image description

Qi Song

I'm an Applied Scientist at Amazon.com. I obtained my Ph.D. from Database Group at Washington State University under supervision of Prof. Yinghui Wu . I got my BS and MS degree from Beihang University in 2012 and 2015. My research spans the areas of Big Data, databases systems and data management, with emphasis on dynamic graphs, knowledge graph, graph query models and languages, distributed graph processing, neural network based machine learning for graphs [PhD Thesis].
Email: songqi1990(at)gmail.com

Selected Publications

[Full List] [Google Scholar]
  1. Explaining Missing Data in Graphs: A Constraint-based Approach. [Paper][Slide]
    IEEE International Conference on Data Engineering (ICDE), 2021.
    Qi Song, Peng Lin, Hanchao Ma, Yinghui Wu

  2. Answering Why-Questions for Subgraph Queries. [Paper]
    Accepted by IEEE Transactions on Knowledge and Data Engineering(TKDE), 2020.
    Qi Song, Mohammad Hossein Namaki, Peng Lin, Yinghui Wu

  3. Repairing Entities using Star Constraints in Multirelational Graphs. [Paper][Slide]
    IEEE International Conference on Data Engineering (ICDE), 2020.
    Peng Lin, Qi Song, Yinghui Wu

  4. Answering Why-questions by Exemplars in Attributed Graphs. [Paper][Slide][Poster][Talk]
    ACM SIGMOD Conference on Management of Data (SIGMOD), 2019.
    Mohammad Hossein Namaki, Qi Song, Yinghui Wu, Shengqi Yang

  5. Answering Why-Questions for Subgraph Queries in Multi-Attributed Graphs. [Paper][Slide][Poster]
    IEEE International Conference on Data Engineering (ICDE), 2019.
    Qi Song, Mohammad Hossein Namaki, Yinghui Wu

  6. TGNet: Learning to Rank Nodes in Temporal Graphs. [Paper][Slide]
    ACM International Conference on Information and Knowledge Management(CIKM), 2018.
    Qi Song, Bo Zong, Yinghui Wu, Lu-An Tang, Hui Zhang, Guofei Jiang and Haifeng Chen

  7. Mining Summaries for Knowledge Graph Search. [Paper]
    IEEE Transactions on Knowledge and Data Engineering(TKDE), Vol.30 (Issue No. 10), 1887-1900, 2018.
    Qi Song, Yinghui Wu, Peng Lin, Luna Xin Dong, Hui Sun

  8. Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection. [Paper]
    International Conference on Learning Representations(ICLR), 2018.
    Bo Zong, Qi Song, Martin Renqiang Min, Wei Cheng, Cristian Lumezanu, Daeki Cho, Haifeng Chen

Intern Experience

Amazon

2019.5-2019.8
Applied Scientist Intern.
Topic: Time fixed effects model for long-running experiment and graph-based exploration tool.

JD AI Research

2018.5-2018.8
Intern research assistant.
With Dr. Wei Li, Jin Guo and (Martin) Congmin Min
Topic: User prompt generation for online e-commerce dialogue system.

NEC Labs America

2017.5-2017.8
Intern research assistant.
With Dr. Bo Zong
Topic: Unsupervised anomaly detection model for network attack detection.

NEC Labs America

2016.5-2016.8
Intern research assistant.
With Dr. Bo Zong
Topic: Temporal graph ranking for system log analysis.

Awards

  1. NSF Student Travel Award for SIGMOD 2019
  2. NSF Student Travel Award for ICDE 2019
  3. SIGIR Student Travel Award for CIKM 2017
  4. NSF Student Travel Award for ICDM 2016
  5. NSF student travel support to NSF Graduate Data Science Workshop 2016, Seattle
  6. NSF student travel support to NSF Graduate Data Science Workshop 2015, Seattle
  7. EDBT student travel grant for EDBT summer school 2015, Palamos Spain
  8. MediaTek Inc. - Beihang Univ. Science and Technology Award 2014