Qing Wang's Homepage

Qing Wang

Contact information
Address: 07-129, IBM Thomas J. Watson Research Center, 1101 Kitchawan Rd, Yorktown Heights, NY 10598, USA
Phone: (914)945-1751 Email: Qing(dot)Wang1(at)ibm(dot)com

About Me

Qing Wang received her Ph.D. in 2018 from School of Computing and Information Sciences at Florida International University under the supervision of Distinguished University Professor, Ryder Professor & Director S. S. Iyengar and Associate Director & Eminent Scholar Chaired Professor Shu-Ching Chen. Qing entered the Ph.D. program in Fall 2014,immediately after obtaining her Master and Bachelor degree in Computer Science from Xidian University in 2013 and Zhengzhou University in 2009. She was the recipient of 2018 FIU SCIS Overall Outstanding Graduate Student. She received the Best Student Paper Award from 2017 IEEE SCC. Qing's research focuses on interactive recommender system [irs_ppt], multi-armed bandit algorithm [intro_ppt] and automatic service management. Her dissertation is "Intelligent Data Mining Techniques for Automatic Service Management". [ppt]

More details can be found in her CV and Google Scholar.

Research Experience

  • Discovery Lab, School of Computing and Information Science, FIU, Aug. 2014 - Dec. 2018
    • Log Ming System. It is an online mining system including a pre-processing module for raw log data, a visualization module for log data with 2D and 3D presentation, the important algorithms module to mining association rule or temporal relationships for log events.
    • Multi-armed Bandit Model. Bandit models are very popular applying into various interacitve recommender systems. I am interested in modeling the interactive behaviors between users and items to learn user's preference. [ppt]

Industrial Experience

  • IBM Thomas J. Watson Research Center, Postdoctoral Researcher, Yorktown Heights, NY, USA (Mar. 2019 - Present)

    AI for Operations (natural language processing, machine learing, deep learning and reinforcement learing).

    (1) event grouping, event correlation

    (2) fault localization, root cause analysis

    (3) fault generation

  • IBM Thomas J. Watson Research Center, Research Intern at Cognitive Service Foundation Team, Yorktown Heights, NY, USA (May 2018 - July 2018)

    (1) Proposed and implemented learning Models for AI Skills Orchestration: aiming to utilize bandit algorithms for interactive skills planning.

    (2) Developed a learning Logical Representations model of Natural Languages with Little Supervision: aiming to learn the logic forms from human language using deep learning and reinforcement learning.

    (3) Published a patent about anomaly detection.

    (4) Paper publication: AISTAR: an intelligent system for online IT ticket automation recommendation, BigData 2018.

  • IBM Thomas J. Watson Research Center, Research Intern at Cognitive Service Foundation Team, Yorktown Heights, NY, USA (May 2017 - July 2017)

    (1) Proposed and modeled the automation recommendation procedure of IT automation services as a contextual bandit problem with dependent arms, where the arms are organized in the form of hierarchies.

    (2) Paper publication: Online it ticket automation recommendation using hierarchical multi-armed bandit algorithms, SDM 2018.

  • IBM Thomas J. Watson Research Center, Research Intern at Cognitive Service Foundation Team, Yorktown Heights, NY, USA (June 2016 - August 2016)

    (1) Proposed and implemented an integrated framework for constructing the domain knowledge base, which is capable of extracting the domain informative phrases from unstructured text snippets.

    (2) Paper publication: Constructing the knowledge base for cognitive IT service management, IEEE SCC, 2017, Best Student Paper Award.

  • IBM SPSS, Software Engineering Intern, Xi'an, Shaanxi, China (August 2011 - June 2012)

    Designed and implemented an automatic testing framework for CADS platform using IBM Rational Functional Tester. This framework can help customizing test cases with XML configuration file, and execute them automatically.

Service Activities

  1. Session Chair of L13 New Computational Models for Big Data, 2018 IEEE Big Data. (Dec.,2018).


  3. PC member 2020, CIKM, DSHealth, DLG.

  4. PC member 2021, AAAI.


  1. "An Integrated Solution for Ontology-based Ticket Recommendation Using Problem Inference,” IBM Intern Workshop, Yorktown Heights, NY, Jun. 20-23, 2016.

  2. “STAR: A System for Ticket Analysis and Resolution,” SIGKDD, Halifax, Canada, Aug.13-17, 2017.

  3. "Taking Digital Service by Storm: from Traditional AI to Deep AI", 'Five Minute Madness' presentation, 2019 IBM Northeast Region Academy Affiliates Face-to-Face Meeting. (Jun.,2019).


Journal Articles
  1. Qifeng Zhou, Xiang Liu, Qing Wang " Interpretable Sentence Pair Models Based on Attention Mechanism ", Information Sciences, 2020. [pdf]

  2. Qing Wang, Chunqiu Zeng, Wubai Zhou, Tao Li, S. S. Iyengar, Larisa Shwartz, Genady Y. Grabarnik " Online Interactive Collaborative Filtering Using Multi-armed Bandit with Dependent Arms ", In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018. [pdf]

  3. Hongjun Li, Biao Cai, Shaojie Qiao, Qing Wang, Yan Wang " ExTCKNN: Expanding Tree-based Continuous K Nearest Neighbor Query in Road Networks with Traffic Rules ", In IEEE Access, 2018.

