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      Liu  Yang

      PhD Candidate, Research Assistant
      Homepage in Github.io: https://yangliuy.github.io/ (Accessible from Mainland China)

I am a fourth-year PhD student in the Center for Intelligent Information Retrieval (CIIR) , College of Information and Computer SciencesUniversity of Massachusetts Amherst under the supervision of Prof. W. Bruce Croft. I am also working closely with Prof. Jiafeng Guo.

I was a Research Assistant at Text Mining Group in School of Information Systems, Singapore Management University, under the supervision of Prof. Jing Jiang on text mining and machine learning. I was working closely with Prof. Feida Zhu. I got my Master degree in Computer Science from University of Massachusetts Amherst and another Master degree from Peking UniversityFor industrial experiences, I worked as a research intern in Microsoft Research Redmond, Microsoft Bing and a software engineer intern in Search R&D Department of Baidu IncMy research areas include information retrieval, natural language processing,  text mining and machine learning. I have published papers in conferences such as SIGIR, ACL, CIKM, ICDM, NAACL, COLING and ECIRMoreover, I have served as the PC member for top-tier conferences including KDD, ACL, WSDM and CIKM. I'm now focusing on research on deep learning, question answering, statistical language models, probabilistic graphical models, ranking and relevance, learning to rank and online user modeling/profiling.

I expect to graduate in Summer 2019 and am on the job market for research related positions starting in Summer 2019. Drop me an email if you are hiring and find us a good match :)

Academic Experience

Industrial Experience
Research Interests

PhD thesis topic: Deep Learning in QA/Conversations and IR/Search
  • Information Retrieval/ Web Search/ Question Answering
    • Ranking and Relevance/ Language Modeling/ Learning to Rank, Answer Retrieval/ Question Answering/ Machine Comprehension/ Learning to Match, Dialogue Systems/ Human-Computer Conversation/ Sequence-to-Sequence Models, Query Expansion/Query Reformulation/Query Processing and Understanding, Search Evaluation/ User Satisfaction/ Search Personalization
  • Text Mining/ Data Mining/ Natural Language Processing
    • Topic Modeling, Sentiment Analysis/ Opinion Mining, Online User Modeling/ Profiling, Recommender System, Community Question Answering, Information Extraction and Summarization
  • Statistical Machine Learning/ Deep Learning/ Artificial Intelligence
    • Probabilistic Graphical Models, Matrix Factorization/ Collaborative Filtering, Neural Networks/ Deep Learning/ Representation Learning

Recent News
  • [Apr. 2018] One short paper is accepted by ACL'18.
  • [Apr. 2018] Passed the PhD dissertation proposal defense. 
  • [Apr. 2018] One full paper and two short papers are accepted by SIGIR'18. See you in Ann Arbor Michigan during SIGIR'18.
  • [Sept. 2017] Visited Prof. Jiafeng Guo in ICT/CAS, Dr. Hang Li in Toutiao Inc, Dr. Minghui Qiu in Alibaba Inc. and Dr. Zhaochun Ren in data science lab at JD.com.
  • [Apr. 2017] One full paper is accepted by SIGIR'17 and one paper is accepted by SIGIR'17 Neu-IR workshop. See you in Tokyo during SIGIR'17.
  • [Sept.2016] Finished a summer internship in Microsoft Research Redmond.
  • [Jul.  2016] One full paper is accepted by CIKM'16 and I will attend CIKM'16 in Indianapolis, IN, USA.
  • [Jun. 2016] One full paper is accepted by ICTIR'16.
  • [Mar.2016] One short paper is accepted by SIGIR'16.
  • [Dec.2015] Two full papers are accepted by ECIR'16 and I will attend ECIR'16 in Padova, Italy.
  • [Aug.2015] Finished a summer internship in Microsoft Research Redmond/Bing.
  • [May.2014] One full paper is accepted by COLING'14.
  • [Oct. 2013] Attended CIKM'13 in San Francisco, CA, USA.
  • [Jul.  2013] One full paper and one short paper are accepted by CIKM'13.

Publications  By Topics Google Scholar Google Calendar CS Top Cited Papers (5 SIGIR, 3 CIKM, 1ACL, 2 ECIR, 1 ICDM, 1 NAACL, 1 COLING, 1 ICTIR)

         PhD Thesis Related Research (PhD thesis topic: Deep Learning in QA/Conversations and IR/Search)
  • [18] Minghui Qiu, Liu Yang, Feng Ji, Wei Zhou, Weipeng Zhao, Jun Huang, Haiqing Chen, W. Bruce Croft, Wei Lin. Transfer Learning for Context-Aware Question Matching in Information-seeking Conversation Systems in E-commerce. In Proceedings of  the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018), Melbourne, Australia, July 15-20, 2018. Short PaperAcceptance rate=24% (126 out of 526(CCF Rank A)
        Other Previous Research:
    Selected Professional Services
    • PC Member, The 27th ACM International Conference on Information and Knowledge Management (CIKM 2018)
    • PC Member, The 24rd SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018)
    • PC Member, The 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018)
    • PC Member, The 4th ACM International Conference on the Theory of Information Retrieval (ICTIR 2018)
    • Reviewer, The 40th European Conference on Information Retrieval (ECIR 2018)
    • PC Member, The 11th ACM International Conference on Web Search and Data Mining (WSDM 2018)
    • Reviewer, The 26th international World Wide Web Conference (WWW 2017)
    • PC Member, The 26th ACM International Conference on Information and Knowledge Management (CIKM 2017)
    • PC Member, The 3rd ACM International Conference on the Theory of Information Retrieval (ICTIR 2017)
    • PC Member, The 24th ACM International Conference on Information and Knowledge Management (CIKM 2015)

    Links

    Selected Open Source Projects
    • MatchZooMatchZoo is a toolkit for deep neural text matching. It was developed with a focus on facilitating the designing, comparing and sharing of deep text matching models. The implemented models include ARC-I/ARC-II, DSSM, CDSSM, MatchPyramid, DRMM, aNMM, MV-LSTM, Duet, etc.
    • NeuralResponseRanking: NeuralResponseRanking is an open source package for several neural matching models for response ranking in information-seeking conversations.
    • LDAGibbsSampling: LDAGibbsSampling is an open source package for Gibbs sampling inference of LDA model, which could be used for topic modeling in text mining.
    Selected Awards
    • Student Travel Award of SIGIR 2018/ SIGIR 2017/ CIKM 2016/ ECIR 2016/ CIKM 2013, 2013-2018
    • Best Paper Award Runner-ups of SocInfo 2013, Kyoto, Japan, 2013
    • Top 10 Undergraduates of Liaoning Province, Department of Education, Liaoning Province, 2011
    • ACM-ICPC Programming Contest ,second prize, Northeastern University, 2011
    • National Scholarship(top 1%), National Ministry of Education, 2010
    • IBM Chinese Excellent Student Scholarship(top 1%), IBM, 2010
    • International Mathematical Contest in Modelling(MCM), Honorable Mention, SIAM and MAA, 2010
    • Chinese Undergraduate Mathematical Contest in Modeling(CUMCM), National Second Prize (First Prize in Liaoning Province), 2009