Conference Papers

Conference Papers

  1. Chen J, Guo Y, Guo H, Wang Y, Yin R, Better Listening through Seeing? Origins and Theory-Driven Solution to Multimodal Cognitive Conflict in Image Generation, INFORMS Workshop on Data Science, San Francisco, CA. Nov. 2026
  2. Zhu W, Chen X, Wang Z, Wang J, Dong X, Cai R, Sang H, Wang H, Qiu P, Deng Y, Huang M, Tiwari P, Rappazzo BH, Wang Y, AriadneMem: Threading the Maze of Lifelong Memory for LLM Agents, Workshop on Efficient Reasoning, Conference on Language Modeling (COLM), Oct. 2026
  3. Zhu W, Dong X, Chen X, Cai R, Qiu P, Wang Z, Frunza O, Deng Y, Tang S, Gu J, Wang Y, Your Agent is More Brittle Than You Think: Efficiently Mitigating Indirect Injections in Agentic LLMs, Workshop on Efficient Reasoning, Conference on Language Modeling (COLM), Oct. 2026
  4. Chen J, Guo Y, Guo H, Wang Y, Yin R, Better Listening through Seeing? Origins and Theory-Driven Solution to Multimodal Cognitive Conflict in Image Generation. Conference on Information Systems and Technology (CIST) , San Francisco, CA, Oct. 2026
  5. Chen Y, Zhu W, Chen X, Wang Z, Li X, Qiu P, Wang H, Dong X, Xiong Y, Schneider, A, Nevmyaka Y, Wang Y, AHA: Aligning Large Audio-Language Models for Reasoning Hallucinations via Counterfactual Hard Negatives, The 64th Annual Meeting of the Association for Computational Linguistics, (ACL) Findings, July 2026
  6. Chen X, Zhu W, Qiu P, Dong X, Wang H, Wu H, Li H, Sotiras A, Wang Y, Razi A, DRA-GRPO: Your GRPO Needs to Know Diverse Reasoning Paths for Mathematical Reasoning, The 64th Annual Meeting of the Association for Computational Linguistics, (ACL) Findings, July 2026
  7. Dong X, Zhu W, Chen X, Wang Z, Qiu P, Tang S, Li X, Wang Y, LLaDA-MedV: Exploring Large Language Diffusion Models for Biomedical Image Understanding, In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Denver, CO, June 2026.
  8. Chen X, Zhu W, Li G, Dong X, Xiong Y, Wang H, Qiu P, Song Q, Wang Z, Tang S, Wang Y, Razi A, OTPrune: Distribution-Aligned Visual Token Pruning via Optimal Transport, In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) Findings Workshop, Denver, CO, June 2026.
  9. Dong X, Zhu W, Wang H, Chen X, Qiu P, Yin R, Su Y, Wang Y, Talk Before You Retrieve: Agent-Led Discussions for better RAG in Medical QA, Workshop on Multi-Agent Learning and Its Opportunities in the Era of Generative AI, the Fourteen Internation Conference on Learning Representations (ICLR), Apr. 2026
  10. Xiong Y, Dong X, Zhu W, Li X, Dumitrascu OM, Wang Y, SGW-GAN: Sliced Gromov-Wasserstein Guided GANs for Retinal Fundus Image Enhancement, Workshop on Pixels to Patients: Bridging CV State-of-Art with Clinical Impact, IEEE Winter Conference on Applications of Computer Vision (WACVW), Tucson AZ, Mar. 2026. [Oral]
  11. Dong X, Zhu W, Xiong Y, Chen X, Wang H, Li X, Cheng J, Wang Z, Tang S, Dumitrascu OM, Wang Y, VAOT: Vessel-Aware Optimal Transport for Retinal Fundus Enhancement, Workshop on Pixels to Patients: Bridging CV State-of-Art with Clinical Impact, IEEE Winter Conference on Applications of Computer Vision (WACVW), Tucson AZ, Mar. 2026. [Oral]
  12. Li X, Zhu W, Dong X, Wang H, Xiong Y, Dumitrascu OM, Wang Y, nnMobileNet++: Towards Efficient Hybrid Networks for Retinal Image Analysis, Workshop on Pixels to Patients: Bridging CV State-of-Art with Clinical Impact, IEEE Winter Conference on Applications of Computer Vision (WACVW), Tucson AZ, Mar. 2026.
  13. Dong X, Zhu W, Chen X, Wang H, Li X, Xiong Y, Cheng J, Wang Z, Tang S, Dumitrascu OM, Wang Y, Bridging Restoration and Diagnosis: A Comprehensive Benchmark for Retinal Fundus Enhancement, Workshop on Pixels to Patients: Bridging CV State-of-Art with Clinical Impact, IEEE Winter Conference on Applications of Computer Vision (WACVW), Tucson AZ, Mar. 2026.
  14. Zhu W, Dong X, Li X, Qiu P, Chen X, Northrup W, Razi A, Sotiras A, Su Y, Wang Z, Tang S, Wang Y, What Matters in Reinforcement Learning Based Training for Medical Vision Language Model: An Empirical Study, Workshop on Pixels to Patients: Bridging CV State-of-Art with Clinical Impact, IEEE Winter Conference on Applications of Computer Vision (WACVW), Tucson AZ, Mar. 2026.
  15. Wang H, Zhu W, Tang S, Wang Z, Dong X, Li X, Chen X, Bastola A, Huang X, Wang Y, Razi A, EZBlender: Efficient 3D Editing with Plan-and-ReAct Agent, Workshop on Visual Art, Generative AI, and the Legal/Ethical Dilemma, IEEE Winter Conference on Applications of Computer Vision (WACVW), Tucson AZ, Mar. 2026.
  16. Zhu W, Chen X, Wang Z, Tang S, Ghosh S, Dong X, Koner R, Wang Y, EVTP-IVS: Effective Visual Token Pruning For Unifying Instruction Visual Segmentation In Multi-Modal Large Language Models, IEEE Winter Conference on Applications of Computer Vision (WACV), Tucson AZ, Mar. 2026.
  17. Chen X, Zhu W, Qiu P, Wang H, Li H, Wu H, Sotiras A, Wang Y, Razi A, Prompt-OT: An Optimal Transport Regularization Paradigm for Knowledge Preservation in Vision-Language Model Adaptation, IEEE Winter Conference on Applications of Computer Vision (WACV), Tucson AZ, Mar. 2026.
