您现在的位置是: 刘驰

硕士生导师

姓名:刘驰
所在学科:计算机科学与技术
职称:教授、博士生导师
联系电话:13718763233
E-mail:chiliu@bit.edu.cn
通信地址:北京理工大学软件楼316

个人信息

        刘驰,教授、博士生导师、北京理工大学计算机学院副院长、国家优秀青年科学基金获得者、中国电子学会会士、英国工程技术学会会士(Fellow of IET)、 英国计算机学会会士(Fellow of British Computer Society)和英国皇家艺术学会会士(Fellow of Royal Society of Arts)。2006年本科于清华大学电子工程系,2010年博士毕业于英国帝国理工学院。后在美国IBM TJ Watson研究中心和IBM中国研究院任研究主管。主要研究方向是:大数据、人工智能和物联网技术。发表高水平SCI/EI论文百余篇,其中CCF-A类论文30余篇、ESI高被引论文5篇,授权国内外发明专利20余项,编著中英文书籍10本,Google Scholar统计引用5000余次,H index为32。获得省部级一等奖、二等奖、三等奖各1项。

       现任国家信息产业“十四五”规划专家顾问组成员、第四届全国信标委技术委员会委员、曾任中国工程院“十三五”战略性新兴领域高级咨询专家等。担任IEEE Transactions on Network Science and Engineering编辑(Associate Editor)、IEEE ICC 2020 Symposium Chair on Next Generation Networking、IEEE INFOCOM和IJCAI TPC。


科研方向

人工智能、物联网、大数据、边缘计算


代表性学术成果

CCF-A类论文:

[JSAC]. C. H. Liu*, Z. Chen, J. Tang, J. Xu, C. Piao, "Energy-Efficient UAV Control for Effective and Fair Communication Coverage: A Deep Reinforcement Learning Approach," IEEE Journal of Selected Areas in Communications, Vol:3, no:9, pp: 2059-2070, 2018. 高被引论文

[JSAC]. C. H. Liu*, Z. Chen, Y. Zhan, "Energy-Efficient Distributed Mobile Crowd Sensing: A Deep Learning Approach," IEEE Journal of Selected Areas in Communications, Volume: 37, Issue: 6, Page(s): 1262 – 1276, June 2019.

[TKDE]. C. H. Liu*, J. Xu, J. Tang and J. Crowcroft, "Social-aware Sequential Modeling of User Interests: A Deep Learning Approach," IEEE Transactions on Knowledge and Data Engineering, Volume: 31, Issue: 11, Page(s): 2200 – 2212, Nov. 1 2019.

[TKDE]. C. H. Liu*, Y. Wang, C. Piao, Z. Dai, Y. Yuan, G. Wang, D. Wu, "Time-Aware Location Prediction by Convolutional Area-of-Interest Modeling and Memory-Augmented Attentive LSTM," IEEE Transactions on Knowledge and Data Engineering, doi: 10.1109/TKDE.2020.3005735, June 2020.

[TKDE]. R. Han, C. H. Liu*, S. Li, L. Chen, G. Wang, J. Tang and J. Ye, “SlimML: Removing Non-critical Input Data in Large-scale Iterative Machine Learning,” IEEE Transactions on Knowledge and Data Engineering, Volume: 33, Issue: 5, Page(s): 2223-2236, May 2021.

[TMC]. C. H. Liu, X. Ma, X. Gao and J. Tang*, "Distributed Energy-Efficient Multi-UAV Navigation for Long-Term Communication Coverage by Deep Reinforcement Learning," in IEEE Transactions on Mobile Computing, Volume: 19, Issue:6, Page(s): 1274-1285, JUNE 2020

[TMC]. C. H. Liu*, Z. Dai, Y. Zhao, J. Crowcroft, D. Wu and K. K. Leung, "Distributed and Energy-Efficient Mobile Crowdsensing with Charging Stations by Deep Reinforcement Learning," in IEEE Transactions on Mobile Computing, Volume: 20, Issue: 1, Page(s): 130-146, January 2021.

[TMC]. H. Gao#, C. H. Liu*#, J. Tang, D. Yang, W. Wang, "Online Quality-Aware Incentive Mechanism Design for Mobile Crowdsensing with Extra Bonus," IEEE Transactions on Mobile Computing, Volume: 18, Issue: 11, Page(s): 2589 – 2603, Nov. 1 2019.

[TMC]. Y. Zhan, C. H. Liu*, Y. Zhao, J. Zhang and J. Tang, "Free Market of Multi-Leader Multi-Follower Mobile Crowdsensing: An Incentive Mechanism Design by Deep Reinforcement Learning," in IEEE Transactions on Mobile Computing, Volume: 19, Issue: 10, Page(s): 2316 - 2329, July 2019.

