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Chao Chen

Here is the complete list of my publications.

For further information, please also refer to my Google Scholar and my DBLP Profile.

Conferences

  • Wentao Huang, Weimin Lyu, Peiliang Lou, Qingqiao Hu, Xiaoling Hu, Shahira Abousamra, Wenchao Han, Ruifeng Guo, Jiawei Zhou, Chao Chen, Chen Wang: "Act Like a Pathologist: Tissue-Aware Whole Slide Image Reasoning", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2026 ( paper)

  • Jachao Lee, Shahira Abousamra, Michael L. Miller, Harrison Xiao, Kevin L. Gardner, Andrew F. Teich, Chao Chen: "Automated anatomical segmentation for human hippocampal histology sections", in Proceedings of SPIE--the International Society for Optical Engineering, 2026

  • Meilong Xu, Xiaoling Hu, Shahira Abousamra, Chen Li, Chao Chen: "MATCH: Multi-faceted Adaptive Topo-Consistency for Semi-Supervised Histopathology Segmentation", in the Conference on Neural Information Processing Systems (NeurIPS), 2025

  • Meilong Xu, Saumya Gupta, Xiaoling Hu, Chen Li, Shahira Abousamra, Dimitris Samaras, Prateek Prasanna, Chao Chen: "TopoCellGen: Generating Histopathology Cell Topology with a Diffusion Model", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025 (Oral presentation, acceptance rate 0.7%, paper)

  • Aniruddha Ganguly, Debolina Chatterjee, Wentao Huang, Jie Zhang, Alisa Yurovsky, Travis Steele Johnson, Chao Chen: "MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025 (acceptance rate 22.1%, paper)

  • Saumya Gupta, Dimitris Samaras, Chao Chen:"TopoDiffusionNet: A Topology-aware Diffusion Model", in The International Conference on Learning Representations (ICLR), 2025

  • Weimin Lyu, Jiachen Yao, Saumya Gupta, Lu Pang, Tao Sun, Lingjie Yi, Lijie Hu, Haibin Ling, Chao Chen:"Backdooring Vision-Language Models with Out-Of-Distribution Data", in The International Conference on Learning Representations (ICLR), 2025

  • Lingjie Yi, Jiachen Yao, Weimin Lyu, Haibin Ling, Raphael Douady, Chao Chen:"Geometry of Long-Tailed Representation Learning: Rebalancing Features for Skewed Distributions", in The International Conference on Learning Representations (ICLR), 2025

  • Lingjie Yi, Tao Sun, Yikai Zhang, Songzhu Zheng, Weimin Lyu, Haibin Ling, Chao Chen:"PivotAlign: Improve Semi-Supervised Learning by Learning Intra-Class Heterogeneity and Aligning with Pivots", in IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025

  • Mahmudul Hasan, Ariadna Kim Silva, Shahira Abousamra, Shao-Jun Tang, Prateek Prasanna, Joel Saltz, Kevin L. Gardner, Chao Chen, Alisa Yurovsky:"New Spatial Phenotypes from Imaging Uncover Survival Differences for Breast Cancer Patients", in the 15th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), 2024 (Oral Presentation)

  • Weimin Lyu, Zexin Bi, Fusheng Wang, Chao Chen:"BadCLM: Backdoor Attack in Clinical Language Models for Electronic Health Records", in Proceedings of AMIA Annual Symposium (AMIA), 2024 (nominated for best student paper)

  • Mahmudul Hasan, Xiaoling Hu, Shahira Abousamra, Prateek Prasanna, Joel Saltz, Chao Chen:"Semi-Supervised Contrastive VAE for Disentanglement of Digital Pathology Images", in International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), 2024 (acceptance rate 31%, paper)

  • Wentao Huang, Xiaoling Hu, Shahira Abousamra, Prateek Prasanna, Chao Chen:"Hard Negative Sample Mining for Whole Slide Image Classification", in International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), 2024 (acceptance rate 31%, paper)

  • Chen Li, Xiaoling Hu, Shahira Abousamra, Meilong Xu, Chao Chen:"Spatial Diffusion for Cell Layout Generation", in International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), 2024 (acceptance rate 31%, paper)

  • Weimin Lyu, Lu Pang, Tengfei Ma, Haibin Ling, Chao Chen:"TrojVLM: Backdoor Attack Against Vision Language Models", in European Conference on Computer Vision (ECCV), 2024 (acceptance rate 27.9%, paper)

  • Meilong Xu, Xiaoling Hu, Saumya Gupta, Shahira Abousamra, Chao Chen:"Semi-supervised Segmentation of Histopathology Images with Noise-Aware Topological Consistency", in European Conference on Computer Vision (ECCV), 2024 (acceptance rate 27.9%, paper)