  18. Chen X, Qiu P, Zhu W, Wang H, Li H, Dong X, Sun X, Yu X, Wang Y, Razi A, Sotiras A, Cracking Instance Jigsaw Puzzles: A Superior Alternative to Multiple Instance Learning for Whole Slide Image Analysis, International Conference on Computer Vision (ICCV), Oct. 2025
  19. Zhu W, Qiu P, Chen X, Yang Z, Sotiras A, Razi A, Wang Y, How Effective Can Dropout Be in Multiple Instance Learning? Forty-Second International Conference on Machine Learning (ICML), Jul. 2025
  20. Chen X, Zhu W, Qiu P, Wang H, Li H, Li Z, Wang Y, Sotiras A, Razi A, FIC-TSC: Learning Time Series Classification with Fisher Information Constraint, Forty-Second International Conference on Machine Learning (ICML), Jul. 2025
  21. Che J, Guo Y, Guo H, Wang Y, Yin R, Better Listening Through Seeing: Theory-Driven Image Generation for Multimodal Online Learning, Summer Workshop on AI for Business (SWAIB), Jul 2025
  22. Chen Y, Farazi M, Yang Z, Fan Y, Ashton N, Reiman E, Su Y, Wang Y, Enhancing Alzheimer’s Diagnosis: Leveraging Anatomical Landmarks in Graph Convolutional Neural Networks on Tetrahedral Meshes, Information Processing In Medical Imaging (IPMI), Jun. 2025
  23. Dong, X., Wang, Y., Chen, Y., Li, X., Wang, H., Qiu, P., Chen X, Razi A, Xiong Y, Dumitrascu OM and Zhu, W. DME-MobileNet: Fine-Tuning nnMobileNet for Diabetic Macular Edema Classification. In MICCAI Challenge on Ultra-Widefield Fundus Imaging for Diabetic Retinopathy, May 2025
  24. Wang, H., Zhu, W., Dong, X., Chen, Y., Li, X., Qiu, P., Chen, X., Vasa, V.K., Xiong, Y., Dumitrascu, O.M., Razi, A. and Wang Y. Many-MobileNet: Multi-model Augmentation for Robust Retinal Disease Classification. In MICCAI Challenge on Ultra-Widefield Fundus Imaging for Diabetic Retinopathy, May 2025
  25. Chen Y, Su Y, Dumitrascu C, Chen K, Weidman D, Caselli RJ, Ashton N, Reiman EM, Wang Y, Plasma-CycleGAN: Plasma Biomarker-Guided MRI to PET Cross-Modality Translation Using Conditional CycleGAN, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Houston, TX, US, Apr. 2025 [oral]
  26. Dong X, Zhu W, Li X, Sun G, Su Y, Dumitrascu O, Wang Y, TPOT: Topology Preserving Optimal Transport in Retinal Fundus Image Enhancement, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Houston, TX, US, Apr. 2025
  27. Li X, Zhu W, Dong X, Dumitrascu O, Wang Y, EViT-Unet: U-Net Like Efficient Vision Transformer for Medical Image Segmentation on Mobile and Edge Devices, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Houston, TX, US, Apr. 2025
  28. Qiu P, Zhu W, Kumar S, Chen X, Yang J, Sun X, Razi A, Wang Y, Sotiras A, Multimodal Variational Autoencoder: a Barycentric View, The 39th Annual AAAI Conference on Artificial Intelligence, Philadelphia PA, Feb. 2025 [oral]
  29. Chen X, Qiu P, Zhu W, Li H, Wang H, Sotiras A, Wang Y, Razi A, Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences, The 39th Annual AAAI Conference on Artificial Intelligence, Philadelphia PA, Feb. 2025
  30. Farazi M, Wang Y, A Recipe for Geometry-Aware 3D Mesh Transformers, IEEE Winter Conference on Applications of Computer Vision (WACV), Tucson AZ, Jan. 2025.
  31. Vasa V, Qiu P, Zhu W, Xiong Y, Dumitrascu O, Wang Y, Context-Aware Optimal Transport Learning for Retinal Fundus Image Enhancement, IEEE Winter Conference on Applications of Computer Vision (WACV), Tucson AZ, Jan. 2025
  32. Dong X, Vasa V, Zhu W, Qiu P, Chen X, Su Y, Xiong Y, Yang Z, Chen Y, Wang Y, CUNSB-RFIE: Context-aware Unpaired Neural Schrödinger Bridge in Retinal Fundus Image Enhancement, IEEE Winter Conference on Applications of Computer Vision (WACV), Tucson AZ, Jan. 2025
  33. Wang H, Zhu W, Qin J, Li X, Dumitrascu O, Chen X, Qiu P, Razi A, Wang Y, RBAD: A Dataset and Benchmark for Retinal Bifurcation Angle Detection, IEEE-EMBS International Conference on Biomedical and Health Informatics (ICBHI), 2024
  34. Zhu W, Chen X, Qiu P, Sotiras A, Razi A, Wang Y, DGR-MIL: Exploring Diverse Global Representation in Multiple Instance Learning for Whole Slide Image Classification, 18th European Conference on Computer Vision (ECCV), MiCo Milano, Oct. 2024
  35. Zhu W, Chen X, Qiu P, Farazi M, Sotiras A, Razi A, Wang Y, SelfReg-UNet: Self-Regularized UNet for Medical Image Segmentation, 27th International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI, Marrakesh, Morocco, Oct. 2024
  36. Chen X*, Qiu P*, Zhu W*, Li H, Wang H, Sotiras A, Wang Y, Razi A, TimeMIL: Advancing Multivariate Time Series Classification via a Time-Aware Multiple Instance Learning, 41st International Conference on Machine Learning (ICML), Vienna, Austria, July 2024.
  37. Yang Z, Zhou M, Shan M, Wen B, Xuan Z, Hill M, Bai H, Qi G-J, Wang Y, OmniMotionGPT: Animal Motion Generation with Limited Data, In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, June 2024.
  38. Zhu W, Qiu P, Chen X, Li X, Lepore N, Dumitrascu O, Wang Y, nnMobileNet: Rethinking CNN for Retinopathy Research, Data Curation and Augmentation in Enhancing Medical Imaging Applications Workshop (DCAMI), in conjunction with CVPR 2024, Seattle, WA, June 2024.
  39. Jalili-Mallak N, Tu Y, Lu Z-L, Wang Y, Enhancing 3T Retinotopic Maps Using Diffeomorphic Registration, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Athens, Greece, May 2024.
  40. Xiong Y, Zhu W, Lu Z-L, Wang Y, Reconstructing Retinal Visual Images from 3T fMRI Data Enhanced by Unsupervised Learning, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Athens, Greece, May 2024. [oral]
  41. Yang Z, Su Y, Rouhi R, Farazi M, Zhu W, Chen Y, Reiman EM, Caselli RJ, Chen K, Wang Y, Lepore N, Pre-Training Graph Attention Convolution for Brain Structural Imaging Biomarker Analysis and Its Application to Alzheimer’s Disease Pathology Identification, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Athens, Greece, May 2024. [oral]
  42. Yang Z, Ding K, Liu H, Wang Y, MGM-AE: Self-Supervised Learning on 3D Shape Using Mesh Graph Masked Autoencoders, IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, Jan. 2024.
  43. Yang Z, Ren M, Ding K, Gerig G, Wang Y, Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation, 37th Conference on Neural Information Processing Systems (NeurIPS), New Orleans, LA, Dec. 2023.