[TMC]. D. Wu, D. I. Arkhipov, Y. Zhang, C. H. Liu, A. Regan, "Online War-driving by Compressive Sensing," IEEE Transactions on Mobile Computing, Vol:14, no: 11, pp:2349-2362, 2014.

[TMC]. L. Wang, Z. Yu, D. Zhang, B. Guo, C. H. Liu, "Heterogeneous Multi-Task Assignment in Mobile Crowdsensing Using Spatiotemporal Correlation," IEEE Transactions on Mobile Computing, Vol:18, no: 1, pp:84-97, 2019.

[TPAMI]. S. Li, C. H. Liu*, Q. Lin, Q. Wen, L. Su, G. Huang, Z. Ding, "Deep Residual Correction Network for Partial Domain Adaptation," in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol:43, no: 7, pp: 2329-2344, July 2021.

[TPAMI]. S. Li, B. Xie, Q. Lin, C. H. Liu, G. Huang, and G. Wang, “Generalized Domain Conditioned Adaptation Network,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, doi: 10.1109/TPAMI.2021.3062644, 01 March 2021.

[TPDS]. R. Han, C. H. Liu*; Z. Zong, L. Y. Chen, W. Liu, S. Wang, J. Zhan, "Workload-adaptive Configuration Tuning for Hierarchical Cloud Schedulers," in IEEE Transactions on Parallel and Distributed Systems, Volume: 30, Issue:12, Page(s): 2879-2895, DECEMBER 2019.

[TPDS]. R. Han, S. Li, X. Wang, C. H. Liu*, G. Xin, L. Y. Chen, “Accelerating Gossip-based Deep Learning in Heterogeneous Edge Computing Platforms,” in IEEE Transactions on Parallel and Distributed Systems, Volume: 32, Issue: 7, Page(s): 1591-1602, July 2021.

[TPDS]. R. Han, D. Li, J. Ouyang, C. H. Liu*, G. Wang, D. Wu, L. Y. Chen, “Accurate Differentially Private Deep Learning on the Edge,” in IEEE Transactions on Parallel and Distributed Systems, Volume: 32, Issue: 9, Page(s): 2231-2247, SEPTEMBER 2021.

[TC]. R. Han, C. H. Liu*, S. Li, S. Wen, and X. Liu, “Accelerating Deep Learning Systems via Critical Set Identification and Model Compression,” IEEE Transactions on Computers, vol. 69, no. 7, pp. 1059-1070, 1 July 2020.

[KDD]. H. Wang, C. H. Liu*, Z. Dai, J. Tang, G. Wang, “Energy-Efficient 3D Vehicular Crowdsourcing for Disaster Response by Distributed Deep Reinforcement Learning,” in ACM SIGKDD 2021, virtual, 14-18 August 2021.

[INFOCOM]. C. H. Liu, Z. Dai, H. Yang, J. Tang, “Multi-Task-Oriented Vehicular Crowdsensing: A Deep Learning Approach,” in IEEE INFOCOM 2020, Toronto, Canada, 6-9 July, pp. 1123-1132.

[INFOCOM]. C. H. Liu, C. Piao, J. Tang, “Energy-Efficient UAV Crowdsensing with Multiple Charging Stations by Deep Learning,” in IEEE INFOCOM 2020, Toronto, Canada, 6-9 July, pp. 199-208.

[INFOCOM]. Z. Dai, H. Wang, C. H. Liu*, R. Han, J. Tang, G. Wang, “Mobile Crowdsensing for Data Freshness: A Deep Reinforcement Learning Approach,” in IEEE INFOCOM 2021, Vancouver, Canada, 10-13 May, 2021.

[INFOCOM]. Z. Xu, J. Tang, J. Meng, W. Zhang, Y. Wang, C. H. Liu, D. Yang, "Experience-driven Networking: A Deep Reinforcement Learning based Approach," in IEEE INFOCOM 2018, Honolulu, USA, pp. 1871-1879.

[ICDE]. C. H. Liu, Y. Zhao, Y. Yuan, G. Wang, D. Wu, K. K. Leung, “Curiosity Driven Energy-Efficient Worker Scheduling in Vehicular Crowdsourcing: A Deep Reinforcement Learning Approach,” in IEEE ICDE 2020, Dallas, USA, April 2020, pp:25-36.

[ICDE]. C. H. Liu, C. Piao, X. Ma, Y. Yuan, J. Tang, G. Wang, “Modeling Citywide Crowd Flows using Attentive Convolutional LSTM,” in IEEE ICDE 2021, Chania, Crete, Greece, April 19-23 2021, pp:217-228.

[CVPR]. S. Li, K. Gong, C. H. Liu, Y. Wang, F. Qiao, X. Chen, “MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition,” in IEEE CVPR 2021, virtual, June 19-25, 2021.