  • Weimin Lyu, Xiao Lin, Songzhu Zheng, Lu Pang, Haibin Ling, Susmit Jha, Chao Chen: "Task-Agnostic Detector for Insertion-Based Backdoor Attacks", in The 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL Findings), 2024

  • Saarthak Kapse, Pushpak Pati, Srijan Das, Jingwei Zhang, Chao Chen, Maria Vakalopoulou, Joel Saltz, Dimitris Samaras, Rajarsi R. Gupta, Prateek Prasanna: "SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024 (acceptance rate 23.6%, paper)

  • Jiachen Yao, Nina Hagemann, Qiaojie Xiong, Jianxu Chen, Dirk M. Hermann, Chao Chen: "Topological Analysis of Mouse Brain Vasculature via 3D Light-sheet Microscopy Images", in IEEE International Symposium on Biomedical Imaging (ISBI), 2024 (paper)

  • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen, Yusu Wang: "Cycle Invariant Positional Encoding for Graph Representation Learning", in Learning on Graphs Conference (LoG), 2023 (Oral presentation, paper)

  • Weimin Lyu, Songzhu Zheng, Lu Pang, Haibin Ling, Chao Chen: "Attention-Enhancing Backdoor Attacks Against BERT-based Models", in EMNLP Findings , 2023

  • Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen: "Topology-Aware Uncertainty for Image Segmentation", in the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2023 (acceptance rate 26.1%, paper)

  • Chen Li, Xiaoling Hu, Shahira Abousamra, Chao Chen: "Calibrating Uncertainty for Semi-Supervised Crowd Counting", in International Conference on Computer Vision (ICCV), 2023, (acceptance rate 26.15%, paper)

  • Aishik Konwer, Xiaoling Hu, Joseph Bae, Xuan Xu, Chao Chen, Prateek Prasanna: "Enhancing Modality-Agnostic Representations via Meta-Learning for Brain Tumor Segmentation", in International Conference on Computer Vision (ICCV), 2023, (acceptance rate 26.15%, paper)

  • Shahira Abousamra, Danielle Fassler, Jiachen Yao, Rajarsi R. Gupta, Tahsin Kurc, Luisa Escobar-Hoyos, Dimitris Samaras, Kenneth Shroyer, Joel Saltz, Chao Chen: "Unsupervised Stain Decomposition via Inversion Regulation for Multiplex Immunohistochemistry Images", in Medical Imaging with Deep Learning (MIDL), 2023, (Oral presentation, paper)

  • Shahira Abousamra, Rajarsi Gupta, Tahsin Kurc, Dimitris Samaras, Joel Saltz, Chao Chen: "Topology-Guided Multi-Class Cell Context Generation for Digital Pathology", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023, (Acceptance rate of CVPR is 25.8%, paper).

  • Lu Pang, Tao Sun, Haibin Ling, Chao Chen: "Backdoor Cleansing with Unlabeled Data", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023, (Acceptance rate of CVPR is 25.8%, paper).

  • Xiaoling Hu, Dimitris Samaras, Chao Chen: "Learning Probabilistic Topological Representations Using Discrete Morse Theory", in the International Conference on Learning Representations (ICLR), 2023 (Spotlight, acceptance rate for oral/spotlight is 7.5%, paper)

  • Chen Li, Xiaoling Hu, Chao Chen: "Confidence Estimation Using Unlabeled Data", in the International Conference on Learning Representations (ICLR), 2023 (acceptance rate 32%, paper)

  • Jiachen Yao, Yikai Zhang, Songzhu Zheng, Mayank Goswami, Prateek Prasanna, Chao Chen: "Learning to Segment from Noisy Annotations: A Spatial Correction Approach", in the International Conference on Learning Representations (ICLR), 2023 (acceptance rate 32%, paper)

  • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen: "Neural Approximation of Extended Persistent Homology on Graphs", in the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022 (paper, acceptance rate 25.6%)

  • Saumya Gupta, Xiaoling Hu, James Kaan, Michael Jin, Mutshipay Mpoy, Katherine Chung, Gagandeep Singh, Mary Saltz, Tahsin Kurc, Joel Saltz, Apostolos Tassiopoulos, Prateek Prasanna and Chao Chen: "Learning Topological Interactions for Multi-Class Medical Image Segmentation", in European Conference on Computer Vision (ECCV), 2022 (Oral presentation, acceptance rate 2.7%, paper)

  • Weimin Lyu, Xinyu Dong, Rachel Wong, Songzhu Zheng, Kayley Abell-Hart, Fusheng Wang and Chao Chen: "A Multimodal Transformer: Fusing Clinical Notes with Structured EHR Data for Interpretable In-Hospital Mortality Prediction", in Proceedings of AMIA Annual Symposium (AMIA), 2022

  • Lujain Alsaleh, Chen Li, Justin L. Couetil, Kun Huang, Jie Zhang, Chao Chen and Travis S. Johnson: "Spatial transcriptomic analysis reveals associations between genes and cellular topology in breast and prostate cancers", in International Conference on Intelligent Biology and Medicine (ICIBM), 2022

  • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang and Chao Chen: "Cycle Representation Learning for Inductive Relation Prediction", in International Conference on Machine Learning (ICML), 2022 (acceptance rate 21.9%, paper, poster)

  • Weimin Lyu, Songzhu Zheng, Tengfei Ma, Chao Chen: "A Study of the Attention Abnormality in Trojaned BERTs", in The 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022 (acceptance rate 26%, paper).

  • Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pritham Pingali, Chao Chen, Mayank Goswami: "Stability of SGD: Tightness Analysis and Improved Bounds", in The Conference on Uncertainty in Artificial Intelligence (UAI), 2022

  • Aishik Konwer, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna: "Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022, (Oral Presentation, the overall acceptance rate of CVPR is 25.33%).

  • Fan Wang, Hubert Wagner, Chao Chen: "GPU Computation of the Euler Characteristic Curve for Imaging Data", in International Symposium on Computational Geometry (SoCG), 2022.

  • Xiaoling Hu, Xiao Lin, Michael Cogswell, Yi Yao, Susmit Jha, Chao Chen: "Trigger Hunting with a Topological Prior for Trojan Detection", in the International Conference on Learning Representations (ICLR), 2022

  • Wenjia Zhang, Yikai Zhang, Xiaoling Hu, Mayank Goswami, Chao Chen, Dimitris Metaxas: "A Manifold View of Adversarial Risk", in International Conference on Artificial Intelligence and Statistics (AISTATS), 2022

  • Songzhu Zheng, Yikai Zhang, Hubert Wagner, Mayank Goswami, Chao Chen: "Topological Detection of Trojaned Neural Networks", in the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021, (acceptance rate 26%)

  • Shahira Abousamra, David Belinsky, John Van Arnam, Felicia Allard, Eric Yee,Rajarsi Gupta, Tahsin Kurc, Dimitris Samaras, Joel Saltz, Chao Chen: "Multi-Class Cell Detection Using Spatial Context Representation", in International Conference on Computer Vision (ICCV), 2021 (Oral, acceptance rate 3%)

  • Jiaqi Yang, Xiaoling Hu, Chao Chen, Chialing Tsai: "A Topological-Attention ConvLSTM Network and Its Application to EM Images", in the 24th International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), 2021 (acceptance rate 32.7%)

  • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang and Chao Chen: "Persistence Homology for Link Prediction: An Interactive View", in International Conference on Machine Learning (ICML), 2021 (acceptance rate 21.5%, paper)

  • Fan Wang, Saarthak Kapse, Steven Liu, Prateek Prasanna, and Chao Chen: "TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer", in international conference on Information Processing in Medical Imaging (IPMI), 2021

  • Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Amit Gupta, Chao Chen, Joel Saltz, Prateek Prasanna: "Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network", in Medical Imaging with Deep Learning(MIDL), 2021

  • Xiaoling Hu, Yusu Wang, Li Fuxin, Dimitris Samaras, Chao Chen: "Topology-Aware Segmentation Using Discrete Morse Theory", in the Nineth International Conference on Learning Representations (ICLR), 2021, (Spotlight, acceptance rate for spotlight+oral = 5.6%)

  • Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Mayank Goswami, Chao Chen: "Learning with feature dependent label noise: a progressive approach", in the Nineth International Conference on Learning Representations (ICLR), 2021, (Spotlight, acceptance rate for spotlight+oral = 5.6%)

  • Jiaqi Yang, Xiaoling Hu, Chao Chen , Chia-Ling Tsai: "3D Topology-Preserving Segmentation with Compound Multi-Slice Representation", in IEEE International Symposium on Biomedical Imaging (ISBI), 2021

  • Shahira Abousamra, Minh Hoai Nguyen, Dimitris Samaras, Chao Chen: "Localization in the Crowd with Topological Constraints", in The 35th AAAI Conference in Artificial Intelligence (AAAI), 2021, (acceptance rate 21%)

  • Pengxiang Wu, Songzhu Zheng, Mayank Goswami, Dimitris Metaxas, Chao Chen: "A Topological Filter for Learning with Label Noise", in the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), 2020, (acceptance rate 20.1%)

  • Jialin Yuan, Chao Chen, Li Fuxin: "Deep Variational Instance Segmentation", in the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), 2020, (acceptance rate 20.1%)

  • Cong Chen, Jiaqi Yang, Chao Chen and Changhe Yuan: "Solving Multiple Inference by Minimizing Expected Loss", in the 10th international conference on probabilistic graphical models (pgm), 2020.

  • Cong Chen, Changhe Yuan, Chao Chen: "efficient heuristic search for m-modes inference", in the 10th international conference on probabilistic graphical models (pgm), 2020.