  44. Rouhi R, Tanedo J, Wei I M, Valder M, Zanjal S, Gajawelli N, Nelson M, Deoni S, Wang Y, Linguraru M G, Lepore N, Automated Segmentation of the Hippoampus in Pediatric Imaging, 18th International Symposium on Medical Information Processing and Analysis (SIPAIM). Mexico City, Mexico. Nov., 2023
  45. Ye K, Tang H, Dai S, Guo L,  Liu J,  Wang Y, Leow A, Thompson PM, Huang H, Zhan L, Bidirectional Mapping with Contrastive Learning on Multimodal Neuroimaging Data, 26th International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI, Vancouver, Canada Oct. 2023 [Oral]
  46. Zhu W, Qiu P, Chen X, Li H, Wang H, Leporé N, Dumitrascu OM, Wang Y, Beyond MobileNet: An improved MobileNet for Retinal Diseases. In Proceedings of the MICCAI Myopic Maculopathy Analysis Challenge 2023, Springer, 2023.
  47. Li H, Zhu W, Chen X, Wang, Y, Prediction of Spherical Equivalent With Vanilla ResNet. In Proceedings of the MICCAI Myopic Maculopathy Analysis Challenge 2023. Springer, 2023.
  48. Farazi M, Yang Z, Zhu W, Qiu P, Wang Y, TetCNN: Convolutional Neural Networks on Tetrahedral Meshes, Information Processing In Medical Imaging (IPMI), Jun. 2023 [Oral]
  49. Zhu W*, Qiu P*, Dumitrascu O, Sobczak J, Farazi M, Yang Z, Nandakumar K, Wang Y, OTRE: Where Optimal Transport Guided Unpaired Image-to-Image Translation Meets Regularization by Enhancing, Information Processing In Medical Imaging (IPMI), Jun. 2023
  50. Zhu W, Qiu P, Farazi M, Nandakumar K, Dumitrascu O, Wang Y, Optimal Transport Guided Unsupervised Learning for Enhancin Low-Quality Retinal Images, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Apr. 2023
  51. Fu Y, Huang Y, Dong S, Wang Y, Yu T, Niu M, Zhuo C, SFCNEXT: A Simple Fully Convolutional Network for Effective Brain Age Estimation with Small Sample Size, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Apr. 2023
  52. Xiong Y, Tu Y, Lu Z-L, Wang Y, Characterizing visual cortical magnification with topological smoothing and optimal transportation, SPIE Medical Imaging, Feb. 2023
  53. Farazi M, Zhu W, Yang Z, Wang Y, Anisotropic Multi-Scale Graph Convolutional Network for Dense Shape Correspondence, IEEE Winter Conference on Applications of Computer Vision (WACV), Jan. 2023
  54. Zhu W, Qiu P, Lepore N, Dumitrascu OM, Wang Y, Self-Supervised Equivariant Regularization Reconciles Multiple Instance Learning: Joint Referable Diabetic Retinopathy Classification and Lesion Segmentation, 18th International Symposium on Medical Information Processing and Analysis (SIPAIM). Campinas, Brazil. Nov., 2022.
  55. Fan D, Gajawelli N, Paulli A, Perry E, Tanedo J, Deoni S, Linguraru M, Wang Y, and Lepore N, NEC-NET : Segmentation and Feature Extraction Network for the Neurocranium in Early Childhood, 18th International Symposium on Medical Information Processing and Analysis (SIPAIM). Campinas, Brazil. Nov., 2022.
  56. Wu J, Su Y, Reiman EM, Caselli RJ, Chen K, Thompson PM, Wang J*, Wang Y*, Investigating the Effect of Tau Deposition and APOE on Hippocampal Morphometry in Alzheimer’s Disease: A Federated Chow Test Model, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Mar. 2022 [Oral]
  57. Fan Y, Wang Y, “Geometry-Aware Hierarchical Bayesian Learning on Manifolds,” IEEE Winter Conference on Applications of Computer Vision (WACV), Jan. 2022
  58. Wu J, Zhu W, Su Y, Gui J, Lepore N, Reiman EM, Caselli RJ, Thompson PM, Chen K, Wang Y, “Predicting Tau Accumulation in Cerebral Cortex with Multivariate MRI Morphometry Measurements, Sparse Coding, and Correntropy“, 17th International Symposium on Medical Information Processing and Analysis (SIPAIM), Campinas, Brazil, Nov. 2021
  59. Htite, ED., Gajawelli, N., Saint-Martin, C., Wei, M., Sarah, P., Wang, Y., Wintermark, P., Deoni, S., Lepore, N., Brossard-Racine, M. (2021). Altered hippocampal morphometry in infants born preterm. 17th International Symposium on Medical Information Processing and Analysis (SIPAIM). Campinas, Brazil. Nov., 2021. Platform Presentation. 
  60. Zhang M*, Guo Y*, Lei N, Zhao Z, Wu J, Xu X, Wang Y, Gu X, “Cortical Surface Shape Analysis based on Alexandrov Polyhedra“, IEEE International Conference on Computer Vision (ICCV), Virtual, Oct. 2021
  61. Yang Z, Wu J, Thompson PM, Wang Y, “Deep Learning on SDF for Classifying Brain Biomarkers“, 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Nov. 2021
  62. Tu Y, Ta D, Lu Z-L, Wang Y, “Topological Receptive Field Model for Human Retinotopic Mapping“, 24th International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI, Strasbourg, France, Oct. 2021
  63. Zhang M*, An D*, Lei N, Wu J, Zhao T, Xu Y, Wang Y, Gu X, Cortical Morphometry Analysis Based on Worst Transportation Theory, Information Processing In Medical Imaging (IPMI), Jun. 2021
  64. Wu J, Zhang J, Li Q, Su Y, Chen K, Reiman EM, Wang J, Lepore N, Ye J, Thompson PM, Wang Y, Patch-based surface morphometry feature selection with federated group lasso regression, 16th International Symposium on Medical Information Processing and Analysis (SIPAIM), Lima, Peru, Oct. 2020
  65. Mukherjee S Paquette N, Gajawelli N, Wang Y, Wallace J, Nelson MD, Panigrahy A, Lepore N, Deep-learning based tractography for neonates, 16th International Symposium on Medical Information Processing and Analysis (SIPAIM), Lima, Peru, Oct. 2020
  66. Fan Y, Wang Y, Convolutional Bayesian Models for Anatomical Landmarking on Multi-Dimensional Shapes, 23rd International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI, Lima, Peru, Oct. 2020
  67. Zhang W, Zhan L, Thompson PM, Wang, Y, “Deep Representation Learning For Multimodal Brain Networks“, 23rd International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI, Lima, Peru, Oct. 2020
  68. Tu Y, Ta D, Lu Z-L, Wang Y, “Optimizing Visual Cortex Parameterization with Error-Tolerant Teichmüller Map in Retinotopic Mapping“, 23rd International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI, Lima, Peru, Oct. 2020
