Professor Yalin Wang joined School of Computing and Augmented Intelligence (SCAI) at Arizona State University in 2010. He took his postdoctoral training in mathematics and neuroimaging at University of California, Los Angeles. He was promoted to associate professor in 2017 and full professor in 2023. He received the “2016 Best Junior Faculty Researcher Award” from ASU CIDSE. He received multiple Best Paper and Best Paper Finalist awards. He has published more than 200 peer-reviewed journal and conference papers. Dr. Wang's research interests include medical imaging, computer vision, machine learning, computer graphics, geometric modeling, and statistical pattern recognition.
Education
PhD Electrical Engineering, University of Washington 2002
Zhang J, Dong Q, Shi J, Li Q, Stonnington CY, Gutman BA, Chen K, Reiman EM, Caselli RJ, Thompson PM, Ye J, Wang Y, Predicting Future Cognitive Decline with Hyperbolic Stochastic Coding, Medical Image Analysis, 2021, In Press.
Stonnington CM, Wu J, Zhang J, Shi J, Bauer III RJ, Devadas V, Su Y, Locke DEC, Reiman EM, Caselli RJ, Chen K, Wang Y, Improved prediction of imminent progression to clinically significant memory decline using surface multivariate morphometry statistics and sparse coding, Journal of Alzheimer's Disease, 2021, In Press
Wang G, Dong Q, Wu J, Su Y, Chen K, Su Q, Zhang X, Hao J, Yao T, Liu L, Zhang C, Caselli RJ, Reiman EM, Wang Y, Developing Univariate Neurodegeneration Biomarkers with Low-Rank and Sparse Subspace Decomposition, Medical Image Analysis, 2021, 67:101877
Dong Q*, Zhang W*, Stonnington CM, Wu J, Gutman BA, Chen K, Su Y, Baxter LC, Thompson PM, Reiman EM, Caselli RJ, Wang Y, Applying Surface-Based Morphometry to Study Ventricular Abnormalities of Cognitively Unimpaired Subjects Prior to Clinically Significant Memory Decline, NeuroImage: Clinical, 2020, 27:102338
Kuang L, Jia J, Zhao D, Xiong F, Han X, Wang Y, Default Mode Network Analysis of APOE Genotype in Cognitively Unimpaired Subjects Based on Persistent Homology, Frontiers in Aging Neuroscience, 2020, 12:188
Dong Q*, Zhang J*, Li Q, Wang J, Lepore N, Thompson PM, Caselli RJ, Ye J, Wang Y, Integrating Convolutional Neural Networks and Multi-Task Dictionary Learning for Cognitive Decline Prediction with Longitudinal Images, Journal of Alzheimer's Disease, 2020, 75(3): 971-992
Tu Y*, Mi L*, Zhang W, Zhang H, Zhang J, Fan Y, Goradia D, Chen K, Caselli RJ, Reiman EM, Gu X, Wang Y, ADNI Group, Computing Univariate Neurodegenerative Biomarkers with Volumetric Optimal Transportation: A Pilot Study, Neuroinformatics, 2020, 18(4): 531-548
Shi J, Wang Y, Hyperbolic Wasserstein Distance for Shape Indexing, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, 42(6): 1362-1376
Dong Q*, Zhang W*, Wu J, Li B, Schron EH, McMahon T, Shi J, Gutman BA, Chen K, Baxter LC, Thompson PM, Reiman EM, Caselli RJ, Wang Y, Applying Surface-Based Hippocampal Morphometry to Study APOE-e4 Allele Dose Effects in Cognitively Unimpaired Subjects, NeuroImage: Clinical, Mar. 2019, 22:101744
Kuang L, Han X, Chen K, Caselli RJ, Reiman EM, Wang Y, A Concise and Persistent Feature to Study Brain Resting-State Network Dynamics: Findings from the Alzheimer’s Disease Neuroimaging Initiative, Human Brain Mapping, 40(4), Mar. 2019, pp. 1062-1081
Wang G, Wang Y, Towards a Holistic Cortical Thickness Descriptor: Heat Kernel-Based Grey Matter Morphology Signatures, NeuroImage, 147, Feb. 2017, pp. 360-380.
Shi J, Zhang W, Tang M, Caselli RJ, Wang Y, Conformal Invariants for Multiply Connected Surfaces: Application to Landmark Curve-Based Brain Morphometry Analysis, Medical Image Analysis, 35, Jan. 2017, pp. 517-529.
Li B, Shi J, Gutman BA, Baxter LC, Thompson PM, Caselli RJ, Wang Y, Influence of APOE Genotype on Hippocampal Atrophy over Time - An N=1925 Surface-based ADNI Study, PLOS ONE 11(4), e0152901, 2016.