  • Fan Wang, Huidong Liu, Dimitris Samaras, Chao Chen: "TopoGAN: A Topology-Aware Generative Adversarial Network", in European Conference on Computer Vision(ECCV), 2020, (paper, supplemental material, Oral, acceptance rate 2.1%).

  • Hui Qu, Yikai Zhang, Qi Chang, Zhennan Yan, Chao Chen, Dimitris Metaxas: "Learn distributed GAN with Temporary Discriminators", in European Conference on Computer Vision(ECCV), 2020, (acceptance rate 27.1%).

  • Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen: "Error-Bounded Correction of Noisy Labels", in International Conference on Machine Learning (ICML), 2020, (acceptance rate 21.8%).

  • Andrew Aukerman, Mathieu Carrière, Chao Chen, Kevin Gardner, Raúl Rabadán, Rami Vanguri: "Persistent Homology Based Characterization ofthe Breast Cancer Immune Microenvironment: A Feasibility Study", in International Symposium on Computational Geometry (SoCG), 2020.

  • Qi Chang, Hui Qu, Yikai Zhang, Mert Sabuncu, Chao Chen, Tong Zhang, Dimitris Metaxas: "Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020, (acceptance rate 22.1%).

  • Shahira Abousamra, Danielle Fassler, Le Hou, Yuwei Zhang, Rajarsi Gupta, Tahsin Kurc, Luisa F. Escobar-Hoyos, Dimitris Samaras, Beatrice Knudson, Kenneth Shroyer, Joel Saltz, Chao Chen: "Weakly-Supervised Deep Stain Decomposition for Multiplex IHC Images", in IEEE International Symposium on Biomedical Imaging (ISBI), 2020

  • Qi Zhao, Ze Ye, Yusu Wang, Chao Chen: "Persistence Enhanced Graph Neural Network", in International Conference on Artificial Intelligence and Statistics (AISTATS), 2020

  • Ze Ye, Kin Sum Liu, Tengfei Ma, Jie Gao, Chao Chen: "Curvature Graph Network", in the Eighth International Conference on Learning Representations(ICLR), 2020, (pdf, code, acceptance rate 26.5%).

  • Yikai Zhang, Hui Qu, Dimitris Metaxas, Chao Chen: "Local Regularizer Improves Generalization", in The 34th AAAI Conference in Artificial Intelligence (AAAI), 2020, (acceptance rate 20.6%)

  • Xiaoling Hu, Fuxin Li, Dimitris Samaras, Chao Chen: "Topology-Preserving Deep Image Segmentation", in the Thirty-third Conference on Neural Information Processing Systems (NeurIPS), 2019, (acceptance rate 21.2%)

  • Xiuyan Ni, Yang Yu, Peng Wu, Youlin Li, Shaoliang Nie, Qichao Que, Chao Chen: "Feature Selection for Facebook Feed Ranking System via a Group-Sparsity-Regularized Training Algorithm", in The 28th ACM International Conference on Information and Knowledge Management (CIKM), 2019

  • Ze Ye, Cong Chen, Changhe Yuan, Chao Chen: "Diverse Multiple Prediction on Neural Image Reconstruction", in the 22st International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), 2019, (Early Acceptance)

  • Yikai Zhang, Hui Qu, Chao Chen, Dimitris Metaxas:"Taming the Noisy Gradient: Train Deep Neural Networks with Small Batch Sizes", in the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019, (acceptance rate 17.9%)

  • Xudong Zhang, Pengxiang Wu, Changhe Yuan, Yusu Wang, Dimitris Metaxas, Chao Chen: "Heuristic Search for Homology Localization Problem and Its Application in Cardiac Trabeculae Reconstruction", in the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019, (acceptance rate 17.9%)

  • Chao Chen, Xiuyan Ni, Qinxun Bai, Yusu Wang: "A Topological Regularizer for Classifiers via Persistent Homology", in International Conference on Artificial Intelligence and Statistics (AISTATS), 2019

  • Pengxiang Wu, Hui Qu, Jingru Yi, Qiaoying Huang, Chao Chen, Dimitris Metaxas: "Deep Attentive Feature Learning for Histopathology Image Classification", in IEEE International Symposium on Biomedical Imaging (ISBI), 2019

  • Pengxiang Wu, Chao Chen, Jingru Yi, Dimitris Metaxas: "Point Cloud Processing via Recurrent Set Encoding", in The 33rd AAAI Conference in Artificial Intelligence (AAAI), 2019, (acceptance rate 16.2%)

  • Cong Chen, Changhe Yuan, Ze Ye, Chao Chen: "Solving M-Modes in Loopy Graphs Using Tree Decompositions", in The 9th International Conference on Probabilistic Graphical Models (PGM), 2018.

