Hongyang Gao, Ph.D. Candidate 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 Ph.D. Candidate in Department of Computer Science & Engineering, Texas A&M University. My advisor is Dr. Shuiwang Ji.

Education

• Ph.D. in Computer Science, Texas A&M University, Aug 2020 (Expected)

• M.S. in Computer Science, Tsinghua Univeristy, Jul 2012

• B.S. in Biomedical English, Peking University, Jul 2009

Publications

I have published 8 papers as the first author (1 TPAMI, 1 NeurIPS, 1 ICML, 2 KDD, 1 WWW, 1 AAAI, and 1 ICDM) and co-authored another 3 papers (2 KDD and 1 SDM).

2020

• Hongyang Gao, Lei Cai, and Shuiwang Ji
  Adaptive Convolutional ReLUs
  Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020
  

2019

• 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 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, 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

Services

Program Committee Member

• NeurIPS 2019
• ICML 2019
• ICLR 2020
• AAAI 2019, 2020

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, 2019
• Guest lecture on Texas A&M University to CSCE 636: Deep Learning on Graph Data, 2018

Research Interests

• Machine learning

• Deep learning

• Computational biology

• Computational neuroscience