# overview
Shuiwang Ji is currently an Associate Professor in the Department of Computer Science & Engineering, Texas A&M University, leading the Data Integration, Visualization, and Exploration (DIVE) Laboratory. Ji received the Ph.D. degree in Computer Science from Arizona State University in 2010, advised by Prof. Jieping Ye. His research interests include machine learning, data mining, and computational neuroscience. Ji received the National Science Foundation CAREER Award in 2014. He has authored over 80 research articles and has coauthored a book. Currently, Ji serves as an Action Editor for Data Mining and Knowledge Discovery, and an Associate Editor for ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Neural Networks and Learning Systems, and BMC Bioinformatics. Ji is a Program Chair for the 2017 Bioimage Informatics Conference and a senior member of IEEE.

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4603 Computer Vision And Multimedia Computation

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4607 Graphics, Augmented Reality And Games

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Networking And Information Technology R&d (nitrd)

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3102 Bioinformatics And Computational Biology

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Networking And Information Technology R&d (nitrd)

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3404 Medicinal And Biomolecular Chemistry

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Networking And Information Technology R&d

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Networking And Information Technology R&d

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4009 Electronics, Sensors And Digital Hardware

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Networking And Information Technology R&d

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1.1 Normal Biological Development And Functioning

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5 Development Of Treatments And Therapeutic Interventions

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Gene Expression Pattern Image Annotation

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Alzheimer's Disease Including Alzheimer's Disease Related Dementias (ad/adrd)

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Networking And Information Technology R&d

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Networking And Information Technology R&d

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3102 Bioinformatics And Computational Biology

# educationAndTraining[].organization.label
Arizona State University - (Tempe, Arizona, United States)

# awardsAndHonors[].label
Enhancing Development and Generating Excellence in Scholarship (EDGES) Fellow

# publications[].label
FlowX: Towards Explainable Graph Neural Networks via Message Flows.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Structural Graphical Lasso for Learning Mouse Brain Connectivity

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Interpreting Image Classifiers by Generating Discrete Masks.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis

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Neuronal Activities in the Mouse Visual Cortex Predict Patterns of Sensory Stimuli.

# publications[].label
Efficient and Invariant Convolutional Neural Networks for Dense Prediction

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Smoothed Dilated Convolutions for Improved Dense Prediction

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Deep Convolutional Neural Networks for Multi-Instance Multi-Task Learning

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Learning Convolutional Text Representations for Visual Question Answering

# publications[].publisher
Society for Industrial and Applied Mathematics

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Hypergraph spectral learning for multi-label classification

# publications[].publisher
Association for Computing Machinery (ACM)

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Discriminant sparse neighborhood preserving embedding for face recognition

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3D convolutional neural networks for human action recognition

# publications[].label
Adversarial Attacks and Defenses on Graphs

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
A least squares formulation for a class of generalized eigenvalue problems in machine learning

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
BigNeuron: A resource to benchmark and predict best-performing algorithms for automated reconstruction of neuronal morphology

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Automated gene expression pattern annotation in the mouse brain.

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Deep Low-Shot Learning for Biological Image Classification and Visualization From Limited Training Samples.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Parallel Lasso Screening for Big Data Optimization

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
GraphEBM: Molecular Graph Generation with Energy-Based Models

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Multi-Modality Disease Modeling via Collective Deep Matrix Factorization

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].publisher
Association for Computing Machinery (ACM)

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Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns.

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A deep transfer learning approach for improved post-traumatic stress disorder diagnosis

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Canonical correlation analysis for multilabel classification: a least-squares formulation, extensions, and analysis.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Graph Representation Learning via Hard and Channel-Wise Attention Networks

# publications[].publisher
Association for Computing Machinery (ACM)

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Spherical Message Passing for 3D Graph Networks

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Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter

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TRACE NORM REGULARIZATION: REFORMULATIONS, ALGORITHMS, AND MULTI-TASK LEARNING

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Society for Industrial & Applied Mathematics (SIAM)

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An accelerated gradient method for trace norm minimization

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Group Contrastive Self-Supervised Learning on Graphs

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Learning sparse representations for fruit-fly gene expression pattern image annotation and retrieval.

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Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].publisher
Society for Industrial & Applied Mathematics (SIAM)

# publications[].label
CorDEL: A Contrastive Deep Learning Approach for Entity Linkage

# publications[].label
Deep Learning of High-Order Interactions for Protein Interface Prediction

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Non-Local U-Nets for Biomedical Image Segmentation

# publications[].publisher
Association for the Advancement of Artificial Intelligence (AAAI)

# publications[].label
Deep learning based imaging data completion for improved brain disease diagnosis.

# publications[].label
GraphDF: A Discrete Flow Model for Molecular Graph Generation

# publications[].label
Smoothed dilated convolutions for improved dense prediction

# publications[].label
Three-dimensional protein shape similarity analysis based on hybrid features.

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A machine learning approach for the identification of protein secondary structure elements from electron cryo-microscopy density maps.

