複製鏈接
請複製以下鏈接發送給好友
https://baike.baidu.hk/item/王志傑/57216766
複製
複製成功

王志傑

（重慶大學副教授、博士生導師）

鎖定
王志傑於上海交通大學計算機科學與工程系獲博士學位，現為重慶大學計算機學院副教授、博士生導師。他曾在中山大學、香港理工大學等機構從事科學研究工作。近年來，他在IEEE TKDE、IEEE TPDS、IEEE TALSP、IEEE TMM、IEEE TCSS、IEEE TSUSC、IJCAI、AAAI、ICDM、ECAI等多個期刊和會議發表論文。他是多個國際期刊和會議特邀審稿人，包括IEEE TKDE, IEEE TMM, IEEE TBD, IEEE TVT, IEEE TGCN, ACM TODS, Geoinformatica, VLDB, ICDE, AAAI，IJCAI, MDM, SmartData, NDBC等。他曾/現擔任中國計算機學會大數據專委會通訊委員、中國計算機學會數據庫專委會通訊委員、中國計算機學會廣東YOCSEF委員、廣東省大數據專委會委員、國家自然科學基金廣東聯合基金重點項目子課題負責人，國家自然科學基金面上項目負責人。他作為課題骨幹參與了國家重點研發計劃、國家自然科學基金青年科學基金項目等多個國家級和省部級科研項目，曾獲IEEE ICPADS優秀學生論文獎，廣東省計算機學會優秀論文獎。他的主要研究興趣為大數據、人工智能、數據挖掘等。 [1] 
中文名
王志傑
畢業院校
上海交通大學
學位/學歷
博士
職    業
教師
專業方向
大數據、人工智能、數據挖掘
任職院校
重慶大學

目錄

  1. 1 研究方向
  2. 2 學術成果
  3. ▪ 論文
  4. ▪ 項目

王志傑研究方向

大數據、人工智能、數據挖掘 [1] 

