Education

• Ph.D. Student at Department of Computer Science & Engineering, Texas A&M University
  June 2021 - Now      College Station, TX
  Advised by Prof. James Caverlee.
  
  
• Master of Engineering at Information Engineering, Waseda University
  Sep 2017 - Sep 2019       Tokyo, Japan
  Advised by Prof. Kamata Sei-ichiro.
  
  
• Bachelor at School of Information Science and Engineering, Southeast University
  Sept 2014 - July 2018       Nanjing, China
  Special Class for the Gifted Young, Chien-Shiung Wu Honor College.

Experiences

1. Applied Scientist Intern at Amazon
   Automated Marketing Team
   Sep 2024 - Nov 2024      Seattle, WA
   
   
2. Research Intern at NEC Labs America
   Machine Learning Department
   May 2024 - Aug 2024      Princeton, NJ
   Mentor: Dr. Martin Renqiang Min.
   
   
3. Research Intern at NEC Labs America
   Machine Learning Department
   May 2023 - Aug 2023      Princeton, NJ
   Mentor: Dr. Martin Renqiang Min.
   
   
4. Research Intern at Baidu Research
   Big Data Lab
   June 2020 - Aug 2020      Beijing, China
   Mentored by Dr. Haoyi Xiong and Prof. Dejing Dou.

Publications

* indicates equal contribution.
1. KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques [Paper]
   Rui Yang, Haoran Liu, Edison Marrese-Taylor, Qingcheng Zeng, Yu He Ke, Wanxin Li, Lechao Cheng, Qingyu Chen,
   James Caverlee, Yutaka Matsuo, Irene Li
   Preprint.
   
   
2. Everything Perturbed All at Once: Enabling Differentiable Graph Attacks [Paper]
   Haoran Liu, Bokun Wang, Jianling Wang, Xiangjue Dong, Tianbao Yang, James Caverlee
   International Conference on World Wide Web (WWW), 2024. Short Paper Track.
   
   
3. Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models [Paper]
   Meng Liu, Haoran Liu, Shuiwang Ji
   International Conference on Learning Representations (ICLR), 2023
   
   
4. Learning Hierarchical Protein Representations via Complete 3D Graph Networks [Paper] [Code]
   Limei Wang*, Haoran Liu*, Yi Liu, Jerry Kurtin, Shuiwang Ji
   International Conference on Learning Representations (ICLR), 2023
   
   
5. ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs [Paper] [Code]
   Limei Wang*, Yi Liu*, Yuchao Lin, Haoran Liu, Shuiwang Ji
   Conference on Neural Information Processing Systems (NeurIPS), 2022
   
   
6. DIG: A Turnkey Library for Diving into Graph Deep Learning Research [Paper] [Code]
   Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan,
   Haoran Liu, Cong Fu, Bora Oztekin, Xuan Zhang, Shuiwang Ji
   Journal of Machine Learning Research (JMLR), 2022
   
   
7. Exploring the Common Principal Subspace of Deep Features in Neural Networks [Paper]
   Haoran Liu, Haoyi Xiong, Yaqing Wang, Haozhe An, Dejing Dou
   Machine Learning Journal (MLJ), 2022
   
   
8. Edge-guided Hierarchically Nested Network for Real-time Semantic Segmentation [Paper]
   Yuqi Li, Sei-Ichiro Kamata, Haoran Liu
   IEEE International Conference on Signal and Image Processing Applications (ICSIPA), 2019
   Best Paper Award
   
   
9. Hybrid Featured based Pyramid Structured CNN for Texture Classification [Paper]
   Haoran Liu, Sei-Ichiro Kamata, Yuqi Li
   IEEE International Conference on Signal and Image Processing Applications (ICSIPA), 2019
   
   

Awards

• D. E. Shaw Research Graduate and Postdoctoral Women’s Fellowship. 2023
• Best Paper Award. ICSIPA. 2019.
• IPS Special Scholarship for International Student. Waseda University. 2017-2018.
• Foundation for the Advancement of Industry, Science and Technology (FAIS) Scholarship. 2017-2018.
• Second Prize in National Undergraduate Electronics Design Contest. 2016.

Services

Conference reviewer: NeurIPS (23', 24'), ICLR (23', 24', 25'), KDD (23'), SIGIR(23'), LoG (22', 23', 24'), NeurIPS Dataset and Benchmark Track (22', 23', 24'), CVPR (24', 25'), ICDM (20'), etc.
Jounal reviewer: IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Cybernetics.