Hongning Wang

Assistant Professor of Computer Science

Office: Rice Hall, Room 408

Phone: 434-982-2228

Email: hw5x-at-virginia-dot-edu

I am an assistant professor in the Department of Computer Science of University of Virginia. My research interest includes data mining, machine learning, and information retrieval, with a special emphasis on computational user behavior modeling. I graduated from the CS@UIUC in May 2014. Our group homepage is at HCDM@UVa.

News

  • Our paper "Variance Reduction in Gradient Exploration for Online Learning to Rank" received the Best Paper Award at SIGIR'2019!

  • I gave an invitated talk about "Join Network Embedding with Topic Embedding for User Representation Learning" at LinkedIn.

  • I gave an invitated talk about "Learning Contextual Bandits in a Non-Stationary Environment" at Pinterest.

  • I gave an invitated talk about "Context Attentive Document Ranking and Query Suggestion in Search Tasks" at the Task Intelligence Workshop, WSDM'2019, Melbourne Australia.

  • I was selected for the WSDM 2019 Outstanding Senior Program Committee Award.

  • Our proposal of "Learning and Improving Alzheimer's Patient-Caregiver Relationships via Smart Healthcare Technology" has been funded by NSF SCH program. More details about this award can be found here.

  • Thanks Nvidia for the generious support of a Titan XP GPU!

  • Our proposal of "The Building Adapter: Automatic Mapping of Commercial Buildings for Scalable Building Analytics" has been funded by the U.S. Department of Energy. More details about this award can be found here.

  • Our proposal of "Cyber Physical Mappings - Empower Building Analytics at Scale" has been funded by NSF IIS program. More details about this award can be found here.

  • I gave an invitated talk about "Contextual Bandits in a Collaborative Environment" at the Department of Computer Science and Technology, Tsinghua University, Beijing China.

  • We have been awarded by the Yelp Dataset Challenge Round Eight!

  • Our group homepage is now available at HCDM@UVa.

  • Our proposal of "Collaborative Sensing: An Approach for Immediately Scalable Sensing in Buildings" has been funded by NSF CPS program. More details about this award can be found here.

  • Our proposal of "Collaborative Learning with Incomplete and Noisy Knowledge" has been funded by NSF III program. More details about this award can be found here.

  • I gave an invitated talk about "Collaborative Online Learning" at Yahoo Search Science Team.

  • I have received the NSF Faculty Early Career Development Program (CAREER) Award. More details about this award can be found here.

  • Our proposal of "Call for Special Issue on Search, Mining and their Applications on Mobile Devices" has been accepted by the ACM Transactions on Information Systems (TOIS). Call for papers will be announced shortly.

  • I gave an invitated talk about "Human-centric big data mining" at Center for Embedded Systems for Critical Applications (CESCA) in the Department of Electrical and Computer Engineering at Virginia Tech.

  • I gave an invitated talk about "Human-centric big data mining" in Quantitative Psychology Group in the Department of Psychology at UVa.

  • My research is reported on UVa Today.

  • The course website for CS6501 Text Mining has been deployed.

  • I was selected for the WSDM 2015 Outstanding Reviewer Award.

  • I have position opennings for Ph.D. students for Fall 2015. If you are self-motivated and want to pursue a Ph.D. degree in the areas of data mining and information retrieval, please contact me. More information about the graduate admission at CS@UVa can be found here. Please note the application deadline is December 15th, 2014.

  • I am going to offer CS6501: Text Mining next Spring semester.

  • I am offering CS6501: Information Retrieval this Fall semester.

  • I joined CS@UVa as an assistant professor.


Award and Honor


Invited Talks


Academic Activities

  • Program committee member:
    • International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR): 2019, 2018, 2017, 2016, 2015
    • International ACM KDD Conference on Knowledge Discovery and Data Mining (KDD): 2019, 2018, 2017, 2016, 2015
    • The World Wide Web Conference (WWW): 2020 (SPC), 2019, 2018, 2016, 2015
    • ACM International Conference on Web Search and Data Mining (WSDM): 2019 (SPC), 2018 (SPC), 2017, 2016, 2015
    • Conference on Neural Information Processing Systems (NeurIPS): 2019
    • Annual Meeting of the Association for Computational Linguistics (ACL): 2019, 2018, 2017, 2015
    • ACM International Conference on Information and Knowledge Management (CIKM): 2017, 2015, 2014
    • International Conference on Machine Learning (ICML): 2014, 2013, 2012
    • Association for the Advancement of Artificial Intelligence (AAAI): 2019, 2018, 2017
    • IEEE International Conference on Data Mining (ICDM): 2019
    • ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR): 2019
  • Journal reviewer: TKDE, TOIS, TPAMI, TOIS, Neurocomputing, BMC Bioinformatics, Information Processing & Management, IJAIT, Neural Processing Letters, World Wide Web Journal, International Journal of Machine Learning and Cybernetics.
  • Public services: KDD 2020 Student Sponsorship Co-Chair, SIGIR 2018 Student Sponsorship Chair, WSDM 2018 Demo Track Chair, CIKM 2016 Publicity chair, AIRS 2016 area chair for IR Models and Theories, NLPCC 2015 area chair for Search and Advertisement.

Selected Publications

[Google Scholar] [DBLP] [Full List]
  1. Qingyun Wu, Zhige Li, Huazheng Wang, Wei Chen and Hongning Wang. Factorization Bandits for Online Influence Maximization. The 25th ACM SIGKDD Conference On Knowledge Discovery And Data Mining (KDD'2019), p636-646, 2019. (PDF)
  2. Yiyi Tao, Yiling Jia, Nan Wang and Hongning Wang. The FacT: Taming Latent Factor Models for Explainability with Factorization Trees. The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), p295-304, 2019. (PDF)
  3. Huazheng Wang, Sonwoo Kim, Eric McCord-Snook, Qingyun Wu and Hongning Wang. Variance Reduction in Gradient Exploration for Online Learning to Rank. The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), p835-844, 2019. Best Paper Award (PDF)
  4. Wasi Uddin Ahmad, Kai-Wei Chang and Hongning Wang. Context Attentive Document Ranking and Query Suggestion. The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), p385-394, 2019. (PDF, code)
  5. Qingyun Wu, Huazheng Wang, Yanen Li and Hongning Wang. Dynamic Ensemble of Contextual Bandits to Satisfy Users' Changing Interests. The Web Conference 2019 (WWW 2019), p2080-2090, May 2019. (PDF)
  6. Qi Yi, Qingyun Wu, Hongning Wang, Jie Tang and Maosong Sun. Bandit Learning with Implicit Feedback. The 32nd Conference on Neural Information Processing Systems (NIPS 2018), p7287-7297, 2018. (PDF)
  7. Nan Wang, Yiling Jia, Yue Yin and Hongning Wang. Explainable Recommendation via Multi-Task Learning in Opinionated Text Data. The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), p165-174, 2018. (PDF)
  8. Qingyun Wu, Naveen Iyer and Hongning Wang. Learning Contextual Bandits in a Non-stationary Environment. The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), p495-504, 2018. (PDF)
  9. Huazheng Wang, Qingyun Wu and Hongning Wang. Learning Hidden Features for Contextual Bandits. The 25th ACM International Conference on Information and Knowledge Management (CIKM 2016), p1633-1642, 2016. (PDF, code)
  10. Qingyun Wu, Huazheng Wang, Quanquan Gu and Hongning Wang. Contextual Bandits in A Collaborative Environment. The 39th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'2016), p529-538, 2016. (PDF, Slides, code)