王志傑學術成果

王志傑論文

1. Y. Xu, B. Yao, Z. Wang, X. Gao, J. Xie, M. Guo. Skia: Scalable and Efficient In-Memory Analytics for Big Spatial-Textual Data. IEEE Transactions on Knowledge and Data engineering (TKDE), doi: 10.1109/TKDE.2019.2915828.
2. Y. Le, Z. Wang, Z. Quan, J. He, B. Yao. ACV-tree: A New Method for Sentence Similarity Modeling. The 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018, Stockholm, Sweden.
3. J. Yin, C. Gan, K. Zhao, X. Lin, Z. Quan, Z. Wang. A Novel Model for Imbalanced Data Classification. The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020, New York, USA.
4. W. Liu, Z. Wang, B. Yao, J. Yin. Geo-ALM: POI Recommendation by Fusing Geographical Information and Adversarial Learning Mechanism. The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019, Macao, China.
5. Z. Quan, Z. Wang, T. Ye, S. Guo. Task Scheduling for Energy Consumption Constrained Parallel Applications on Heterogeneous Computing Systems.IEEE Transactions on Parrallel and Distributed Systems (TPDS), 2020, 31(5): 1165-1182.
6. Z. Chen, B. Yao, Z. Wang, X. Gao, S. Shang, S. Ma, M. Guo. Flexible Aggregate Nearest Neighbor Queries and its Keyword-Aware Variant on Road Networks. IEEE Transactions on Knowledge and Data engineering (TKDE), doi: 10.1109/TKDE.2020.2975998.
7. M. Nie, Z. Wang, C. Gan, Z, Quan, B. Yao, J. Yin. An Improved Hierarchical Datastructure for Nearest Neighbor Search. The 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019, poster, Honolulu, Hawaii, USA.
8. Z. Wang, D. Wang, B. Yao, M. Guo. Probabilistic Range Query over Uncertain Moving Objects in Constrained Two-dimensional Space. IEEE Transactions on Knowledge and Data engineering (TKDE), 2015, 27(3), 866-879.
9. X. Lin, Z. Wang, Z. Quan, T. Jiang, X. Zeng. KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction. The 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020.
10. X. Lin, Z. Wang, L. Ma, X. Wu. Saliency Detection via Multi-Scale Global Cues. IEEE Transactions on Multimedia (TMM), 2019, 21(7): 1646-1659.
11. X. Lin, L. Ma, B. Sheng, Z. Wang, W. Chen. Utilizing Two-phase Processing with FBLS for Single Image deraining. IEEE Transactions on Multimedia (TMM), doi:10.1109/TMM.2020.2987703.
12. Z. Quan, Z. Wang, Y. Le, B. Yao, K. Li, J. Yin. An Efficient Framework for Sentence Similarity Modeling.
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 2019, 27(4):853-865.
13. Z. Chen, B. Yao, Z. Wang, W. Zhang, K. Zheng, P. Kalnis, F. Tang. ITISS: An Efficient Framework for Querying Big Temporal Data. Geoinformatica, 2020, 24 (1): 27-59.
14. Z. Wang, B. Yao, R. Cheng, X. Gao, L. Zou, H. Guan, M. Guo. SMe: Explicit & Implicit Constrained-Space Probabilistic Threshold Range Queries for Moving Objects. Geoinformatica, 2016, 20(1): 19-58.
15. Z. Wang, X. Lin, M. Fang, B. Yao, Y. Peng, H. Guan, M. Guo. RE2L: An Efficient Output-sensitive Algorithm for Computing Boolean Operations on Circular-arc Polygons and Its Applications. Computer-Aided Design (CAD), 2017, 83(2):1-14.
16. X. Lin, K. Zhao, T. Xiao, Z. Quan, Z. Wang, P. S. Yu. DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Prediction. The 24th European Conference on Artificial Intelligence (ECAI), 2020.
17. T. Xiao, Z. Wang, Z. Quan, K. Zhao, X. Liao. LPV: A Log Parser Based on Vectorization for Offline and Online Log Parsing. The 20th IEEE International Conference on Data Mining (ICDM), 2020, Sorrento, Italy.
18. X. Lin, Z. Quan, Z. Wang, H. Huang, X. Zeng. A Novel Molecular Representation with BiGRU Neural Networks for Learning Atoms. Breifings in Bioinformaitics (BIB), doi: 10.1093/bib/bbz125.
19. D. Yang, J. Guo, Z. Wang, Y. Wang, J. Zhang, L. Hu, J. Yin, J. Cao. FastPM: An Approach to Pattern Matching via Distributed Stream Processing. Information Sciences (INS), 2018, 453: 263-280.
20. X. Lin, Z. Wang, X. Tan, M. Fang, L. Ma, N. Xiong. MCCH: A Novel Convex Hull-Based Prior Method for Saliency Detection. Information Sciences (INS), 2019, 485: 521-539.
21. M. Nie, Z. Wang, J. Yin, B. Yao. Reachable Region Query and Its Applications. Information Sciences (INS), 2019, 476:95-105.
22. H. Liu, L. Yang, J. Ding, Y. Guo, X. Xie, Z. Wang. Scalable Tensor-Train-Based Tensor Computations for Cyber-Physical-Social Big Data. IEEE Transactions on Computational and Social Systems (TCSS), doi:10.1109/TCSS.2019.2957337.
23. J. Zhang, Z. Wang, K. Wang, S. Guo, B. Wang, M. Guo. Improving Power Efficiency for Online Video Streaming Service: A Self-Adaptive Approach. IEEE Transactions on Sustainable Computing (TSUSC), short, 2019, 4(3): 308-313.
24. M. Zeng, B. Yao, Z. Wang, Y. Shen, F. Li, J. Zhang, H. Lin, M. Guo. CATIR: An Efficient Method for Content-and-Text Based Image Retrieval. Journal of Computer Science and Technology (JCST), 2019, 34(2): 287-304.
25. Z. Quan, Y. Guo, X. Lin, Z. Wang, X. Zeng. GraphCPI: Graph Neural Representation Learning for Compound-Protein Interaction. IEEE International Conference on Bioinformatics & Biomedicine (BIBM), 2019, San Diego, California, USA.
26. Z. Wang, Z. Quan, Z. Wang, X. Hu, Y. Chen. Text To Image Synthesis with Bidirectional Generative Adversarial Network. IEEE International Conference on Multimedia & Expo (ICME),oral, 2020, London, United Kingdom.
27. W. Liu, Z. Wang, B. Yao, M. Nie, J. Wang, R. Mao and J. Yin. Geographical Relevance Model for Long Tail Point-of-Interest Recommendation. The 23rd International Conferfence on Database Systems for Advanced Applications (DASFAA), 2018, Gold Coast, Queensland, Australia.
28. Z. Quan, X. Lin, Z. Wang, Yan Liu, F. Wang, K. Li. A System for Learning Atoms Based on Long Short-Term Memory Recurrent Neural Networks. IEEE International Conference on Bioinformatics & Biomedicine (BIBM), 2018, Madrid, Spain.
29. Z. Wang, L. Ma, X. Lin, H. Zhong. Saliency Detection via Multi-Center Convex Hull Prior. The 43rd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2018, Calgary, Canada.
30. B. Yao, W. Zhang, Z. Wang, Z. Chen, S. Shang, K. Zheng, M. Guo. Distributed In-memory Analytics for Big Temporal Data. The 23rd International Conference on Database Systems for Advanced Applications (DASFAA),2018,Gold Coast, Queensland, Australia.
31. Z. Wang, L. Ma, X. Lin, X. Wu. MSGC: A New Bottom-Up Model for Salient Object Detection. IEEE International Conference on Multimedia & Expo (ICME), oral, 2018, San Diego, California, USA.
32. H. Hu, S. Qian, J. Cao, J. Yu, G. Xue, Y. Zhu, M. Li, Z. Wang. Optimizing The Waiting Time of Sensors in A MANET to Strike A Balance between Energy Consumption and Data Timeliness. The 25th IEEE International Conference on Parallel and Distributed Systems (ICPADS), 2019, Tianjin, China. [1] 

王志傑項目

1. 國家自然科學基金面上項目, “Query Processing for Moving Objects in Obstructed Space”，負責人（PI）
2. 國家自然科學基金廣東聯合基金重點項目, “Acquisition, Management and Knowledge Construction of Educational Big Data”，共同負責人(Co-PI).
3. 國家重點研發計劃, “High Efficient and Scalable Big Data Computing Model, Optimization Technology and System”, 參與人 (Participant).
4. 重慶大學引進人才科研啓動基金, 負責人 (PI).
5. 國家自然科學基金青年基金, “Incremental Format Inference from Ad Hoc Data”, 參與人 (Participant). [1] 
參考資料