# publications[].label
Learning Local and Global Multi-Context Representations for Document Classification

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Allen mouse brain atlases reveal different neural connection and gene expression patterns in cerebellum gyri and sulci.

# publications[].label
CorDEL: A Contrastive Deep Learning Approach for Entity Linkage

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Extracting shared subspace for multi-label classification

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Deep Convolutional Neural Networks for Detecting Secondary Structures in Protein Density Maps from Cryo-Electron Microscopy.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
XFake: Explainable Fake News Detector with Visualizations

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
A least squares formulation for a class of generalized eigenvalue problems in machine learning

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Integrative analysis of the connectivity and gene expression atlases in the mouse brain.

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Graph and Geometry Generative Modeling for Drug Discovery

# publications[].publisher
Association for Computing Machinery (ACM)

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How to Estimate the Regularization Parameter for Spectral Regression Discriminant Analysis and its Kernel Version?

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging.

# publications[].label
An accelerated gradient method for trace norm minimization

# publications[].publisher
Association for Computing Machinery (ACM)

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An Interpretable Neural Model with Interactive Stepwise Influence

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Computational modeling of cellular structures using conditional deep generative networks.

# publications[].label
Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks

# publications[].label
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis.

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Second-Order Pooling for Graph Neural Networks.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Drosophila gene expression pattern annotation through multi-instance multi-label learning.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality.

# publications[].label
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Computational network analysis of the anatomical and genetic organizations in the mouse brain.

# publications[].label
Kernel uncorrelated and regularized discriminant analysis: A theoretical and computational study

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Automated annotation of Drosophila gene expression patterns using a controlled vocabulary.

# publications[].label
Multi-class discriminant kernel learning via convex programming

# publications[].label
Self-Supervised Learning of Graph Neural Networks: A Unified Review.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Multi-task feature learning via efficient <inf>2, 1</inf>-norm minimization

# publications[].label
DIG: A Turnkey Library for Diving into Graph Deep Learning Research

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Explainability in Graph Neural Networks: A Taxonomic Survey.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
XGNN: Towards Model-Level Explanations of Graph Neural Networks

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Automated Data Augmentations for Graph Classification

# publications[].label
Machine Learning Explanations to Prevent Overtrust in Fake News  Detection

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JARVIS-Leaderboard: a large scale benchmark of materials design methods

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A Deep Learning Approach for Targeted Contrast-Enhanced Ultrasound Based Prostate Cancer Detection.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Deep convolutional neural networks for multi-modality isointense infant brain image segmentation.

# publications[].label
Multiview Partitioning via Tensor Methods

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Line Graph Neural Networks for Link Prediction.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets.

# publications[].label
Workshop on Optimization Based Methods for Emerging Data Mining Problems

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Feature Selection Based on Structured Sparsity: A Comprehensive Study.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Discriminant Analysis for Dimensionality Reduction: An Overview of Recent Developments

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Sparsity Learning Formulations for Mining Time-Varying Data

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Voxel Deconvolutional Networks for 3D Brain Image Labeling.

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Learning subspace kernels for classification

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Image-level and group-level models for Drosophila gene expression pattern annotation.

# publications[].label
Mining Discrete Patterns via Binary Matrix Factorization

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Global Pixel Transformers for Virtual Staining of Microscopy Images.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Global voxel transformer networks for augmented microscopy

# publications[].label
Self-Supervised Learning of Graph Neural Networks: A Unified Review

# publications[].label
Frontiers of Graph Neural Networks with DIG

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Machine Learning Explanations to Prevent Overtrust in Fake News Detection

# publications[].publisher
Association for the Advancement of Artificial Intelligence (AAAI)

# publications[].label
Deep models for brain EM image segmentation: novel insights and improved performance.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Automated annotation of developmental stages of Drosophila embryos in images containing spatial patterns of expression.

# publications[].label
3D convolutional neural networks for human action recognition.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
DeepEM3D: approaching human-level performance on 3D anisotropic EM image segmentation.

# publications[].label
Augmented Equivariant Attention Networks for Microscopy Image Transformation.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
A Unified Framework for Generalized Linear Discriminant Analysis

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
New phenotype discovery method by unsupervised deep representation learning empowers genetic association studies of brain imaging

# publications[].label
FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis.

# publications[].label
Segmenting Delaminations in Carbon Fiber Reinforced Polymer Composite CT using Convolutional Neural Networks

# publications[].label
Advanced graph and sequence neural networks for molecular property prediction and drug discovery.

# publications[].label
Adaptive diffusion kernel learning from biological networks for protein function prediction.

# publications[].label
Advanced Graph and Sequence Neural Networks for Molecular Property  Prediction and Drug Discovery

# publications[].label
A least squares formulation for canonical correlation analysis

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
A Shared-Subspace Learning Framework for Multi-Label Classification

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Group Contrastive Self-Supervised Learning on Graphs.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
XFake: Explainable Fake News Detector with Visualizations

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Generating 3D Molecules for Target Protein Binding