  4. Tao Li, Chunqiu Zeng, Wubai Zhou, Wei Xue, Yue Huang, Zheng Liu, Qifeng Zhou, Bin Xia, Qing Wang, Wentao Wang, Xiaolong Zhu "FIU-Miner (A Fast, Integrated, and User-Friendly System for Data Mining) and Its Applications", In Knowledge and Information Systems(KAIS), 2016.
Conference Papers
  1. Pooja Aggarwal, Ajay Gupta, Prateeti Mohapatra, Seema Nagar, Atri Mandal,Qing Wang, Amit Paradkar "Localization of Operational Faults in Cloud Applications by Mining Causal Dependencies in Logs using Golden Signals", AIOPs of the 18th International Conference on Service-Oriented Computing (ICSOC 2020).

  2. Qing Wang, Larisa Shwartz, Genady Ya. Graharnik, Michael Nidd, Jinho Hwang, "Leveraging AI in Service Automation Modeling: from Classical AI Through Deep Learning to Combination Models", the 17th International Conference on Service-Oriented Computing (ICSOC 2019). Springer, Toulouse, France, 2019. (acceptance rate:15%) [pdf]

  3. Kaylin Hagopian, Qing Wang, Yupeng Gao, Tengfei Ma, Lingfei Wu."" Learning Logical Representations from Natural Languages with Weak Supervision and Back Translation", " Knowledge Representation & Reasoning Meets Machine Learning Workshop at NeurIPS, Vancouver, Canada, 2019.

  4. Qing Wang, Chunqiu Zeng, S. S. Iyengar, Tao Li, Larisa Shwartz, Genady Ya. Graharnik, "AISTAR: An Intelligent Integrated System for Online IT Ticket Automation Recommendation", In the proceedings of the 6th annual IEEE International Conference on Big Data (IEEE BigData 2018), Seattle, WA, USA 2018.[pdf]

  5. Qing Wang, S. S. Iyengar, Tao Li, Larisa Shwartz, Genady Ya. Graharnik "Online IT automation recommendation Using Hierarchical Multi-armed Bandit Algorithms", SIAM International Conference on Data Mining (SDM), 2018.[pdf] [ppt]

  6. Wubai Zhou, Wei Xue, Ramesh Baral, Qing Wang, Chunqiu Zeng, Tao Li, Jian Xu, Zheng Liu, Larisa Shwartz, Genady Ya.Grabarnik, "STAR: A System for Ticket Analysis and Resolution", In the proceedings of the 23nd annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017.

  7. Wei Xue, Wubai Zhou, Tao Li, Qing Wang, "MTNA: A Neural Multi-Task Model for Aspect Category Classification and Aspect Term Extraction on Restaurant Reviews ", In the proceeding of the 8th International Joint Conference on Natural Language Processing (IJCNLP), 2017.

  8. Qing Wang, Wubai Zhou, Chunqiu Zeng, Tao Li, Larisa Shwartz, Genady Ya.Grabarnik, "Constructing the Knowledge Base for Cognitive IT Service Management ", In the proceedings of the 14th IEEE International Conference on Services Computing (SCC), 2017. [Best Student Paper Award] [ppt]

  9. Chunqiu Zeng, Qing Wang, Wentao Wang, Tao Li, Larisa Shwartz, " Online Inference for Time-Varying Temporal Dependency Discovery from Time Series ", In the proceedings of the 4th annual IEEE International Conference on Big Data(IEEE Big Data), 2016. Regular Research Paper (acceptance rate: 18.68%)
  10. Tao Li, Wubai Zhou, Chunqiu Zeng, Qing Wang, Qifeng Zhou, Dingding Wang, Jia Xu, Yue Huang, Wentao Wang, Minjing Zhang, Steve Luis, Shu-Ching Chen, Naphtali Rishe, "DI-DAP: An Efficient Disaster Information Delivery and Analysis Platform in Disaster Management", In Proceedings of the 25th ACM Conference on Information and Knowledge Management (CIKM 2016), Indianapolis, US, Oct.2016. Full paper at industrial track(acceptance rate:22/111=19.8%)

  11. Chunqiu Zeng, Qing Wang, Shekoofeh Mokhtari, Tao Li,"Online Context-Aware Recommendation with Time Varying Multi-Armed Bandit ", In the proceedings of the 22nd annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016. Research Track (acceptance rate:142/784=18%) [pdf,video].

Selected Patents
  1. A system and method to assess technical risk in IT service management using visual pattern recognition, 2018.
  2. A system and method to automatically map operational records without configuration information to topology graph, 2019.
  3. A system and method for just in time assembly of transaction for micro-services system, 2019.
  4. A system and method for Interactive Diagnosis of an Issue Through Collective Intelligence, 2020.


  1. IBM Research Accomplishment Award. (Dec., 2019).

  2. NIPS Travel Award. (Dec., 2019).

  3. FIU Overall Outstanding Graduate Student Award. (Nov., 2018)

  4. FIU GPSC Student Travel Award. (Nov., 2018).

  5. FIU Dissertation Year Fellowship. (Aug., 2018 - Aug., 2019)

  6. DiDi Beijing-IEEE Future Elite Forum Invitation. (May. 10-11, 2018)

  7. SIAM Student Travel Award. (May., 2018).

  8. SIGKDD Student Travel Award. (Jul., 2017).

  9. FIU GPSC Student Travel Award. (Jul., 2017).

  10. IEEE SCC Best Student Paper Award. (Jun., 2017)

  11. The Winner of Poster Presentation in Engineering Computing of GSAW 2017 Scholarly Forum. (Mar., 2017)