Song Jiang

songjiang (at) cs (dot) ucla (dot) edu

About Me

• I'm a Ph.D. candidate at Computer Science Department, University of California, Los Angeles (UCLA). My advisor is Prof. Yizhou Sun. Prior to UCLA, I got my Master of Engineering degree from Tsinghua University, and Bachelor of Engineering degree from Shandong University.

• I have broad interests in machine learning, graphs, and causality.

Publication

Conferences

• A Single Vector Is Not Enough: Taxonomy Expansion via Box Embeddings
  

  • Song Jiang, Qiyue Yao, Qifan Wang and Yizhou Sun.
    

  • WWW 2023, Austin, TX
    

  • [Paper] [code]

• Estimating Causal Effects on Networked Observational Data via Representation Learning
  

  • Song Jiang and Yizhou Sun.
    

  • CIKM 2022, Atlanta, GA
    

  • [Paper] [code]

• Bridging Self-Attention and Time Series Decomposition for Periodic Forecasting
  

  • Song Jiang, Tahin Syed, Xuan Zhu, Joshua Levy, Boris Aronchik and Yizhou Sun.
    

  • CIKM 2022, Atlanta, GA
    

  • [Paper] [code]

• HINTS: Citation Time Series Prediction for New Publications via Dynamic Heterogeneous Information Network Embedding
  

  • Song Jiang, Bernard Koch and Yizhou Sun
    

  • WWW 2021, virtual
    

  • [Paper] [Code]

• Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks
  

  • Difan Zou, Ziniu Hu, Yewen Wang, Song Jiang, Yizhou Sun and Quanquan Gu
    

  • NeurIPS'19, Vancouver, Canada
    

  • [Paper]

Workshops and Preprints

• Unit Selection: Learning Benefit Function from Finite Population Data
  

  • Ang Li, Song Jiang, Yizhou Sun and Judea Pearl
    

  • NeurIPS 2022 Workshop on Causality for Real-world Impact
    

  • [Arxiv]

• Learning probabilities of causation from finite population data
  

  • Ang Li, Song Jiang, Yizhou Sun and Judea Pearl
    

  • Preprint 2022
    

  • [Arxiv]

• Deep Learning of Potential Outcomes
  

  • Bernard Koch, Tim Sainburg, Pablo Geraldo, Song Jiang, Yizhou Sun, and Jacob Gates Foster
    

  • Preprint 2021
    

  • [Arxiv]

Industry Experience

• Meta AI, Research intern
  

  • Menlo Park, CA,  Jun 2022 - Sept 2022
  
  

• Amazon Web Services (AWS), Applied scientist intern
  

  • Boston, MA (Remote),  Jun 2021 - Sept 2021
  
  

• Snap Inc., Research intern
  

  • Santa Monica, CA (Remote),  Jun 2020 - Aug 2020

Education

• Ph.D. University of California, Los Angeles (UCLA),  Sept 2018 - now
  

• M.E.    Tsinghua University,  Aug 2015  - Jul 2018
  

• B.E.      Shandong University,  Sept 2011 - Jun 2015
  

Services

• PC member / reviewer:

  • Conference: ICML 2023, KDD 2023 2020, WWW2023, AAAI 2023, ICWSM 2023, ICASSP 2023, CIKM 2022, LoG 2022, IJCAI 2021-2022, ECML-PKDD 2020-2022

  • Journal: TPAMI, TNNLS, TKDE, Neurocomputing, TBD.

  
  
  
  

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