for single-cell RNA-Seq profiles using deep manifold transformation with batch-correction." Communications Biology.
Protein structure and folding pathway prediction based on remote homologs recognition using PAthreader
Kailong Zhao, Yuhao Xia, Fujin Zhang, Zelin Zang, Stan Z. Li, Guijun Zhang. (2023). "Protein structure and folding pathway prediction based on remote homologs recognition using PAthreader." Communications biology.
Architecture-Agnostic Masked Image Modeling–From ViT back to CNN
Siyuan Li, Di Wu, Fang Wu, Zelin Zang, Stan Li. (2023). "Architecture-Agnostic Masked Image Modeling--From ViT back to CNN." International Conference on Machine Learning (ICML23).
Machine learning for predictive deployment of UAVs with multiple access
Feiyang Guo, Linyan Lu, Zelin Zang, Mohammad Shikh-Bahaei. (2023). "Machine learning for predictive deployment of UAVs with multiple access." IEEE Open Journal of the Communications Society.
DLME: Deep Local-flatness Manifold Embedding
Zelin Zang, Siyuan Li, Di Wu, Ge Wang, Kai Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li. (2022). "DLME: Deep Local-flatness Manifold Embedding." ECCV 2022.
Artificial intelligence defines protein-based classification of thyroid nodules
Yaoting Sun*, Sathiyamoorthy Selvarajan*, Zelin Zang*, Wei Liu, Yi Zhu, Hao Zhang, Wanyuan Chen, Hao Chen, Lu Li, Xue Cai, et al. (2022). "Artificial intelligence defines protein-based classification of thyroid nodules." Cell Discovery.
Deep manifold embedding of attributed graphs
Zelin Zang, Siyuan Li, Di Wu, Jianzhu Guo, Yongjie Xu, Stan Z. Li. (2022). "Deep manifold embedding of attributed graphs." Neurocomputing.
Generalized Clustering and Multi-Manifold Learning with Geometric Structure Preservation
Lirong Wu, Zicheng Liu, Jun Xia, Zelin Zang, Siyuan Li, Stan Z. Li. (2022). "Generalized Clustering and Multi-Manifold Learning with Geometric Structure Preservation." IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Eleven routine clinical features predict COVID-19 severity uncovered by machine learning of longitudinal measurements
Kai Zhou, Yaoting Sun, Lu Li, Zelin Zang, Jing Wang, Jun Li, Junbo Liang, Fangfei Zhang, Qiushi Zhang, Weigang Ge, et al. (2021). "Eleven routine clinical features predict COVID-19 severity uncovered by machine learning of longitudinal measurements." Computational and structural biotechnology journal.
Align yourself: Self-supervised pre-training for fine-grained recognition via saliency alignment
Di Wu, Siyuan Li, Zelin Zang, Kai Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li. (2021). "Align yourself: Self-supervised pre-training for fine-grained recognition via saliency alignment." arXiv preprint arXiv:2106.15788.
Phenotype classification using proteome data in a data-independent acquisition tensor format
Fangfei Zhang, Shaoyang Yu, Lirong Wu, Zelin Zang, Xiao Yi, Jiang Zhu, Cong Lu, Ping Sun, Yaoting Sun, Sathiyamoorthy Selvarajan, et al. (2020). "Phenotype classification using proteome data in a data-independent acquisition tensor format." Journal of the American Society for Mass Spectrometry.
Markov-lipschitz deep learning
Stan Z. Li, Zelin Zang, Lirong Wu. (2020). "Markov-lipschitz deep learning." arXiv preprint arXiv:2006.08256.
Two-dimensional discrete feature based spatial attention CapsNet For sEMG signal recognition
Guoqi Chen, Wanliang Wang, Zheng Wang, Honghai Liu, Zelin Zang, Weikun Li. (2020). "Two-dimensional discrete feature based spatial attention CapsNet For sEMG signal recognition." Applied Intelligence.
Hybrid Deep Neural Network Scheduler for Job-Shop Problem Based on Convolution Two-Dimensional Transformation
Zelin Zang, Wanliang Wang, Yuhang Song, Linyan Lu, Weikun Li, Yule Wang, Yanwei Zhao. (2019). "Hybrid Deep Neural Network Scheduler for Job-Shop Problem Based on Convolution Two-Dimensional Transformation." Computational intelligence and neuroscience.