  69. Tu Y, Ta D, Lu Z-L, Wang Y, “Diffeomorphic Smoothing for Retinotopic Mapping“, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Apr. 2020 [Oral] (Best Paper Award Finalist)
  70. Tu Y, Ta D, Gu X, Lu Z-L, Wang Y, “Diffeomorphic Registration for Retinotopic Mapping via Quasiconformal Mapping“, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Apr. 2020
  71. Zhang J, Wang Y, “Temporally Adaptive-Dynamic Sparse Network for Modeling Disease Progression“, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Apr. 2020
  72. Farazi M, Zhan L, Lepore N, Thompson PM, Wang Y, “A Univariate Persistent Brain Network Feature Based on the Aggregated Cost of Cycles from the Nested Filtration Networks“, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Apr. 2020
  73. Zhang W, Wang Y, “Deep Multimodal Brain Network Learning For Joint Analysis of Structural Morphometry and Functional Connectivity“, In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Apr. 2020
  74. Zhang J, Zhang J, Ghosh S, Li D, Zhu J, Zhang H, Wang Y, “Regularize, Expand and Compress: NonExpansive Continual Learning,”, IEEE Winter Conference on Applications of Computer Vision (WACV), Mar. 2020 [Oral]
  75. Mi L, Zhang W, Wang Y, “Regularized Wasserstein Means for Aligning Distributional Data“, 34th AAAI Conference on Artificial Intelligence (AAAI-20), Feb. 2020 [Oral]
  76. Mi L, Zhang W, Wang Y, “Regularized Wasserstein Means for Aligning Distributional Data”, Optimal Transport & Machine Learning, a NeurIPS 2019 Workshop, Vancouver, Dec. 2019
  77. Fan Y, Lepore N, Wang Y, “Morphometric Gaussian Process for Landmarking on Grey Matter Tetrahedral Models“, 15th International Symposium on Medical Information Processing and Analysis (SIPAIM), Medellin, Colombia, Nov. 2019 [Oral]
  78. Zhang J, Wang Y, “Continually Modeling Alzheimer’s Disease Progression via Deep Multi-Order Preserving Weight Consolidation“, 22nd International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI, Shenzhen, China, Oct. 2019
  79. Zhang W, Wang Y, “Geometric Brain Surface Network For Brain Cortical Parcellation“, 1st International Workshop on Graph Learning in Medical Image (GLMI), in Conjunction with MICCAI, Oct. 2019 [Oral]
  80. Wen C, Lei N, Ma M, Qi X, Zhang W, Wang Y, Gu X, “Surface Foliation Based Brain Morphometry Analysis“, 7th MICCAI Workshop on Mathematical Foundations of Computational Anatomy, in Conjunction with MICCAI, Oct. 2019 [Oral]
  81. Dong Q*, Zhang J*, Li Q, Thompson PM, Caselli RJ, Ye J, Wang Y, “Multi-task Dictionary Learning based Convolutional Neural Networks for Longitudinal Clinical Score Prediction in Alzheimer’s Disease“,  Joint Workshop on Human Brain and Artificial Intelligence, in Conjunction with IJCAI, Aug. 2019 [Oral]
  82. Zhang W, Mi L, Thompson PM, Wang Y, “A Geometric Framework for Feature Mappings in Multimodal Fusion of Brain Image Data“, Information Processing In Medical Imaging (IPMI), Jun. 2019
  83. Paquette, N., Suri A, Ganesh B, Tsao S, Gaonkar B, Wang Y, Nelson M, Panigrahy A, and Lepore N, “Neonaral Brain MRI Cortical Segmentation via Geodesic Transforms”, in IEEE International Symposium on Biomedical Imaging (ISBI). 2019, IEEE: Venice, Italy
  84. Mi L, Zhang W, Gu X, Wang Y, “Variational Wasserstein Clustering“, European Conference on Computer Vision (ECCV), Munich, Germany, Sep. 2018
  85. Fan Y, Wang G, Lepore N, Wang Y, “A Tetrahedron-Based Heat Flux Signature for Cortical Thickness Morphometry Analysis“, 21st International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI, Granada, Spain, Sep. 2018
  86. Zhang W, Shu K, Wang S, Liu H, Wang Y, “Multimodal Fusion of Brain Networks with Longitudinal Couplings“, 21st International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI, Granada, Spain, Sep. 2018
  87. Zhang J, Wang X, Li D, Wang Y, “Dynamically Hierarchy Revolution: DirNet for Compressing Recurrent Neural Network on Mobile Devices”, IJCAI-ECAI-18, 2018 [Oral]
  88. Tu Y, Wen C, Zhang W, Wu J, Zhang J, Chen K, Caselli RJ, Reiman EM, Gu X, Wang Y,  “Isometry Invariant Shape Descriptors for Abnormality Detection on Brain Surfaces Affected by Alzheimer’s Disease“, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018 [Oral]
  89. Wu J, Zhang J, Shi J, Chen K, Caselli RJ, Reiman EM, Wang Y, “Hippocampus Morphometry Study on Pathology-Confirmed Alzheimer’s Disease Patients with Surface Multivariate Morphometry Statistics“, In IEEE International Symposium on BIOMEDICAL IMAGING: From Nano to Macro (ISBI). 2018 [Oral]
  90. Zhang J, Tu Y, Li Q, Caselli RJ, Thompson PM, Ye J, Wang Y, “Multi-Task Sparse Screening for Predicting Future Clinical Scores Using Longitudinal Cortical Thickness Measures“, In IEEE International Symposium on BIOMEDICAL IMAGING: From Nano to Macro (ISBI). 2018
  91. Mi L, Zhang W, Zhang J, Fan Y, Goradia D, Chen K, Reiman EM, Gu X, Wang Y, “An Optimal Transportation based Univariate Neuroimaging Index“, IEEE International Conference on Computer Vision (ICCV), Venice, Italy, Oct. 2017
  92. Yu X, Lei N, Wang Y, Gu X, “Intrinsic 3D Dynamic Surface Tracking based on Dynamic Ricci Flow and Teichmuller Map“,  IEEE International Conference on Computer Vision (ICCV), Venice, Italy, Oct. 2017
  93. Singh S, Srivastava A, Mi L, Caselli RJ, Chen K, Goradia D, Reiman EM and Wang Y, “Deep Learning based Classification of FDG-PET Data for Alzheimer’s Disease Categories“, 13th International Symposium on Medical Information Processing and Analysis (SIPAIM), San Andres Island, Co.lombia, Oct. 2017 [Oral]
  94. Gajawelli N, Denoi S, Shi J, Dirks H, Linguraru MG, Nelson MD, Wang Y, Lepore N, Cranial Thickness Changes in Early Childhood, 13th International Symposium on Medical Information Processing and Analysis (SIPAIM), San Andres Island, Colombia, Oct. 2017
  95. Chou Z, Paquette N, Ganesh B, Wang Y, Ceschin R, Nelson MD, Macyszyn L, Gaonkar B, Panigrahy A, Lepore N, Bayesian automated cortical segmentation for neonatal MRI, Proc SPIE Int Soc Opt Eng, pp. 10572, 2017 
