卓漢逵

卓漢逵，男，博士，中山大學信息科學與技術學院計算機系講師。

基本介紹

  • 中文名：卓漢逵
  • 畢業院校：中山大學、港科技大學
  • 學位/學歷：博士
  • 職業：教師
  • 性別：男
研究領域,人物經歷,教育經歷,工作經歷,海外經歷,所獲榮譽,學術兼職,教授課程,學術成果,科研項目,代表性論著,

研究領域

人工智慧、智慧型規劃、機器學習/數據挖掘。

人物經歷

教育經歷

  • 2004.9-2009.6，中山大學信息科學與技術學院計算機系/香港科技大學計算機科學與工程系(聯合培養)，博士
  • 2000.9-2004.6，中山大學信息科學與技術學院計算機系，本科

工作經歷

  • 2016.7至今，先進網路與計算系統研究所 副所長
  • 2014.1至今， 中山大學數據科學與計算機學院，副教授
  • 2009.9-2013.12，中山大學信息科學與技術學院計算機系，講師

海外經歷

  • 2015.4-2015.10，美國亞利桑那州立大學，訪問學者
  • 2013.5-2014.5，香港諾亞方舟實驗室/香港科技大學，訪問學者
  • 2012.2-2013.2，美國亞利桑那州立大學，博士後
  • 2007.10-2009.12，香港科技大學計算機科學與工程系，研究助理/博士後

所獲榮譽

  • 廣東省特支計畫科技創新青年拔尖人才
  • 廣東省傑出青年
  • 廣州市珠江科技新星

學術兼職

  • 國際智慧型規劃與調度頂級會議ICAPS, Conference Co-chair, 2021
  • 國際人工智慧協會AAAI Senior PC, 2020
  • 國際人工智慧頂級會議IJCAI Senior PC, 2019
  • 國際智慧型規劃與調度頂級會議ICAPS Sponsorship co-chair，2019
  • 國際人工智慧頂級會議IJCAI展示分會Co-Chair，2016
  • 國際人工智慧頂級會議IJCAI程式委員會資深委員，2013至今
  • 國際人工智慧協會AAAI 委員會委員，2012至2019
  • 國際智慧型規劃頂級會議ICAPS程式委員會委員，2012至今

教授課程

  • 凸最佳化（本科）
  • 智慧型算法及套用（本科）
  • 人工智慧 (本科)
  • 機器學習 (本科)
  • 資料庫 (本科)
  • 人工智慧（研究生）

學術成果

科研項目

  1. 企事業單位委託科技項目、基於人機融合智慧型規劃的智慧型製造平台研究與開發、2018.5-2020.5、310萬元、在研、主持。
  2. 廣東省傑出青年基金、基於大數據遷移學習和馬爾可夫邏輯網路的規劃識別算法研究、2017.5-2021.5、100萬元、在研、主持。
  3. 廣東省發展和改革委員會、大數據時代下價格行政執法智慧型輔助決策研究、2017.7-2018.7、20萬元、在研、主持。
  4. 國家自然科學基金廣東省聯合基金重點項目課題，U1611262，基於多模態大數據分析方法的肛腸疾病臨床診斷標準及演化模型研究，2017/01-2020/12，225萬元，在研、主持。
  5. 廣州市珠江新星、201710010196，基於大數據遷移學習和約束可滿足的行為識別算法研究，2017/05-2020/04，30萬元，在研，主持。
  6. 國家自然科學基金青年基金、基於Markov邏輯網路的HTN模型獲取算法、2014/01-2016/12、27萬元、結題、主持。
  7. 廣東省自然科學基金博士啟動項目、智慧型規劃中不確定性動作模型的自動獲取研究、2011/10-2013/10、3萬元、結題、主持。
  8. 企事業單位委託科技項目、接入晶片配套工具開發項目、2011/12-2013/12、36.86萬元、結題、主持。
  9. 廣東省殘疾人聯合會、盲人電腦語音輔助系統的研究與實現、2014/7-2018/7、240萬元、在研、主持。
  10. 教育部高校基本科研業務費青年教師重點培育項目、基於智慧型規劃和感測器的行為識別、2014/01-2015/12、30萬元、結題、主持。
  11. 廣州市科技計畫項目、國產雲資料庫管理系統EBASE IV的研究與套用、2011/10-2014/09、30萬元、結題、主持。
  12. 企事業單位委託科技項目、惠州市社保基金電子監察平台設計與開發、2010/12-2016/12、290.6 萬元、結題、主持。
  13. 企事業單位委託科技項目、廣西圖書裝備管理雲平台建設項目、2014/7-2015/12、80萬元、結題、主持。
  14. 企事業單位委託科技項目、基於大數據的推薦系統研究與實現、2013/08-2014/08、35萬元、結題、主持。