  • Xiuyan Ni, Zhennan Yan, Tingting Wu, Jin Fan, Chao Chen: "A Region-of-Interest-Reweight 3D Convolutional Neural Network for the Analytics of Brain Information Processing", in the 21st International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), 2018, (Oral Presentation, Acceptance Rate 4%).

  • Xiuyan Ni, Novi Quadrianto, Yusu Wang, Chao Chen: "Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data", in the 34rd International Conference on Machine Learning (ICML), 2017, (acceptance rate 25.46%) (pdf)

  • Pengxiang Wu, Chao Chen, Yusu Wang, Shaoting Zhang, Changhe Yuan, Zhen Qian, Dimitris Metaxas, Leon Axel: "Optimal Topological Cycles and Their Application in Cardiac Trabeculae Restoration", in the 25th biennial international conference on Information Processing in Medical Imaging (IPMI), 2017, (Oral presentation, acceptance rate 14.32%, pdf, code)

  • Chao Chen, Dimitris Metaxas, Yusu Wang, Pengxiang Wu: "Cardiac Trabeculae Segmentation, an Application of Computational Topology", in the 33rd International Symposium on Computational Geometry (SoCG): Multimedia Session, 2017, (pdf, video)

  • Chao Chen, Novi Quadrianto: "Clustering High Dimensional Categorical Data via Topographical Features", in the 33rd International Conference on Machine Learning (ICML), 2016, (acceptance rate 24.26%) (pdf)

  • Cong Chen, Changhe Yuan, Chao Chen: "Solving M-Modes Using Heuristic Search", in the 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016 (pdf)

  • Scott Kulp, Chao Chen, Dimitris Metaxas, Leon Axel: "Ventricular blood flow analysis using topological methods", in International Symposium on Biomedical Imaging (ISBI), 2015 (pdf)

  • Chao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao: "Mode Estimation for High Dimensional Discrete Tree Graphical Models", in Advances in Neural Information Processing Systems (NIPS), 2014 (Spotlight oral, acceptance rate ~5%, pdf, technical report available soon)

  • Mustafa Uzunbas, Chao Chen, Dimitris Metaxas: "Optree: a Learning-Based Adaptive Watershed Algorithm for Neuron Segmentation", in the 17th Annual International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2014. (Early acceptance rate ~10%, pdf)

  • Mingchen Gao, Chao Chen, Shaoting Zhang, Zhen Qian, Mani Vannan, Sarah Rinehart, Dimitris Metaxas, Leon Axel: "Morphological analysis of the papillary muscles and the trabaculae", in International Symposium on Biomedical Imaging (ISBI), 2014 (pdf)

  • Mustafa Uzunbas, Chao Chen, Shaoting Zhang, Kilian Pohl, Kang Li, Dimitris Metaxas: "Collaborative multi organ segmentation by integrating deformable and graphical models", in International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2013 (pdf)

  • Mingchen Gao *, Chao Chen *, Shaoting Zhang, Zhen Qian, Dimitris Metaxas, Leon Axel: "Segmenting the papillary muscles and the trabeculae from high resolution cardiac CT through restoration of topological handles", in International Conference on Information Processing in Medical Imaging (IPMI), 2013 (pdf) (* contributed equally)

  • Chao Chen, Vladimir Kolmogorov, Yan Zhu, Dimitris Metaxas, Christoph Lampert: "Computing the M most probable modes of a graphical model", in International Conference on Artificial Intelligence and Statistics (AISTATS), 2013 (Oral presentation, acceptance rate ~11% pdf, supplemental material)

  • Novi Quadrianto, Chao Chen, Christoph Lampert: "The most persistent soft-clique in a set of sampled graphs", in International Conference on Machine Learning (ICML), 2012 (pdf)

  • Oleksiy Busaryev, Sergio Cabello, Chao Chen, Tamal K. Dey, Yusu Wang: "Annotating simplices with a homology basis and its applications", in Scandinavian Symposium and Workshops on Algorithm Theory (SWAT), 2012 (pdf)

  • Chao Chen, Herbert Edelsbrunner: "Diffusion runs low on persistence fast", in IEEE International Conference on Computer Vision (ICCV), 2011 (Acceptance rate 23.7%, pdf, poster, code)

  • Chao Chen, Daniel Freedman, Christoph H. Lampert: "Enforcing topological constraints in random field image segmentation", in IEEE Computer Vision and Pattern Recognition (CVPR), 2011 (pdf, technical report, poster, code)

  • Chao Chen, Michael Kerber: "An output-sensitive algorithm for persistent homology", in Annual Symposium on Computational Geometry (SoCG), 2011 (pdf)

  • Chao Chen, Daniel Freedman: "Hardness results for homology localization", in Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2010 (pdf)

  • Chao Chen, Daniel Freedman: "Quantifying homology classes", in Annual Symposium on Theoretical Aspects of Computer Science (STACS), 2008 (pdf)
    Note: Proofs of the NP-hardness results in this paper are available in "Quantifying homology classes II: localization and stability".