  96. Gajawelli N, Deoni S, Dirks H, Dean D, O’Muircheartaigh J, Wang Y, Nelson M, Coulon O, Lepore N, “Central Sulcus Development in Early Childhood“, the 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2017
  97. Vlasova R, Wang Y, Dirks H, Dean D, O’Muircheartaigh J, Gonzalez S, Nguyen BK, Nelson M, Deoni S, Lepore N, “Contribution to Speech Development of the Right Anterior  Putamen Revealed with Multivariate Tensor-based Morphometry“,the 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2017 
  98. Zhang J*, Li Q*, Caselli RJ, Thompson PM, Ye J, Wang Y, “Multi-Source Multi-Target Dictionary Learning for Prediction of Cognitive Decline“, In Information Processing In Medical Imaging (IPMI), 2017
  99. Zhang J, Fan Y, Li Q, Thompson PM, Ye J, Wang Y, “Empowering Cortical Thickness Measures in Clinical Diagnosis of Alzheimer’s Disease with Spherical Sparse Coding“, In IEEE International Symposium on BIOMEDICAL IMAGING: From Nano to Macro (ISBI). 2017 [Oral]
  100. Zhang W, Shi J, Yu J, Zhan L, Thompson PM, Wang Y, “Enhancing Diffusion MRI Measures by Integrating Grey and White Matter Morphometry with Hyperbolic Wasserstein Distance“, In IEEE International Symposium on BIOMEDICAL IMAGING: From Nano to Macro (ISBI). 2017
  101. Vlasova R, Gajawelli N, Wang Y, Dirks H, Dean D, O’Muircheataigh J, Lao Y, Yoon J, Nelson M D, Deoni S, Lepore N, “Putamen development in children 12 to 21 months old“, Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis (SIPAIM), Tandil, Argentina, Dec. 2016
  102. Chai, Y, Lao Y, Li Y, Ji C, O’Neil S, Wang Y, Lepore N, Wood J, “Multivariate surface-based analysis of corpus callosum in patients with sickle cell disease“, Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis (SIPAIM), Tandil, Argentina, Dec. 2016
  103. Zhang J, Shi J, Stonnington C, Li Q, Gutman BA, Chen K, Reiman EM, Caselli RJ, Thompson PM, Ye J, Wang Y, Hyperbolic Space Sparse Coding with Its Application on Prediction of Alzheimer’s Disease in Mild Cognitive Impairment, 19th International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI, Athens, Greece, Oct. 2016
  104. Li, Q, Yang T, Zhan, L, Hibar D, Jahanshad N, Wang Y, Ye J, Thompson PM, Wang J, “Large-scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer’s Disease Across Multiple Institutions“, 19th International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI, Athens, Greece, Oct. 2016
  105. Shi J, Zhang W, Wang Y, Shape Analysis with Hyperbolic Wasserstein Distance, In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2016, Las Vegas, NV.
  106. Zhang J, Stonnington C, Li Q, Shi J, Bauer III RJ, Gutman B, Chen K, Reiman EM, Thompson PM, Ye J, Wang Y, Applying sparse coding to surface multivariate tensor-based morphometry to predict future cognitive decline, In IEEE International Symposium on BIOMEDICAL IMAGING: From Nano to Macro (ISBI). 2016 [Oral]
  107. Zhang W, Shi J, Stonnington C, Bauer III RJ, Gutman B, Chen K, Thompson PM, Reiman EM, Caselli RJ, Wang Y, Morphometric Analysis of Hippocampus and Lateral Ventricle Reveals Regional Difference Between Cognitively Stable and Declining Persons, In IEEE International Symposium on BIOMEDICAL IMAGING: From Nano to Macro (ISBI). 2016. [Best Student Paper Award Finalist]
  108. Li Y, Wang J, Yang T, Chen J, Liu L, Zhan L, Hibar DP, Jahanshad N, Wang Y, Zhao S, Thompson PM, Ye J, “Identification of Alzheimer’s Disease Risk Factors by Tree-Structured Group Lasso Screening”, In IEEE International Symposium on BIOMEDICAL IMAGING: From Nano to Macro (ISBI). 2016.
  109. Shi J, Wang Y, Lao Y, Zeschin R, Mi L, Nelson MD, Panigrahy A, Leporé N, “Abnormal Ventricular Development in Preterm Neonates with Visually Normal MRIs”, 11th International Symposium on Medical Information Processing and Analysis (SIPAIM), Nov. 2015, Cuenca, Ecuador
  110. Gajawellia N, Deonic S, Shi J, Xu, L, Dirks, H, Dean D, O’Muircheartaigh, Sawardekar S, Ezis A, Nelson MD, Wang Y, Leporé N, “Changes in Neurocranium Thickness in Early Childhood”, 11th International Symposium on Medical Information Processing and Analysis (SIPAIM), Nov. 2015, Cuenca, Ecuador
  111. Wang G, Wang Y, “ Multi-scale Heat Kernel based Grey Matter Morphology Signature“, 18th International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI 2015, Munich Germany, Oct. 2015
  112. Ta D, Shi J, Barton B, Brewer A, Lu Z-L, Wang Y, “Characterizing Human Retinotopic Mapping with Conformal Geometry: Conformal Distortion Analysis”, the 8th International Workshop on High Performance Computing for Biomedical Image Analysis (HPC-MICCAI), 2015
  113. Su Z, Zeng W, Wang Y, Lu Z-L, Gu X, “ Shape Classification using Wasserstein Distance for Brain Morphometry Analysis“, Information Processing in Medical Imaging, International Conference (IPMI), Proceedings, pp. 411-423, Isle Of Skye, Scotland, June, 2015
  114. Gajawelli N, Deoni SCL, Dirks H, Dean D, O’Muircheartaigh J, Sawardekar S, Ezis A, Wang Y, Nelson M, Coulon O, Leporé N, “Characterization of the central sulcus in the brain in early childhood”, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milano, Italy, Aug. 2015.
  115. Yang T, Wang J, Sun Q, Hibar DP, Jahanshad N, Liu L, Wang Y, Zhan L, Thompson PM, Ye J, “Detecting Genetic Risk Factors for Alzheimer’s Disease in Whole Genome Sequence Data via Lasso Screening.” In IEEE International Symposium on BIOMEDICAL IMAGING: From Nano to Macro. 2015.
  116. Wade BSC, Valcour V, Wendelken-Riegelhaup L, Esmaeili-Firidouni P, Joshi SH, Wang Y, Thompson PM , “Mapping Abnormal Subcortical Brain Morphometry In An Elderly HIV+ Cohort”, In IEEE International Symposium on BIOMEDICAL IMAGING: From Nano to Macro. 2015.
  117. Gutman B, Jahanshad N, Ching CRK, Wang Y, Kochunov P, Nichols T, Thompson PM, “Medial Demons Registration Localizes the Degree of Genetic Influence over Subcortical Shape Variability: An N=1480 Meta-Analysis”, In IEEE International Symposium on BIOMEDICAL IMAGING: From Nano to Macro. 2015.