代表性論著

期刊論文
  • Hankz Hankui Zhuo, Qiang Yang, Derek Hao Hu and Lei Li. Learning Complex Action Models with Quantifiers and Logical Implications. Artificial Intelligence Journal (AIJ), 174(18), 1540-1569, 2010.
  • Qiang Yang, Vincent W. Zheng, Bin Li and Hankz Hankui Zhuo. Transfer Learning by Reusing Structured Knowledge. AI Magazine 32(2), 95-106, 2011.
  • 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. Vol.19, No.4, 2012.
  • Hankz Hankui Zhuo, Hector Muñoz-Avila and Qiang Yang. Learning Hierarchical Task Network Domains from Partially Observed Plan Traces. Artificial Intelligence Journal (AIJ), Jul 2014.
  • Hankz Hankui Zhuo, Qiang Yang. Action-Model Acquisition for Planning via Transfer Learning. Artificial Intelligence Journal (AIJ), Jul 2014.
  • 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)
  • Hankz Hankui Zhuo, Subbarao Kambhampati. Model-Lite Planning: Case-Based vs. Model-Based Approaches. Artificial Intelligence. Volume 246, May 2017, Pages 1–21.
  • Hankz Hankui Zhuo. Recognizing Multi-Agent Plans When Action Models and Team Plans Are Both Incomplete. ACM Transactions on Intelligent Systems and Technology: 30:1-30:24 (2019). (ranked as one of the best journals in all ACM journals in terms of citations received per paper)
  • Hankz Hankui Zhuo, Yantian Zha, Subbarao Kambhampati, Xin Tian. Discovering Underlying Plans Based on Shallow Models. ACM Transactions on Intelligent Systems and Technology. major revision. 2019. (ranked as one of the best journals in all ACM journals in terms of citations received per paper)
會議論文
  • Min Tang, Jiaran Cai, Hankz Hankui Zhuo. Multi-Matching Network for Multiple Choice Reading Comprehension. AAAI 2019: 7088-7095
  • Hankz Hankui Zhuo, Wenfeng Feng, Qian Xu, Qiang Yang, Yufeng Lin. Federated Reinforcement Learning. CoRR abs/1901.08277 (2019)
  • Feng Liao, Hankz Hankui Zhuo, Xiaoling Huang, Yu Zhang. Federated Hierarchical Hybrid Networks for Clickbait Detection. CoRR abs/1906.00638(2019)
  • Zhanhao Xiao, Hai Wan, Hankz Hankui Zhuo, Jinxia Lin, Yanan Liu. Representation Learning for Classical Planning from Partially Observed Traces. CoRRabs/1907.08352 (2019)
  • Yuncong Li (M. Phil Student), Hankz Hankui Zhuo. An HIPS System: Human-in-the-Loop Planning Based on MAXSAT. ICAPS demonstration track. 2018.
  • Wenfeng Feng (M. Phil Student), Hankz Hankui Zhuo, Subbarao Kambhampati. Extracting Action Sequences from Texts Based on Deep Reinforcement Learning. IJCAI, 2018.
  • Mingmin Jin (M. Phil Student), Xin Luo, Huiling Zhu, Hankz Hankui Zhuo. Integrating Deep Learning and Topic Modeling in Context-Aware Recommendation. NAACL. 2018.
  • Chuantao Zong (M. Phil Student), Wenfeng Feng (M. Phil Student), Vincentz Wenchen Zheng Hankz Hankui Zhuo. Adaptive Attention Network for Review Sentiment Classification. PAKDD. 2018.
  • Mengya Wang (M. Phil Student), Erhu Rong (M. Phil Student), Hankz Hankui Zhuo, Huiling Zhu. Embedding Knowledge Graphs Based on Transitivity and Antisymmetry of Rules. PAKDD. 2018.
  • Han Tian (M. Phil Student), Hankz Hankui Zhuo. Paper2vec: Citation-Context Based Document Distributed Representation for Scholar Recommendation. 2017.
  • Junhua He (M. Phil Student), Hankz Hankui Zhuo, Jarvan Law. Distributed-Representation Based Hybrid Recommender System with Short Item Descriptions. 2017.
  • Mengya Wang (M. Phil Student), Hankz Hankui Zhuo, Huiling Zhu. Embedding Knowledge Graphs Based on Transitivity and Antisymmetry of Rules. 2017.
  • 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.
  • 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.
  • Hankz Hankui Zhuo. Human-Aware Plan Recognition. AAAI 2017.
  • Xin Tian, Hankz Hankui Zhuo, Subbarao Kambhampati. Discovering Underlying Plans Based on Distributed Representations of Actions. PDF. (Best Student Paper Nomination)
  • 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.
  • Hankz Hankui Zhuo. Crowdsourced Action-Model Acquisition for Planning. AAAI 2015: 3439-3446
  • Hankz Hankui Zhuo and Subbarao Kambhampati. Action-Model Acquisition from Noisy Plan Traces. International Joint Conference on Artificial Intelligence (IJCAI-13), 2444-2450, 2013.
  • 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.
  • 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.
  • 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.
  • Hankz Hankui Zhuo, Qiang Yang and Subbarao Kambhampati. Action-Model based Multi-agent Plan Recognition. Neural Information Processing Systems (NIPS-12). 377-385, 2012.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.

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