Journals and Book Chapters

  • Sandeep Singhal, Chen Li, Andrew Aukerman, Mathieu Carrière, Michael L. Miller, Hanina Hibshoosh, Jasmine McDonald, Joy Winfield, Sai Tun Hein Aung, Gustavo Martinez-Delgado, Ziv Frankenstein, Young-Ho Lee, Raul Rabadan, Joel Saltz, Chao Chen, Kevin Gardner:"Topology-Based Biomarkers Accurately Predict Breast Cancer Outcome and Survival ", in Cancer Research, 2026

  • Andrea M Bejar, Maria Jaramillo Gonzalez, Ziliang Hong, Gorkem Durak, Elif Keles, Halil Ertugrul Aktas, Zheyuan Zhang, Hongyi Pan, Zeynep Sue Jozwiak, Fergan Bol, Lili Zhao, Chao Chen, Concetto Spampinato, Alpay Medetalibeyoglu, Sukru Mehmet Erturk, Gulbiz Dagoglu Kartal, Yury Velichko, Emil Agarunov, Ziyue Xu, Sachin Jambawalikar, Ivo G Schoots, Marco J Bruno, Chenchang Huang, Tamas Gonda, Candice Bolan, Frank H Miller, Michael B Wallace, Rajesh N Keswani, Pallavi Tiwari, Ulas Bagci:"Multi-center evaluation of radiomics and deep learning to stratify malignancy risk of IPMNs", in Abdominal Radiology, 2026

  • Debolina Chatterjee, Justin L Couetil, Ziyu Liu, Kun Huang, Chao Chen, Jie Zhang, Michael A Kalwat, Travis S Johnson:"Identification of High-Risk Cells in Single-Cell Spatially Resolved Transcriptomics Data Using DEGAS Spatial Smoothing", in Bioinformatics, 2026

  • Justin L Couetil, Ziyu Liu, Chao Chen, Ahmed K Alomari, Kun Huang, Jie Zhang, Travis S Johnson:"Deep Transfer Learning Links Benign Glands to Prostate Cancer Progression via Transcriptomics", in Genomics, Proteomics & Bioinformatics, 2025

  • Jieying Wu, Joseph Bae, Chao Chen, Samuel Ryu, Daniel Lozeau, Alexander Stessin, Prateek Prasanna:"Magnetic Resonance Imaging Radiomic Analysis of Radiation-Induced Morphea of the Breast: A Proof-of-Concept Study", in Advances in Radiation Oncology, 2025

  • Jiaqi Yang, Nitish Mehta, Xiaoling Hu, Chao Chen, and Chia-Ling Tsai:"Text-Driven Weakly Supervised OCT Lesion Segmentation with Structural Guidance", in IEEE Journal of Biomedical and Health Informatics, 2025

  • Shahira Abousamra, Danielle Fassler, Rajarsi Gupta, Tahsin Kurc, Luisa F. Escobar-Hoyos, Dimitris Samaras, Kenneth R. Shroyer, Joel Saltz, Chao Chen:"Label-Efficient Deep Color Deconvolution of Brightfield Multiplex IHC Images", in IEEE Transactions on Medical Imaging, 2025

  • Jiajun Cao, Jan Wenzel, Shanghang Zhang, Josephine Lampe, Hongxiao Wang, Jiachen Yao, Zhicheng Zhang, Shuo Zhao, Yu Zhou, Chao Chen, Markus Schwaninger, Jufeng Yang, Danny Z. Chen, Jianxu Chen:"Rethinking deep learning in bioimaging through a data centric lens", in NPJ Imaging, 2025

  • Yujie Xiao, Manal Elmasry, Ji Dong K. Bai, Andrew Chen, Yuzhu Chen, Brooke Jackson, Joseph O. Johnson, Robert J. Gillies, Prateek Prasanna, Chao Chen, Mehdi Damaghi:"Eco-evolutionary Guided Pathomics Analysis to Predict DCIS Upstaging", in Cancer Research, 2025

  • Jiachen Yao, Lingjie Yi, Mayank Goswami, Chao Chen:"A Theoretical Study of Neural Network Expressive Power via Manifold Topology", in Transactions on Machine Learning Research (TMLR), 2025

  • Zuoyu Yan, Qi Zhao, Ze Ye, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen:"Enhancing Graph Representation Learning with Localized Topological Features", in Journal of Machine Learning Research (JMLR), 2025

  • Yunye Gong, Jiachen Yao, Ruyi Lian, Xiao Lin, Chao Chen, Ajay Divakaran, Yi Yao:"Recovering manifold representations via unsupervised meta-learning", in Frontiers in Computer Science, 2025