  118. Wade BSC, Valcour V, Busovaca E, Esmaeli-Firidouni P, Joshi SH, Wang Y, Thompson PM, “Subcortical shape and volume abnormalities in an elderly HIV+ cohort”, SPIE, Medical Imaging, 2015
  119. Lao Y, Law M, Shi J, Gajawelli N, Haas L, Wang Y and Leporé N, “A T1 and DTI fused 3D Corpus Callosum analysis in pre- vs. post-season contact sports players“, 10th International Symposium on Medical Information Processing and Analysis (SIPAIM), Oct. 2014, Cartagena,Colombia
  120. Shi J, Stonnington CM, Thompson PM, Chen K, Gutman BA, Reschke C, Baxter LC, Reiman EM, Caselli RJ, Wang Y, ADNI Group, “Hyperbolic Ricci Flow and Geodesic Curve Lifting for Consistent Ventricular Surface Registration“, the 7th International Workshop on High Performance Computing for Biomedical Image Analysis (HPC-MICCAI), 2014
  121. Zhan L, Nie Z, Ye J, Wang Y, Jin Y, Jahanshad N, Prasad G, de Zubicaray GI, McMahon KL, Martin NG, Wright MJ, Thompson PM, “Multiple stages classification of Alzheimers disease based on structural brain networks using Generalized Low Rank Approximations (GLRAM)“, MICCAI 2014 Workshop on Computational Diffusion MRI (CDMRI14), 2014
  122. Ta D, Shi J, Barton B, Brewer A, Lu Z-L, Wang Y, “Characterizing Human Retinotopic Mapping with Conformal Geometry: A Preliminary Study“, SPIE, Medical Imaging, 2014
  123. Lao Y, Gajawelli N, Hass L, Wilkins B, Hwang D, Tsao S, Wang Y Law M, Leporé N “3D pre- versus post-season comparisons of surface and relative pose of the corpus callosum in contact sport athletes“, SPIE, Medical Imaging, 2014
  124. Yepes-Calderon F, Pedregosa F, Thirion B, Wang Y*, Leporé N*, “Automatic Pathology Detection by Means of Stored Data Using Machine-Learning Support Vector Machines“, SPIE, Medical Imaging, 2014
  125. Tsao S, Gajawelli N, Zhou J, Shi J, Ye J, Wang Y, Leporé N, “Evaluating the Predictive Power of Multivariate Tensor-based Morphometry in Alzheimer’s Disease Progression via Convex Fused Sparse Group Lasso“, SPIE, Medical Imaging, 2014
  126. Xu L, Collignon O, Wang G, Kang Y, Leporé F, Shi J, Lao Y, Joshi A, Leporé N*, Wang Y*, “Combining Thickness Information with Surface Tensor-based Morphometry for the 3D Statistical Analysis of the Corpus Callosum“, the 4th MICCAI Workshop on Mathematical Foundations of Computational Anatomy (MFCA), 2013.
  127. Joshi S, Shi J, Wang Y, Narr K, Toga A, Woods R, “Surface Shape Matching and Analysis using Intrinsic Coordinate Parameterizations“, the 4th MICCAI Workshop on Mathematical Foundations of Computational Anatomy (MFCA). 2013
  128. Lao Y, Shi J, Wang Y, Ceschin R, Hwang D, Nelson MD, Panigrahy A, Leporé N, “Statistical Analysis of Relative Pose of the Thalamus in Preterm Neonates“, MICCAI workshop on CLinical Imagebased Procedures (CLIP 2013): Translational Research in Medical Imaging. 2013.
  129. Wang G, Zhang X, Su Q, Chen J, Wang L, Ma Y, Liu Q, Xu L, Shi J, Wang Y, “A Heat Kernel based Cortical Thickness Estimation Algorithm“, the 3rd MICCAI Workshop on Multimodal Brain Image Analysis (MBIA), 2013.
  130. Xiang S, Yuan L, Fan W, Wang Y, Thompson PM, Ye J, “ Multi-Source Learning with Block-wise Missing Data For Alzheimer’s Disease Prediction“, The 19th ACM SIGKDD International Conference On Knowledge Discovery and Data Mining (SIGKDD 2013), pp. 185-193, (Full Presentation)
  131. Shi R, Zeng W, Su Z, Damasio H, Lu Z, Wang Y, Yau S.-T. Gu X, Hyperbolic Harmonic Mapping for Constrained Brain Registration, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2531-2538, Portland, Oregan, June, 2013 [Oral]
  132. Su Z, Zeng W, Shi R, Wang Y, Sun J, Gu X, Area Preserving Brain Mapping, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2235-2242, Portland, Oregan, June, 2013
  133. Shi R, Zeng W, Su Z, Wang Y, Damasio H, Lu Z, Yau S.-T. Gu X, Hyperbolic Harmonic Brain Surface Registration with Curvature-based Landmark Matching, Information Processing in Medical Imaging, 23rd International Conference (IPMI), Proceedings, pp. 159-170, Asilomar, CA, June, 2013
  134. Shi J, Wang Y, Ceschin R, An X, Nelson MD, Panigrahy A, Leporé N , Surface Fluid Registration and Multivariate Tensor-based Morphometry in NewBorns – the Effects of Prematurity on the Putamen, Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Hollywood, CA, Dec. 2012
  135. Shi J, Thompson PM, Wang Y, Hyperbolic Ricci Flow and Its Application in Studying Lateral Ventricle Morphometry, MICCAI Workshop: International Workshop on Multimodal Brain Image Analysis (MBIA), Nice, France, Oct. 2012
  136. An X, Liu Z, Shi Y, Li N, Wang Y, Joshi S, “Modeling Dynamic Cellular Morphology in Images”, the 15th International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI 2012, Nice, France, Oct. 2012, Proceedings, Part I. pp. 340-347
  137. Wang Y, Panigrahy A, Shi J, Ceschin R, Nie Z, Nelson MD, Leporé N, “3D vs. 2D Surface Shape Analysis of the Corpus Collosum in Premature Neonates”, MICCAI: Workshop on Paediatric and Perinatal Imaging, Nice, France, Oct. 2012
  138. Zhan L, Wang Y, Thompson PM, “Registration of Spherical Functions from High Angular Resolution Diffusion Imaging using the Heat Kernel Signature and Möbius Transformation”, MICCAI: Workshop on Computational Diffusion MRI”, Nice, France, Oct. 2012 (Oral)
  139. Yuan L, Wang Y, Thompson PM, Narayan VA, Ye J, “Multi-Source Learning for Joint Analysis of Incomplete Multi-Modality Neuroimaging Data”, accepted by The 18th ACM SIGKDD International Conference On Knowledge Discovery and Data Mining (SIGKDD 2012), (Full Presentation)
  140. Nandakumar V, An X, Wang Y, Johnson R, Meldrum D, “Conformal Mapping of Nuclei in 3D Tomographic Cell Images to Assess Shape Heterogeneity”, IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Barcelona, Spain, 2012, pp. 222-225
  141. Gutman B, Wang Y, Rajagopalan P, Toga AW, Thompson PM, “Shape Matching with Medial Curves and 1-D Group-Wise Registration”, IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Barcelona, Spain, 2012, pp. 716-719
  142. Shi J, Thompson PM, Wang Y, “Human Brain Mapping with Conformal Geometry and Multivariate Tensor-based Morphometry”, MICCAI Workshop: International Workshop on Multimodal Brain Image Analysis (MBIA), 2011:Toronto, Canada. (Invited Paper)
  143. Wang Y, Panigrahy A, Shi J, Ceschin R, Nelson MD, Gutman B, Thompson PM, Leporé, N, “Surface Multivariate Tensor-based Morphometry on Premature Neonates: A Pilot Study”, MICCAI Workshop: Image Analysis of Human Brain Development (IAHBD), 2011:Toronto, Canada.