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Recurrent Encoder-Decoder Networks for Time-Varying Dense Prediction

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
A probabilistic latent semantic analysis model for coclustering the mouse brain atlas.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Robust Deep Learning for Improved Classification of AD/MCI Patients

# publications[].label
Dense Transformer Networks for Brain Electron Microscopy Image Segmentation

# publications[].publisher
International Joint Conferences on Artificial Intelligence

# publications[].label
Deep Adversarial Learning for Multi-Modality Missing Data Completion

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Deep Learning Segmentation of Optical Microscopy Images Improves 3-D Neuron Reconstruction.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Global Voxel Transformer Networks for Augmented Microscopy

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Preface to the Large Scale Visual Analytics Workshop

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Deep convolutional neural networks for annotating gene expression patterns in the mouse brain.

# publications[].label
A Robust Deep Model for Improved Classification of AD/MCI Patients.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Explainability in Graph Neural Networks: A Taxonomic Survey

# publications[].label
Learning the Kernel Matrix in Discriminant Analysis via Quadratically Constrained Quadratic Programming

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering.

# publications[].label
IDM 2017: Workshop on Interpretable Data Mining - Bridging the Gap between Shallow and Deep Models

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
Deep Low-Shot Learning for Biological Image Classification and  Visualization from Limited Training Samples

# publications[].label
CleftNet: Augmented Deep Learning for Synaptic Cleft Detection From Brain Electron Microscopy.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
An Efficient Policy Gradient Method for Conditional Dialogue Generation

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Residual Deconvolutional Networks for Brain Electron Microscopy Image Segmentation.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Stochastic Optimization of Areas Under Precision-Recall Curves with  Provable Convergence

# publications[].label
High-resolution prediction of mouse brain connectivity using gene expression patterns.

# publications[].label
A Deep Transfer Learning Approach for Improved Post-Traumatic Stress Disorder Diagnosis

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Generalized linear discriminant analysis: a unified framework and efficient model selection.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Drosophila Gene Expression Pattern Annotation Using Sparse Features and Term-Term Interactions.

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
On Explainability of Graph Neural Networks via Subgraph Explorations

# publications[].label
Global analysis of gene expression and projection target correlations in the mouse brain.

# publications[].label
Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning.

# publications[].label
Towards structured NLP interpretation via graph explainers

# publications[].label
Non-local U-Net for Biomedical Image Segmentation

# publications[].label
Development of XantheneBased Fluorescent Dyes: Machine LearningAssisted Prediction vs. TDDFT Prediction and Experimental Validation

# publications[].label
Discriminant kernel and regularization parameter learning via semidefinite programming

# publications[].publisher
Association for Computing Machinery (ACM)

# publications[].label
On the Equivalence Between Canonical Correlation Analysis and Orthonormalized Partial Least Squares

# publications[].label
A bag-of-words approach for Drosophila gene expression pattern annotation.

# researcherOn[].label
Collaborative Research: ABI Innovation: Towards Computational Exploration of Large-Scale Neuro-Morphological Datasets

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Directorate for Biological Sciences - (Arlington, Virginia, United States)

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CAREER: Towards the Next Generation of Data-Driven

# researcherOn[].awardedBy.label
Directorate for Biological Sciences - (Arlington, Virginia, United States)

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III: Small: Deep Learning for Gene Expression Pattern Image Analysis

# researcherOn[].awardedBy.label
Directorate for Computer & Information Science & Engineering - (Arlington, Virginia, United States)

# researcherOn[].label
III: Small: Collaborative Research: Demystifying Deep Learning on Graphs: From Basic Operations to Applications

# researcherOn[].awardedBy.label
Directorate for Computer & Information Science & Engineering - (Arlington, Virginia, United States)

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III: Medium: Collaborative Research: Towards Scalable and Interpretable Graph Neural Networks

# researcherOn[].awardedBy.label
Directorate for Computer & Information Science & Engineering - (Arlington, Virginia, United States)

# researcherOn[].label
III: Small: Collaborative Research: Structured Methods for Multi-Task Learning

# researcherOn[].awardedBy.label
Directorate for Computer & Information Science & Engineering - (Arlington, Virginia, United States)

# researcherOn[].label
BIGDATA: Collaborative Research: F: Efficient and Exact Methods for Big Data Reduction

# researcherOn[].awardedBy.label
Directorate for Computer & Information Science & Engineering - (Arlington, Virginia, United States)

# researcherOn[].awardedBy.label
National Institute of Neurological Disorders and Stroke - (Bethesda, Maryland, United States)

# etdChairOf[].label
Wang, Zhengyang (2020-12). Deep Attention Networks for Images and Graphs. Doctoral Dissertation.

# etdChairOf[].label
Gao, Hongyang (2020-08). Graph Neural Networks: A Feature and Structure Learning Approach. Doctoral Dissertation.

# etdChairOf[].label
Yuan, Hao (2021-08). Towards Explainable Deep Models for Images, Texts, and Graphs. Doctoral Dissertation.