Hongyang Gao, Ph.D. student Department of Computer Science & Engineering Texas A&M University 520 Harvey R. Bright Building College Station, TX 77843-3112 Phone: 1(708)964-8907 E-mail: hongyang.gao@tamu.edu Google Scholar Github

Short Biography

I am currently a third-year Ph.D. student in Department of Computer Science & Engineering, Texas A&M University. My advisor is Dr. Shuiwang Ji.

Education

• Ph.D., Computer Science, Texas A&M University, September 2018 - Present

• Ph.D., Computer Science, Washington State University, May 2016 - August 2018

• M.S., Computer Science, Tsinghua Univeristy, September 2009 - July 2012

• B.S., Biomedical English, Peking University, September 2004 - July 2009

Publications

2019

• Hongyang Gao and Shuiwang Ji
  Graph U-Nets
  Thirty-sixth International Conference on Machine Learning (ICML), 2019
  [paper] [code] [poster] [slides]

• Hongyang Gao and Shuiwang Ji
  Graph Representation Learning via Hard and Channel-Wise Attention Networks
  The 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2019
  [poster]

• Hongyang Gao, Hao Yuan, Zhengyang Wang, and Shuiwang Ji
  Pixel Transposed Convolutional Networks
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  [paper] [code]

• Hongyang Gao, Yongjun Chen, and Shuiwang Ji
  Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations
  The Web Conference (WWW), 2019
  [paper] [code]

• Lei Cai, Hongyang Gao and Shuiwang Ji
  Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation
  The SIAM International Conference on Data Mining (SDM), 2019
  [paper] [code]

2018

• Hongyang Gao, Zhengyang Wang, and Shuiwang Ji
  ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions
  The Thirty-second Annual Conference on Neural Information Processing Systems (NeurIPS), 2018
  [paper] [code]

• Hongyang Gao, Zhengyang Wang, and Shuiwang Ji
  Large-Scale Learnable Graph Convolutional Networks
  The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018
  [paper] [code]

• Yongjun Chen, Hongyang Gao, Lei Cai, Min Shi, Dinggang Shen, and Shuiwang Ji
  Voxel Deconvolutional Networks for 3D Brain Image Labeling
  The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018
  [paper] [code]

• Lei Cai, Zhengyang Wang, Hongyang Gao, Dinggang Shen, and Shuiwang Ji
  Deep Adversarial Learning for Multi-Modality Missing Data Completion
  The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018
  [paper] [code]

2017

• Hongyang Gao and Shuiwang Ji
  Efficient and Invariant Convolutional Neural Networks for Dense Prediction
  The IEEE International Conference on Data Mining (ICDM), 2017
  [paper] [code]

Awards

• ICML2019 Travel Award
• KDD2019 Travel Award
• KDD2018 Travel Award
• ICDM2017 Travel Award
• Alfred Suksdorf Scholarship, Washington State University, 2016

Services

Program Committee Member

• NeurIPS 2019
• AAAI 2019

Journal Reviewer

• IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
• Data Mining and Knowledge Discovery (DAMI)

Teaching

• Guest lecture on Texas A&M University to CSCE 636: Deep Learning on Graph Data, 2018
• Guest lecture on Washington State University to CPTS 437: Introduction to Machine Learning, 2018
• Guest lecture on Washington State University to CPTS 580: Introduction to Robotics, 2017

Research Interests

• Machine learning

• Deep learning

• Computational biology

• Computational neuroscience