Wang G, Zhang X, Su Q, Shi J, Caselli RJ, Wang Y, A Novel Cortical Thickness Estimation Method based on Volumetric Laplace-Beltrami Operator and Heat Kernel, Medical Image Analys
Shi J, Stonnington CM, Thompson PM, Chen K, Gutman BA, Reschke C, Baxter LC, Reiman EM, Caselli RJ, Wang Y, Studying Ventricular Abnormalities in Mild Cognitive Impairment with Hyperbolic Ricci Flow and Tensor-based Morphometry, NeuroImage, 104(1), Jan. 2015, pp. 1-20.is, 22(1), Feb. 2015, pp. 1-20.
Shi J, Leporé N, Gutman B, Thompson PM, Baxter LC, Caselli RJ, Wang Y, Genetic Influence of APOE4 Genotype on Hippocampal Morphometry ‒ An N=725 Surface-based Alzheimer's Disease Neuroimaging Inituative Study, Human Brain Mapping, 35(8), Aug. 2014, pp. 3903-3918.
Shi J, Thompson PM, Gutman B, Wang Y, Surface Fluid Registration of Conformal Representation: Application to Detect Disease Burden and Genetic Influence on Hippocampus, NeuroImage, 78, Sep. 2013, pp. 111-134.
Wang Y, Yuan L, Shi J, Greve A, Ye J, Toga AW, Reiss AL, Thompson PM, Applying Tensor-based Morphometry to Parametric Surfaces can Improve MRI-based Disease Diagnosis, NeuroImage, 74, July 2013, pp. 209-230.
Wang Y, Shi J, Yin X, Gu X, Chan TF, Yau S.-T., Toga AW, Thompson PM, Brain Surface Conformal Parameterizaiton with the Ricci flow, IEEE Transaction on Medical Imaging, Vol 31, No. 2, Feb. 2012, pp. 251-264.
Wang Y, Song Y, Rajagopalan P, An T, Liu K, Chou Y, Gutman B, Toga AW, Thompson PM, Surface-based TBM Boosts Power to Detect Disease Effects on the Brain: An N=804 ADNI Study, NeuroImage, 56(4), June 2011, pp. 1993-2010
Wang Y, Zhang J, Gutman B, Chan TF, Becker JT, Aizenstein HJ, Lopez OL, Tamburo RJ, Toga AW, Thompson PM, Multivariate Tensor-based Morphometry on Surfaces: Application to Mapping Ventricular Abnormalities in HIV/AIDS, NeuroImage, 49(3), February 2010, pp. 2141-2157
Wang Y, Lui LM, Gu X, Hayashi KM, Chan TF, Toga AW, Thompson PM and Yau S-T, Brain Surface Conformal Parameterization using Riemann Surface Structure, IEEE Transaction on Medical Imaging, Vol. 26, No. 6, June 2007, pp. 853-865.
Gu X, Wang Y, Chan TF, Thompson PM and Yau S-T, " Genus Zero Surface Conformal Mapping and Its Application to Brain Surface Mapping", IEEE Transaction on Medical Imaging, 23(8), Aug. 2004, pp. 949-958
Research Activity
MRI Biomarker Discovery for Preclinical Alzheimers disease with Geometry Methods. HHS-NIH-NIA(7/15/2013 - 6/30/2016).
Collaborative Research: Quantifying Human Retinotopic Mapping by Conformal Geometry. NSF-MPS-DMS(7/1/2014 - 6/30/2017).
III: Small: Multi-modal Neuroimaging Data Fusion and Analysis with Harmonic Maps Under Designed Riemannian Metric. NSF-CISE-IIS(8/1/2014 - 7/31/2017).
ENIGMA Center for Worldwide Medicine, Imaging & Genomics. HHS-NIH-NIBIB(9/29/2014-5/31/2018).
Empowering Diffusion MRI Measures by Integrating White and Grey Matter Morphology. HHS-NIH-NIA(9/1/2015-4/30/2018).
Multi-Source Sparse Learning to Identify MCI and Predict decline. HHS-NIH-NIA(6/1/2016-5/31/2020).
Predicting the Early Childhood Outcomes of Preterm Brain Shape Abnormalities. HHS-NIH-NIBIB(9/22/2017-6/30/2021).
Modeling Multi-modal Neuroimaging Biomarkers in the SVRIII Cohort in Relationship to Differential Genetic Risk for Late-Onset Alzheimers Disease. HHS-NIH-NHLBI(9/15/2018-4/30/2019)
