1. Wenfeng Feng, Hankz Hankui Zhuo, Subbarao Kambhampati. Extracting Action Sequences from Texts Based on Deep Reinforcement Learning. arXiv:1803.02632, 2018

  2. Hankz Hankui Zhuo, Yantian Zha & Subbarao Kambhampati. Discovering Underlying Plans Based on Shallow Models. ArXiv:1803.02208, 2018

  3. Jin Mingmin (M. Phil Student), Mengya Wang (M. Phil Student), Chuantao Zong (M. Phil Student), Hankz Hankui Zhuo and Zhu Huiling. Combining Deep Learning and Topic Modeling for Review Understanding in Context-Aware Recommendation. NAACL 2018. accepted.

  4. Chuantao Zong (M. Phil Student), Wenfeng Feng (M. Phil Student), Vincent W. Zheng, Hankz Hankui Zhuo. Adaptive Attention Network for Review Sentiment Classification. PAKDD 2018. accepted.

  5. Mengya Wang (M. Phil Student), Erhu Rong, Hankz Hankui Zhuo, Huiling Zhu. Embedding Knowledge Graphs Based on Transitivity and Antisymmetry of Rules. PAKDD 2018. accepted.

  6. Han Tian (M. Phil Student), Hankz Hankui Zhuo. Paper2vec: Citation-Context Based Document Distributed Representation for Scholar Recommendation. 2017. https://arxiv.org/abs/1703.06587

  7. Junhua He (M. Phil Student), Hankz Hankui Zhuo, Jarvan Law. Distributed-Representation Based Hybrid Recommender System with Short Item Descriptions. 2017. https://arxiv.org/abs/1703.04854

  8. Mengya Wang (M. Phil Student), Hankz Hankui Zhuo, Huiling Zhu. Embedding Knowledge Graphs Based on Transitivity and Antisymmetry of Rules. 2017. https://arxiv.org/abs/1702.07117

  9. Jarvan Law (M. Phil Student), Hankz Hankui Zhuo, Junhua He, Erhu Rong: LTSG: Latent Topical Skip-Gram for Mutually Learning Topic Model and Vector Representations. 2017. https://arxiv.org/abs/1702.07543

  10. Y. Zhang, S. Sreedharan, A. Kulkarni, T. Chakraborti, Hankz Hankui. Zhuo, S. Kambhampati. Plan Explicability and Predictability for Robot Task Planning. in Proceedings of IEEE International Conference on Robotics and Automation (ICRA), 2017.

  11. Hankz Hankui Zhuo and Subbarao Kambhampati. Model-Lite Planning: Case-Based vs. Model-Based Approaches. Artificial Intelligence. Volume 246, May 2017, Pages 1–21. http://www.sciencedirect.com/science/article/pii/S000437021730005X

  12. Hankz Hankui Zhuo. Human-Aware Plan Recognition. AAAI 2017. [pdf].

  13. Xin Tian, Hankz Hankui Zhuo, Subbarao Kambhampati. Discovering Underlying Plans Based on Distributed Representations of Actions. PDF. (Best Student Paper Nomination) [video]

  14. Xiaomu Luo, Huoyuan Tan, Qiuju Guan, Tong Liu, Hankz Hankui Zhuo, Baihua Shen: Abnormal Activity Detection Using Pyroelectric Infrared Sensors. Sensors 16(6): 822 (2016)

  15. Jie Gao, Hankz Hankui Zhuo, Subbarao Kambhampati, and Lei Li. Crowdsourced Planning with Incomplete Initial-States and Action-Models. The Third AAAI Conference on Human Computation and Crowdsourcing (HCOMP-2015). Works-in-Progress paper. AAAI Press.

  16. Hankz Hankui Zhuo. Crowdsourced Action-Model Acquisition for Planning. AAAI 2015: 3439-3446. [PDF] 

  17. Hankz Hankui Zhuo, Hector Muñoz-Avila and Qiang Yang. Learning Hierarchical Task Network Domains from Partially Observed Plan Traces. Artificial Intelligence. volume 212, July 2014, Pages 134-157. http://dx. doi. org/10. 1016/j. artint. 2014. 04. 003

  18. Hankz Hankui Zhuo and Qiang Yang. Action-model acquisition for planning via transfer learning. Artificial Intelligence. volume 212, July 2014, Pages 80-103. http://dx. doi. org/10. 1016/j. artint. 2014. 03. 004

  19. Hankz Hankui Zhuo. Multi-Agent Plan Recognition from Partially Observed Team Traces. Book Chapter on Plan, Activity, and Intent Recognition Theory and Practice. Chapter 9. Elsevier press. Mar, 2014.