Precise control and prediction of the greenhouse growth environment of Dendrobium candidum
Jin-Ting Ding, Hang-Yao Tu, Ze-Lin Zang, Min Huang, Sheng-Jun Zhou. (2018). "Precise control and prediction of the greenhouse growth environment of Dendrobium candidum." Computers and electronics in agriculture.
Talks
Multi-Modal Molecular Dynamics: Research Planning and Strategic Directions
Planning Meeting at CAIR Strategic Research Planning Session, Hong Kong
Virtual Cell Foundation Models: Technical Architecture and Implementation
Technical Proposal at BGI Virtual Cell Project Planning Meeting, Shenzhen, China
Mass Spectrometry-Based Proteomics for Cancer Subtyping and Prognosis Prediction
Research Seminar at BGI Proteomics Research Seminar, Shenzhen, China
Deep Learning for Spatial Transcriptomics: Coverage and Resolution Enhancement
Academic Seminar at Computational Biology Research Seminar, Beijing, China
Industrial AI Agent System: Mid-term Progress and Technical Achievements
Progress Report at Rootcloud AI Project Review Meeting, Shanghai, China
Medical Artificial Intelligence: Bridging Research and Clinical Practice
Seminar Presentation at Medical AI Research Seminar (Ant Group Collaboration), Hangzhou, China
AI Virtual Cell: Building Computational Models of Cellular Systems
Project Proposal at CAIR Research Proposal Presentation, Hong Kong
AI for Precision Medicine: From Data to Clinical Insights
Workshop Presentation at Guangzhou Health Data Intelligence Workshop, Guangzhou, China
Proteomics Meets Single-Cell: Integration and Analysis Progress
Progress Report at Proteomics and Single-Cell Biology Workshop, Shanghai, China
Multi-Modal Learning for Complex Biological Systems: Challenges and Opportunities
Keynote Speech at Multi-Modal Biological Data Integration Symposium (Opening Ceremony), Beijing, China
Deep Manifold Learning for High-Dimensional Data Analysis: Methods, Theory, and Applications
Ph.D. Dissertation Defense at Zhejiang University, College of Information Science and Electronic Engineering, Hangzhou, China
Foundation Models for Medical Diagnosis and Clinical Decision Support
Invited Lecture at West Coast AI in Healthcare Conference, San Francisco, CA, USA
Cell Annotation and Matching Methods for Single-Cell Analysis
Research Talk at Computational Biology Seminar, Beijing, China
Deep Learning for High-Dimensional Data Analysis and Visualization
Forum Presentation at High-Dimensional Data Analysis Research Forum, Shanghai, China
Recent Developments in Retrieval-Augmented Generation for Scientific Applications
Technical Seminar at AI Technology Forum, Hangzhou, China
Single-Cell Foundation Models and Cell Knowledge Base Construction
Research Preview at BGI Research Seminar, Shenzhen, China
Phylogenetic Tree Generation and Evolutionary Analysis Using Deep Learning
Research Seminar at CAIR (Centre for Artificial Intelligence Research), Hong Kong, Hong Kong
Technical Discussion on Large-Scale Model Training and Optimization
Technical Discussion at Team Technical Meeting, Hangzhou, China
Boosting Unsupervised Contrastive Learning Using Diffusion-Based Data Augmentation From Scratch
Poster Presentation at International Conference on Machine Learning (ICML 2024), Vienna, Austria
Research Presentation: AI for Biological Sciences and Medical Applications
Job Talk at Westlake University / Zhejiang University Joint Faculty Interview, Hangzhou, China
Deep Learning for Proteomics-Based Cancer Classification and Prognosis
Research Talk at BGI Genomics (Hangzhou Genomics Institute), Hangzhou, China
Geometric Deep Learning for Drug Discovery and Single-Cell Omics
Research Talk at Biomedical AI Symposium, Hangzhou, China
High-Performance Computing for AI: Scalable Deep Learning Systems
Lecture at National University of Singapore, HPC-AI Lab, Singapore
Diffusion-Based Data Augmentation for Unsupervised Contrastive Learning
Research Presentation at Lab Research Seminar, Hangzhou, China
FINE Review: AI for Science Research Progress and Applications
Presentation at FINE Research Assessment, Beijing, China
Deep Manifold Transformation for Explainable Visualization (DMTEV)
Talk at Fudan University, School of Computer Science, Shanghai, China
Teaching
Service and leadership
- Currently signed in to 43 different slack teams