Yaqing Wang

Short Biography: I am a fourth year Ph.D. Student under the supervision of Dr. Jing Gao in Department of Computer Science and Engineering, The State University of New York at Buffalo. Before joining UB in 2016, I got my Master of Science degree in Statistics from University of California, San Diego and got my Bachelor of Science degree in Mathematics from Shandong University.

I am broadly interested in data science and artificial intelligence with a focus on data mining and machine learning. In particular, I am interested in Data Integration, Information Trustworthiness Evaluation, Knowledge Graph, Natural Language Processing, Meta-Learning and Generative Models.

News!

  • [2020-07] One paper on Knowledge Graph Validation is accepted by CIKM, 2020.
  • [2020-05] Join Microsoft Research as a research intern.
  • [2020-05] Two papers on automatic textual attribute validation via meta-learning and
    knowledge collection of product knowledge graph are accepted by KDD, 2020.
  • [2020-01] Serve as PC of KDD 2020.
  • [2019-12]One paper accepted by SDM, 2020.
  • [2019-11] One paper accepted by AAAI, 2020.

  • Decomposed Adversarial Learned Inference [Paper]
    Hanbo Li*, Yaqing Wang*(* equal contribution), Changyou Chen, Jing Gao.

2020

  • Automatic Validation of Textual Attribute Values in ECommerce Catalog by Learning with Limited Labeled Data [Paper]
    Yaqing Wang, Yifan Ethan Xu, Xian Li, Xin Luna Dong and Jing Gao.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), San Diego, CA, August 2020 (Oral Paper Acceptance Rate 5.8%)
  • AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types [Paper]
    Gabriel Blanco Saldana, Saurabh Deshpande, Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Haw-Shiuan Chang, Giannis Karamanolakis, Yuning Mao, Yaqing Wang, Christos Faloutsos, Andrew McCallum and Jiawei Han.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), San Diego, CA, August 2020
  • Weak Supervision for Fake News Detection via Reinforcement Learning [Paper] [Full Paper] [Data]
    Yaqing Wang, Weifeng Yang, Fenglong Ma, Jin Xu, Bin Zhong, Qiang Deng, Jing Gao.
    Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020
  • Knowledge Graph Validation via Cross-Graph Representation Learning [To appear]
    Yaqing Wang, Fenglong Ma, Jing Gao.
    Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM), Virtual, October, 2020
  • Rare Disease Prediction by Generating Quality-Assured Electronic Health Records [Paper]
    Fenglong Ma*, Yaqing Wang*(* equal contribution), Jing Gao, Houping Xiao, and Jing Zhou.
    Proceedings of the SIAM International Conference on Data Mining(SDM), 2020.

2019

  • Hypothesis Generation From Text Based On Co-Evolution Of Biomedical Concepts [Paper]
    Kishlay Jha, Guangxu Xun, Yaqing Wang, Aidong Zhang.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019
  • MeSHProbeNet: A Self-attentive Probe Net for MeSH Indexing [Paper]
    Guangxu Xun, Kishlay Jha, Ye Yuan, Yaqing Wang, Aidong Zhang.
    Bioinformatics, Oxford University Press, 2019

2018

  • EANN: Event Adversarial Neural Networks for Multi-Modal Fake News Detection [Paper] [Data&Code] [Video] [Poster]
    Yaqing Wang, Fenglong Ma, Zhiwei Jin, Ye Yuan, Guangxu Xun, Kishlay Jha, Lu Su and Jing Gao.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018
  • Interpretable Word Embeddings For Medical Domain [Paper]
    Kishlay Jha*, Yaqing Wang* (* equal contribution), Guangxu Xun and Aidong Zhang.
    IEEE International Conference on Data Mining (ICDM), 2018
  • A General Framework for Diagnosis Prediction via Incorporating Medical Code Descriptions [Paper]
    Fenglong Ma, Yaqing Wang, Houping Xiao, Ye Yuan, Radha Chitta, Jing Zhou and Jing Gao.
    IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018
  • Multivariate Sleep Stage Classification using Hybrid Self-Attentive Deep Learning Networks [Paper]
    Ye Yuan, Fenglong Ma, Guangxu Xun,Yaqing Wang, Kebin Jia, Lu Su and Aidong Zhang.
    IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018
  • MuVAN: A Multi-view Attention Network for Multivariate Temporal Data [Paper]
    Ye Yuan, Guangxu Xun, Fenglong Ma, Yaqing Wang, Nan Du, Kebin Jia, Lu Su and Aidong Zhang.
    IEEE International Conference on Data Mining (ICDM), 2018
  • Towards Environment Independent Device Free Human Activity Recognition [Paper]
    Wenjun Jiang, Chenglin Miao, Fenglong Ma, Shuochao Yao, Yaqing Wang, Xin Ma, Chen Song,
    Ye Yuan, Hongfei Xue, Dimitrios Koutsonikolas, Wenyao Xu and Lu Su.
    24th Annual International Conference on Mobile Computing and Networking (MobiCom), 2018
  • Concepts-Bridges: Uncovering Conceptual Bridges Based on Biomedical Concept Evolution [Paper]
    Kishlay Jha, Guangxu Xun, Yaqing Wang, Vishrawas Gopalakrishnan and Aidong Zhang.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018

2017

  • Discovering Truths from Distributed Data [Paper] [Code]
    Yaqing Wang, Fenglong Ma, Lu Su, and Jing Gao
    IEEE International Conference on Data Mining (ICDM), 2017

    PC Memebers/Reviewer

  • ICML 2020, KDD 2020, BigData 2020
  • ICLR 2021
  • Travel Awards: AAAI2020, KDD2018, ICDM2017
  • UB Presidential Fellowship, 2016-2020
  • Last updated: July 2020.