Qing WANG
Honorary Research Associate BS(Zhengzhou); ME(Xidian); PhD(Florida) Office : Run Run Shaw Building Email : qwang1@hku.hk

Ph.D. in Computer Science, Florida International University, Miami, FL, U.S.A.
M.E. in Computer Science, Xidian University, Xi’an, Shaan’xi, China.
B.S. in Computer Science, Zhengzhou University, Zhengzhou, Henan, China.

 

Research Interests

Large-Scale Data Mining; Machine Learning; Multi-armed Bandits; Causality Inference; Large Language Models; Reinforcement Learning

Honors

1. IBM Research Accomplishment Award (Watson AIOps). (Nov., 2021)

2. IBM Outstanding Technical Achievement Award. (May, 2021)

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

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

5. IEEE SCC Best Student Paper Award. (Jun. 2017)

Publications

Journal Articles

1. Qing Wang " Intelligent Data Mining Techniques for Automatic Service Management. " Dissertation, 2018.

2. Qing Wang " Quantum Neural Networks: Research and Applications in Weather Prediction. " Thesis, 2013.

3. 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.

4. Qifeng Zhou, Xiang Liu, Qing Wang " Interpretable Duplicate Question Detection Models based on Attention Mechanism ", Information Sciences, 2020.

5. 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.

1. Xinxi Jiang, Xiang Li, Qifeng Zhou, Qing Wang, "GRACE: Generating Cause and Effect of Disaster Sub-Events from Social Media Text", The 2024 ACM Web Conference (WWW-24), Singapore, Singapore, 2024.

2. Shen Yang, Qifeng Zhou, Qing Wang, "Clustering of Bandit with Frequence-Dependent Information Sharing", 45th European Conference on Information Retrieval (ECIR-23), Dublin, Ireland, 2023.

3. Qing Wang, Jesus Rios Aliaga, Karthikeyan Shanmugam, et. al "Fault Injection based Interventional Causal Learning for Distributed Applications", 37th AAAI Conference on Artificial Intelligence (AAAI-23), 2023.

4. Qing Wang " The Use of Bandit Algorithms in Intelligent Interactive Recommender Systems, " arXiv preprint arXiv:2107.00161, 2021.

5. Qing Wang, et. al "Detecting Causal Structure on Cloud Application Microservices Using Granger Causality Models", 14th International Conference on Cloud Computing (IEEE CLOUD 2021).

6. Pooja Aggarwal, Seema Nagar, Ajay Gupta, Larisa Shwartz, Prateeti Mohapatra, Amit Paradkar, Qing Wang, Atri Mandal, "Causal Modeling based Fault Localization in Cloud Systems using Golden Signals", 14th International Conference on Cloud Computing (IEEE CLOUD 2021).

7. Jinhon Hwang, Larisa Shwartz, Qing Wang, Raghav Batta, Harshit Kumar and Michael Nidd "FIXME: Enhance Software Reliability with Hybrid Approaches in Cloud", 43rd International Conference on Software Engineering. (ICSE SEIP 2021).

8. Vijay Arya, Karthikeyan Shanmugam, Pooja Aggarwal, Qing Wang, Prateeti Mohapatra and Seema Nagar "Evaluation of Causal Inference Techniques for AIOps", 8th ACM IKDD CODS and 26th COMAD (CODS-COMAD 2021).

9. 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).

10. 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.

11. 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.

12. 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.

13. 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.

14. 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.

15. 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.

16. 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]

17. 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.

18. 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.

19. 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.

1. Graph Grammar Learning for Automatic Circuit Generation, filed with IBM in 2025.

2. Anomaly Detection Using Event Sequence Prediction, filed with IBM in 2024.

3. Fault localization in a distributed computing system, 2025.

4. Shiftleft topology construction and information augmentation using machine learning, 2025. [High Value Patent]

5. Just in time assembly of transactions, 2024.

6. Learning Causal Relationships, 2023.

7. Transformation of data from legacy architecture to updated architecture, 2023.

8. Synthetic system fault generation, 2023.

9. Automatic mapping of records without configuration information, 2023.

10. Computing system event error corrective action recommendation, 2022.

11. Linking operational events with system changes, 2022.

12. Application topology discovery, 2022. [High Value Patent]

13. Cross-Environment Event Correlation Using Domain-Space Exploration and Machine Learning Techniques, 2022. [High Value Patent]

14. Assessing technical risk in information technology service management using visual pattern recognition, 2022.

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Robotics for IT Management

 

The video was taken in summer of 2017, at IBM T.J Watson Research Center. It was an intern project about robotics for IT Management. and it was used to propagate this project.