  • Fan Wang, Zhilin Zou, Nicole Sakla, Luke Partyka, Nil Rawal, Gagandeep Singh, Wei Zhao, Haibin Ling, Chuan Huang, Prateek Prasanna, Chao Chen:"TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs", in Medical Image Analysis, 2025

  • Xiuxiu Yang, Debolina Chatterjee, Justin L. Couetil, Ziyu Liu, Valerie D. Ardon, Chao Chen, Jie Zhang, Kun Huang, Travis S. Johnson:"Gradient boosting reveals spatially diverse choles- terol gene signatures in colon cancer", in Frontiers in Genetics, 2024

  • Wenjia Zhang, Yikai Zhang, Xiaoling Hu, Yi Yao, Mayank Goswami, Chao Chen, Dimitris Metaxas:"Manifold-driven decomposition for adversarial robustness", in Frontiers in Computer Science, 2024

  • Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen:"Learning to Abstain From Uninformative Data", in Transactions on Machine Learning Research (TMLR), 2024

  • Fan Wang, Hubert Wagner, Chao Chen:"GPU Computation of the Euler Characteristic Curve for Imaging Data", in Journal of Computational Geometry, 2024

  • Xinyu Dong, Rachel Wong, Weimin Lyu, Kayley Abell-Hart, Jianyuan Deng, Yinan Liu, Janos G. Hajagos, Richard N. Rosenthal, Chao Chen, Fusheng Wang:"An Integrated LSTM-HeteroRGNN Model for Interpretable Opioid Overdose Risk Prediction", in Artificial Intelligence In Medicine, 2023

  • Lujain Alsaleh, Chen Li, Justin L. Couetil, Kun Huang, Jie Zhang, Chao Chen, Travis S. Johnson:"Spatial transcriptomic analysis reveals associations between genes and cellular topology in breast and prostate cancers", in Cancers (Special Issue for ICIBM), 2022

  • Tingting Wu, Melissa-Ann Mackie, Chao Chen, Jin Fan:""Representational coding of overt and covert orienting of visuospatial attention in the frontoparietal network", in NeuroImage, 2022

  • Mathieu Carriere, Chao Chen, Kevin Gardner, Rau ́l Rabada ́n, Rami Vanguri:"Persistent homology based characterization of the breast cancer immune microenvironment: a feasibility study", in Journal of Computational Geometry, 2022

  • Shahira Abousamra, Rajarsi Gupta, Le Hou, Rebecca Batiste, Tianhao Zhao, Anand Shankar, Arvind Rao, Chao Chen, Dimitris Samaras, Tahsin Kurc, Joel Saltz:"Deep Learning-Based Mapping of Tumor Infiltrating Lymphocytes in Whole Slide Images of 23 Types of Cancer", in Frontiers in oncology, 2022

  • Danielle J Fassler, Shahira Abousamra, Rajarsi Gupta, Chao Chen, Maozheng Zhao, David Paredes, Syeda Areeha Batool, Beatrice S Knudsen, Luisa Escobar-Hoyos, Kenneth R Shroyer, Dimitris Samaras, Tahsin Kurc, Joel Saltz: "Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images", in Diagnostic pathology, 2020

  • Tingting Wu, Alfredo Spagna, Chao Chen, Kurt P. Schulz, Patrick R. Hof, and Jin Fan: "Supramodal Mechanisms of the Cognitive Control Network in Uncertainty Processing.", in Cerebral Cortex, 2020

  • W. Zheng, T. Eilamstock, T. Wu, A. Spagna, Chao Chen, B. Hu, J. Fan: "Multi-feature based network revealing the structural abnormalities in autism spectrum disorder", in IEEE Transactions on Affective Computing, 2019

  • Suwichaya Suwanwimolkul, Lei Zhang, Dong Gong, Zhen Zhang, Chao Chen, Damith C. Ranasinghe, Qinfeng Shi: "An Adaptive Markov Random Field for Structured Compressive Sensing", in IEEE Transactions on Image Processing (TIP), 2019

  • Tingting Wu, Alexander J. Dufford, Laura J. Egan, Melissa-Ann Mackie, Cong Chen, Changhe Yuan, Chao Chen, Xiaobo Li, Xun Liu, Patrick R. Hof, Jin Fan: "Hick–Hyman Law is Mediated by the Cognitive Control Network in the Brain", in Cerebral Cortex pp. 1-16, May 2017 (pdf)

  • Jingjing Liu, Chao Chen, Yan Zhu, Wei Liu, Dimitris Metaxas: “Video Classification via Weakly Supervised Sequence Modeling”, in Computer Vision and Image Understanding (CVIU) 152 pp. 79-87, Nov. 2016 (pdf)

  • Mustafa Uzunbas, Chao Chen, Dimitris Metaxas: “ An efficient conditional random field approach for automatic and interactive neuron segmentation”, in Medical Image Analysis (MedIA) 27 pp. 31-44, Jan. 2016 (pdf)