  144. Shi J, Wang Y, Thompson PM, Wang Y, “Hippocampal Morphometry Study by Automated Surface Fluid Registration and Its Application to Alzheimer’s Disease”, 3rd MICCAI Workshop on Mathematical Foundations of Computational Anatomy (MFCA), 2011:Toronto, Canada.
  145. Zeng W, Shi R, Wang Y, Gu X, “Teichmüller Shape Descriptor and Its Application to Alzheimer’s Disease Study”, 3rd MICCAI Workshop on Mathematical Foundations of Computational Anatomy (MFCA), 2011:Toronto, Canada.
  146. Wang Y, Chan TF, Toga AW, Thompson PM, “Shape Analysis with Multivariate Tensor-based Morphometry and Holomorphic Differentials”, 12th IEEE International Conference on Computer Vision (ICCV), Kyoto, Japan, Sep. 2009, pp. 2349-2456
  147. Wang Y, Dai W, Chou Y, Gu X, Chan TF, Toga AW, Thompson PM, “Studying Brain Morphometry using Conformal Equivalence Class”, 12th IEEE International Conference on Computer Vision (ICCV), Kyoto, Japan, Sep. 2009, pp. 2365-2372
  148. Wang Y, Chan TF, Toga AW, Thompson PM, “Multivariate Tensor-based Brain Anatomical Surface Morphometry via Holomorphic One-Forms”, 12th International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI 2009, London, UK, Sep. 2009, pp. 337-344
  149. Wang Y, Dai W, Gu X, Chan TF, Yau S-T, Toga AW, Thompson PM, “Teichmüller Shape Space Theory and Its Application to Brain Morphometry”, 12th International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI 2009, London, UK, Sep. 2009, pp. 133-140
  150. Wang Y, Gu X, Chan TF, Thompson PM , “Shape Analysis with Conformal Invariants for Multiply Connected Domains and its Application to Analyzing Brain Morphology”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Miami Beach, FL, USA, Jun. 2009, pp. 202-209
  151. Wang Y, Zhang J, Chan TF, Toga AW, Thompson PM , “ Multivariate Tensor-based Morphometry on Surfaces: Application to Mapping Ventricular Changes in HIV/AIDS“, IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Boston, MA, USA, 2009, pp. 129-132
  152. Dong B, Mao Y, Dinov ID, Tu Z, Shi Y,Wang Y, Toga AW, “Wavelet-Based Representation of Biological Shapes“, International Symposium on Visual Computing (ISVC), Part I, Las Vegas, NV, USA, 2009, pp. 955-964
  153. Wang Y, Gu X, Chan TF, Thompson PM, Yau S-T, “Conformal Slit Mapping and Its Applications to Brain Surface Parameterization“, International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI 2008, LNCS 5241, pp. 585-593
  154. Wang Y, Gu X, Chan TF, Thompson PM, Yau S-T, “ Brain surface conformal parameterization with the slit mapping, IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Paris, France, 2008, pp. 448-451
  155. Wang Y, Yin X, Zhang J, Gu X, Chan TF, Thompson PM, Yau S-T, Brain Mapping with the Ricci Flow Conformal Parameterization and Multivariate Statistics on Deformation Tensors, 2nd MICCAI Workshop on Mathematical Foundations of Computational Anatomy, pp. 36-47, 2008
  156. Lui LM, Thiruvenkadam S, Wang Y, Chan TF, Thompson PM, Optimized Conformal Parameterization of Cortical Surfaces Using Shape Based Matching of Landmark Curves, International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI 2008, LNCS 5241, pp. 494-502
  157. Gutman B, Wang Y, Chan TF, Thompson PM, Toga AW, Shape Registration with Spherical Cross Correlation, 2nd MICCAI Workshop on Mathematical Foundations of Computational Anatomy, pp. 56-67
  158. Gutman B, Wang Y, Morra J, Thompson PM, Toga AW, Disease Classification with Hippocampal Shape Invariants, MICCAI 2008 Workshop on the Computational Anatomy and Physiology of the Hippocampus, pp. 76-86
  159. Wang Y, Gu X, Chan TF, Thompson PM and Yau S-T, “ Brain Surface Conformal Parameterization with the Ricci Flow“, IEEE International Symposium on Biomedical Imaging – From Nano to Macro (ISBI), Washington D.C., USA, 2007, pp. 1312-1315
  160. Gutman B, Wang Y, Lui LM, Chan TF, Thompson PM, “ Hippocampal Surface Discrimination via Invariant Descriptors of Spherical Conformal Maps“, IEEE International Symposium on Biomedical Imaging – From Nano to Macro (ISBI), Washington D.C., USA, 2007, pp. 1316-1319
  161. Wang Y, Gu X, Chan TF, Toga AW, Thompson PM and Yau S-T, “Brain Surface Conformal Parameterization with Algebraic Functions“, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2006, LNCS 4191, pp. 946-954
  162. Lui LM, Wang Y, Chan TF, and Thompson PM, “ A Landmark-based Brain Conformal Parametrization with Automatic Landmark Tracking Technique“, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2006, LNCS 4191, pp. 308-316
  163. Gutman B, Wang Y, Lui LM, Chan TF, and Thompson PM , “ Hippocampal Surface Analysis Using Spherical Harmonic Function Applied to Surface Conformal Mapping “, 8th International Conference on Pattern Recognition (ICPR), Hong Kong, China, 2006, Vol. 3, pp. 964-967
  164. Lui LM, Wang Y, Chan TF and Thompson PM, “Automatic Landmark Tracking and Its Application to the Optimization of Brain Conformal Mapping“, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), New York, NY, Jun. 2006, Vol. 2, pp. 1784-1792
  165. Lui LM, Wang Y, Chan TF and Thompson PM, “Automatic Landmark Tracking Applied to Optimize Brain Conformal Mapping“, IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Arlington, VA, Apr. 2006, pp. 205-208
  166. Wang Y, Jo I, Wong S, Yau S-T, Chan TF, “ Segmentation and Tracking of 3D Neuron Microscopy Images using a PDE based Method and Connected Component Labeling Algorithm“, Life Science Systems and Applications Workshop, IEEE/NLM, Bethesda, MD, USA, Jul. 2006, pp. 72-73
  167. Wang Y, Chiang M-C, and Thompson PM, “Mutual Information-based 3D Surface Matching with Applications to Face Recognition and Brain Mapping“, 10th IEEE International Conference on Computer Vision (ICCV), Beijing, China, Oct. 2005, pp. 527-534
  168. Wang Y, Gu X, Hayashi KM, Chan TF, Thompson PM and Yau S-T, “Surface Parameterization using Riemann Surface Structure“, 10th IEEE International Conference on Computer Vision (ICCV), Beijing, China, Oct. 2005, pp. 1061-1066
  169. Lui LM, Wang Y, Chan TF, “ PDE on manifold using global conformal parametrization“, Variational, Geometric, and Level Set Methods in Computer Vision: Third International Workshop, VLSM 2005, Beijing, China, Oct. 16, 2005, pp. 307-319