  20. Yueyun Jin, Weilin Zeng, Hankz Hankui Zhuo, and Lei Li. Ensemble of Unsupervised and Supervised Models with Different Label Spaces. ADMA (2) 2013: 466-477

  21. Kartik Talamadupula, Subbarao Kambhampati, Yuheng Hu, Tuan Nguyen, Hankz Hankui Zhuo. Herding the Crowd: Automated Planning for Crowdsourced Planning. In the First International Conference on Human Computation (HCOMP-13),AAAI Press,2013. [PDF]

  22. Hankz Hankui Zhuo. and Subbarao Kambhampati. Action-Model Acquisition from Noisy Plan Traces. International Joint Conference on Artificial Intelligence (IJCAI-13),2444-2450,2013. [PDF]

  23. Hankz Hankui Zhuo, Tuan Nguyen and Subbarao Kambhampati. Refining Incomplete Planning Domain Models Through Plan Traces. International Joint Conference on Artificial Intelligence (IJCAI-13),2451-2457,2013. [PDF] 

  24. Hankz Hankui Zhuo, Subbarao Kambhampati and Tuan Nguyen. Model-Lite Case-Based Planning. Association for the Advancement of Artificial Intelligence (AAAI-13). 1077-1083,2013. [PDF]

  25. Hankz Hankui Zhuo, Qiang Yang and Subbarao Kambhampati. Action-Model based Multi-agent Plan Recognition. Neural Information Processing Systems (NIPS-12). 377-385, 2012. [PDF]

  26. Daojun Han, Hankz Hankui Zhuo, Lanting Xia, Lei Li. Permission and Role Automatic Assigning of User in RBAC. Journal of Central South University of Technology (JCSUT). Vol. 19, No. 4, 2012.

  27. Jie Gao, Hankz Hankui Zhuo, Daojun Han, Lei Li. Learning Action Models with Indeterminate Effects. International Conference on Software Engineering and Knowledge Engineering (SEKE-11), Jul 7-9, 2011.

  28. Hankz Hankui Zhuo and Lei Li. Multi-agent Plan Recognition with Partial Team Traces and Plan Libraries. International Joint Conference on Artificial Intelligence (IJCAI-11), 484-489, 2011. [PDF]

  29. Qiang Yang, Vincent W. Zheng, Bin Li and Hankz Hankui Zhuo. Transfer Learning by Reusing Structured Knowledge. AI Magazine 32(2), 95-106, 2011. [PDF]

  30. Hankz Hankui Zhuo, Qiang Yang, Rong Pan and Lei Li. Cross-Domain Action-Model Acquisition for Planning via Web Search. International Conference on Automated Planning and Scheduling(ICAPS-11),298-305,2011.  [PDF]

  31. Hankz Hankui Zhuo, Hector Muñoz-Avila and Qiang Yang. Learning Action Models for Multi-Agent Planning. International Conference on Autonomous Agents and Multiagent Systems (AAMAS-11),217-224, 2011. [PDF]

  32. Hankz Hankui Zhuo, Qiang Yang, Derek Hao Hu and Lei Li. Learning Complex Action Models with Quantifiers and Logical Implications. Artificial Intelligence, 174(18), 1540-1569, 2010. http://dx. doi. org/10. 1016/j. artint. 2010. 09. 007. [PDF]

  33. Hankz Hankui Zhuo, Derek Hao Hu, Chad Hogg, Qiang Yang, Hector Muñoz-Avila. Learning HTN Method Preconditions and Action Models from Partial Observations. International Joint Conference on Artificial Intelligence (IJCAI-09),1804-1810,2009. [PDF]

  34. Hankz Hankui Zhuo, Qiang Yang, Lei Li. Constraint-Based Case-Based Planning Using Weighted MAX-SAT. International Conference on Case-Based Reasoning (ICCBR-09), 374-388, 2009.
    [PDF]

  35. Hankz Hankui Zhuo, Qiang Yang, Lei Li. Transfer Learning Action Models by Measuring the Similarity of Different Domains. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-09), 697-704,2009.
    [PDF]

  36. Hankz Hankui Zhuo, Derek Hao Hu, Qiang Yang, Hector Muñoz-Avila, Chad Hogg. Learning Applicability Conditions in AI Planning from Partial Observations. Learning Structural Knowledge from Observations (IJCAI workshop), 2009. [PDF]

  37. Hankz Hankui Zhuo, Qiang Yang, Derek Hao Hu, Lei Li. Transferring Knowledge from Another Domain for Learning Action Models. Pacific Rim International Conference on Artificial Intelligence (PRICAI-08),1110-1115,2008. [PDF]

  38. Hankz Hankui Zhuo, Lei Li, Qiang Yang, Rui Bian. Learning Action Models with Quantified Conditional Effects for Software Requirement Specification. International Conference on Intelligent Computing (ICIC-08), 874-881, 2008.

  39. Hankz Hankui Zhuo, Lei Li, Rui Bian, Hai Wan. Requirement Specification Based on Action Model Learning. International Conference on Intelligent Computing (ICIC-07), 565-574, 2007.