  • Arjun Jain, Chao Chen, Thorsten Thormählen, Dimitris Metaxas, Hans-Peter Seidel: “Multi-layer stencil creation from images”, in Computer & Graphics (C&G) 48 pp. 11-22, 2015 (pdf, video, website)

  • Chao Chen, Michael Kerber: “An output-sensitive algorithm for persistent homology”, in Computational Geometry: Theory and Applications (CGTA) 46 (4) pp. 435-447 - Special Issue on the 27th Annual Symposium on Computational Geometry, 2013 (pdf)

  • Yu Sheng, Barbara Cutler, Chao Chen, Joshua Nasman: "Perceptual global illumination cancellation in complex projection environments", in Computer Graphics Forum (CGF), Volume 30, Issue 4, Eurographics Symposium on Rendering (EGSR), 2011 (pdf)

  • Daniel Freedman, Chao Chen: "Algebraic topology for computer vision", Chapter 5 of Computer Vision, 239-268, Ed. Sota R. Yoshida, Nova Science Pub. Inc., Hauppauge, New York, 2011 (pdf)

  • Chao Chen, Daniel Freedman: "Hardness results for homology localization", in Discrete & Computational Geometry (DCG) 45(3): 425-448, 2011 (pdf)

  • Chao Chen, Daniel Freedman: "Measuring and computing natural generators for homology groups", in Computational Geometry: Theory and Applications (CGTA) 43(2): 169-181, 2010 (pdf)

  • Chao Chen, Ho-Lun Cheng: "Superimposing voronoi complexes for shape deformation", in International Journal of Computational Geometry and Applications (IJCGA) 16(2-3): 159-174 2006

Workshops

  • Weiran Lyu, Saumya Gupta, Chao Chen, Bei Wang: "Structural Uncertainty Visualization of Morse Complexes for Time-Varying Data Prediction", in Proceedings of the IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis), 2025

  • Juyoung Yun, Shahira Abousamra, Chen Li, Rajarsi Gupta, Tahsin Kurc, Dimitris Samaras, Alison L Van Dyke, Joel Saltz, Chao Chen: "Uncertainty Estimation for Tumor Prediction with Unlabeled Data", in CVPR Workshop on Computer Vision for Microscopy Image Analysis, 2024

  • Meilong Xu, Nate Anderson, Richard M. Levenson, Prateek Prasanna, Chao Chen: "A Topological Comparison of the Fluorescence Imitating Brightfield Imaging and H&E Imaging", in MICCAI International Workshop on Topology- and Graph-Informed Imaging Informatics, 2024

  • Aishik Konwer, Chao Chen, Prateek Prasanna: "MagNET: Modality-Agnostic Network for Brain Tumor Segmentation and Characterization with Missing Modalities", in MICCAI International Workshop on Machine Learning in Medical Imaging, 2023

  • David Paredes, Prateek Prasanna, Christina Preece, Rajarsi R. Gupta, Farzad Fereidouni, Dimitris Samaras, Tahsin Kurc, Richard M. Levenson, Patricia Thompson-Carino, Joel Saltz, Chao Chen: "Automated Assessment of the Curliness of Collagen Fiber in Breast Cancer", in ECCV Workshop BioImage Computing (BIC), 2020

  • X. Ni, T. Gao, T. Wu, J. Fan, Chao Chen: "Learning Human Cognition via fMRI Analysis Using 3D CNN and Graph Neural Network", in MICCAI Workshop MBIA (Multimodal Brain Image Analysis), 2019

  • F.Wang, C.Deng, B. Yuan, Chao Chen: "Hardware Acceleration of Persistent Homology Computation", in MICCAI Workshop HAL-MICCAI (Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention), 2019

  • Chao Chen, Dimitris Metaxas, Yusu Wang, Pengxiang Wu, Changhe Yuan: "Cardiac Trabeculae Segmentation: an Application of Computational Topology", in the 27th Annual Fall Workshop on Computational Geometry (FWCG), 2017

  • Chao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao: "Identifying Sub-Networks of Functional Connectivity Using Modes of Distributions", in the 4th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI), 2014

  • Hubert Wagner, Chao Chen, Erald Vuçini: "Efficient computation of persistent homology for cubical data", in Proceedings of the 4th Workshop on Topology-based Methods in Data Analysis and Visualization (TopoInVis), 2011 (Best paper runner-up, pdf)

  • Chao Chen, Michael Kerber: "Persistent homology computation with a twist", in European Workshop on Computational Geometry (EuroCG), 2011 (pdf)

  • Chao Chen, Daniel Freedman: "Topology noise removal for curve and surface evolution", in Proceedings of the Medical Computer Vision Workshop (MCV) (in conjunction with MICCAI), 2010