  170. Wang Y, Chiang M-C, and Thompson PM, “Automated Surface Matching using Mutual Information Applied to Riemann Surface Structures“, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005: 8th International Conference, Palm Springs, CA, USA, Oct. 26-29, 2005, Proceedings, Part II, pp. 666-674
  171. Wang Y, Gu X, Hayashi KM, Chan TF, Thompson PM and Yau S-T, “Brain Surface Parameterization using Riemann Surface Structure“, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005: 8th International Conference, Palm Springs, CA, USA, Oct. 26-29, 2005, Proceedings, Part II, pp. 657-665
  172. Wang Y, Lui LM, Chan TF and Thompson PM, “Optimization of Brain Conformal Mapping with Landmarks“, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005: 8th International Conference, Palm Springs, CA USA, Oct. 26-29, 2005, Proceedings, Part II, pp. 675-683
  173. Wang Y, Chiang M-C, and Thompson PM, “3D Surface Matching with Mutual Information and Riemann Surface Structures“, Proceedings of the Eighth IASTED International Conference on Computer Graphics and Imaging (CGIM), Honolulu, HI, USA, Aug. 2005, pp. 94-99
  174. Wang Y, Gu X, Hayashi KM, Chan TF, Thompson PM and Yau S-T, “Brain Surface Conformal Parameterization“, Proceedings of the Eighth IASTED International Conference on Computer Graphics and Imaging (CGIM), Honolulu, HI, USA, Aug. 2005, pp. 76-81
  175. Wang Y, Lui LM, Chan TF and Thompson PM, “Combination of Brain Conformal Mapping and Landmarks: A Variational Approach“, Proceedings of the Eighth IASTED International Conference on Computer Graphics and Imaging (CGIM), Honolulu, HI, USA, Aug. 2005, pp. 70-75
  176. Jin M, Wang Y, Yau S-T and Gu X, “Optimal Global Conformal Surface Parameterization for Visualization“, IEEE Visualization, Austin, TX, Oct. 2004, pp. 267-274
  177. Wang Y, Gu X, Chan TF, Thompson PM and Yau S-T “ Volumetric Harmonic Brain Mapping“, IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), Washington D.C., Apr. 2004, pp. 1275-1278
  178. Wang Y, Gu X, Chan TF, Thompson PM and Yau S-T, “ Intrinsic Brain Surface Conformal Mapping using a Variational Method“, Medical Imaging 2004: Image Processing, J. M. Fitzpatrick and M. Sonka (Eds.) Proceedings of SPIE, Vol. 5370, 2004, pp. 241-252
  179. Gu X, Wang Y, Chan TF, Thompson PM and Yau S-T, “ Genus Zero Surface Conformal Mapping and Its Application to Brain Surface Mapping“, C. Taylor and J. Alison Noble (Eds.), Information Processing in Medical Imaging,18th International Conference, IPMI 2003, Ambleside, UK, July 2003. Proceedings, pp. 172-184
  180. Gu X, Wang Y, and Yau S-T, “ Multiresolution Computation of Conformal Structures of Surfaces“, International Conference on Computer, Communication and Control Technologies: CCCT ’03. This paper won the best paper award in the session: Computing Technologies. 
  181. Wang Y, Phillips IT and Haralick RM, “ A Study on the Document Zone Content Classification Problem“, D. Lopresti, Hu J, and R. Kashi (Eds.), Document Image Analysis System V, 5th International Workshop DAS 2002, Princeton, NJ, USA, Aug. 2002. Proceedings, pp. 212 – 223.
  182. Wang Y and Hu J, “ Detecting Tables in HTML Documents“, D. Lopresti, Hu J, and R. Kashi (Eds.), Document Image Analysis System V, 5th International Workshop DAS 2002, Princeton, NJ, USA, Aug. 2002. Proceedings, pp. 249 – 260. This paper won the best student paper award.
  183. Wang Y, Phillips IT and Haralick RM, “ Table Detection Via Probability Optimization“, D. Lopresti, Hu J, and R. Kashi (Eds.), Document Image Analysis System V, 5th International Workshop DAS 2002, Princeton, NJ, USA, Aug. 2002. Proceedings, pp. 272 – 282.
  184. Wang Y, Phillips IT and Haralick RM, “ A Method for Document Zone Content Classification“, 16th International Conference on Pattern Recognition, ICPR2002, Vol. 3, pp. 196 – 199, Quebec City, Canada, Aug. 2002.
  185. Wang Y and Hu J “ A Machine Learning Based Approach for Table Detection on The Web“, The Eleventh International World Web Conference, WWW2002, pp. 242-250, Hawaii, USA, May 2002.
  186. Wang Y, Phillips IT and Haralick RM, “ Automatic Table Ground Truth Generation and A Background-analysis-based Table Structure Extraction Method“, Sixth International Conference on Document Analysis and Recognition , pp. 528-532, Seattle, Washington, U.S.A. Sep. 10-13, 2001. A web pagewas created as a supplement for it.
  187. Wang Y, Haralick RM and Phillips IT, “ Zone Content Classification and Its Performance Evaluation“, Sixth International Conference on Document Analysis and Recognition , pp. 540-544, Seattle, Washington, U.S.A. Sep. 10-13, 2001
  188. Wang Y, Phillips IT and Haralick RM, “ Using Area Voronoi Tessellation to Segment Characters Connected to Graphics“, Workshop on Graphics Recognition (GREC2001), Kingston, Ontario, Canada. Sep. 2001
  189. Wang Y, Phillips IT and Haralick RM, “ Random Table and Its Ground Truth Automatic Generation: A Tool for Table Understanding Research“, Workshop on Document Layout Interpretation and its Applications (DLIA2001), Seattle, Washington, U.S.A. Sep. 2001
  190. Wang Y, Haralick RM and Phillips IT, “Improvement of Zone Content Classification by Using Background Analysis“, Fourth IAPR International Workshop on Document Analysis Systems, Rio de Janeiro, Brazil, 10-13 December, 2000
  191. Wang Y, Phillips IT and Haralick RM, “ Statistical-based Approach to Word Segmentation“, 15th International Conference on Pattern Recognition, ICPR2000, Vol. 4, pp.555-558, Barcelona, Spain, September 2000.
  192. Aksoy S, Ye M, Schauf ML, Song M, Wang Y, Haralick RM, and et al., “Algorithm Performance Contest“, 15th International Conference on Pattern Recognition, ICPR 2000, vol. 4, pp. 870-876. Barcelona, Spain, Sep. 2000.
  193. Wang Y, Phillips IT and Haralick RM, “ From Image to SGML/XML Representation: One Method“, International Workshop on Document Layout Interpretation and Its Applications (DLIA’99), Bangalore, India, September 1999
  194. Wang Y, Tang L, etc. “ A New Method to Recognize Dimension Set and its Application in Architectural Engineering Drawings“, Fifth International Conference on Computer Aided Design and Computer Graphics, Dec. 2~5, 1997, Shenzhen China