[CVPR]. S. Li, J. Zhang, W. Ma, C. H. Liu, W. Li, “Dynamic Domain Adaptation for Efficient Inference,” in IEEE CVPR 2021, virtual, June 19-25, 2021.

[CVPR]. S. Li, M. Xie, K. Gong, C. H. Liu, Y. Wang, W. Li, “Transferable Semantic Data Augmentation for Domain Adaptation,” in IEEE CVPR 2021, virtual, June 19-25, 2021. (Oral presentation)

[CVPR]. T. Wu, J. Huang, G. Gao, X. Wei, X. Wei, X. Luo, C. H. Liu, “Embedded Discriminative Attention Mechanism for Weakly Supervised Semantic Segmentation,” in IEEE CVPR 2021, virtual, June 19-25, 2021.

[ICCV]. S. Li, M. Xie, F. Lv, C. H. Liu, C. Qin, J. Liang, W. Li, “Semantic Concentration for Domain Adaptation,” in IEEE ICCV 2021, virtual, Oct. 10-16, 2021.

[AAAI]. S. Li, C. H. Liu*, Q. Lin, B. Xie, Z. Ding, G. Huang, J. Tang, “Domain Conditioned Adaptation Network,” in AAAI 2020, pp. 11386-11393, New York, 7-12 Feb, 2020.

[AAAI]. S. Li, F. Lv, B. Xie, C. H. Liu, J. Liang, C. Qin, “Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation,” AAAI 2021, Virtual, 2-9 Feb, 2021.

[MM]. S. Li, C. H. Liu*, B. Xie, L. Su, Z. Ding, G. Huang, “Joint Adversarial Domain Adaptation,” in ACM Multimedia 2019, pp: 729-737, Nice, France.

[MM]. Z. Liu, G. Gao, A. K. Qin, T. Wu and C. H. Liu, “Action Recognition with Bootstrapping based Long-range Temporal Context Attention,” in ACM Multimedia 2019, pp: 583-591, Nice, France.

[MM]. S. Li, B. Xie, J. Wu, Y. Zhao, C. H. Liu*, Z. Ding, “Simultaneous Semantic Alignment Network for Heterogeneous Domain Adaptation,” in ACM Multimedia 2020, pp: 3866–3874, Seattle, USA.

[MM]. S. Li, B. Han, Z. Yu, C. H. Liu*, K. Chen, S. Wang, “I2V-GAN: Unpaired Infrared-to-Visible Video Translation,” in ACM Multimedia 2021, virtual.

代表性论著:
[5] 刘驰、王占健、马晓鑫、戴子彭等(编著),《深度强化学习:学术前沿与实践应用》,机械工业出版社,排版中待发表 (in Chinese)
[4] 刘驰、罗童、林秋霞、王新科、樊路遥、温琦(编著),《大数据技术体系与开源生态》,人民邮电出版社,2018年8月 (in Chinese)
[3] 刘驰、胡柏青、谢一等(编著),《大数据治理与安全:从理论到开源实践》,机械工业出版社,201年9月1日 (in Chinese)
[2] 刘驰(主编)、符积高、徐闻春(编著),《Spark:原理、机制及应用》,机械工业出版社,2016年3月
[1] 马建(主编)、岩延、刘驰(副主编),《物联网技术概论》第二版,机械工业出版社,2015年1月


承担科研情况

1. 国家重点研发计划课题(云计算与大数据重点专项),“大规模云数据中心运行数据管理关键技术”,项目负责人, 2018~2021

2. 国家重点研发计划前沿科技创新专项课题,项目负责人,2019~2021

3. 国家自然科学基金(国家重大科研仪器研制项目),复杂结构失稳特征的长时高速高分辨测量仪器研制,项目参与人,2018~2021

4. 国家自然科学基金(优青项目),“移动群体感知关键技术”、项目负责人,2021~2023

5. 国家自然科学基金(面上项目),“绿色群智计算中的可信任务分配与数据定价技术研究”、项目负责人, 2018~2021

6. 国家自然科学基金(青年项目),“保证信息质量的节能物联网关键技术研究”、项目负责人,2014~2016

7. 工信部高质量发展专项课题,“大数据平台软件”、项目负责人,2020-2021

8. 工信部2013年电子商务集成创新试点工程,"中国轻工业产品全生命周期追溯平台建设", 项目负责人,2013~2015

9. 科技部高端外国专家引进计划,“大数据智能前沿基础研究与国际合作”,2020

10. 科技部高端外国专家引进计划,“大数据技术前沿研究与国际合作”,2021

11. 装备预研航天科技联合基金、项目负责人,2019

12. 装备预研共用技术项目、项目负责人,2018-2019


所获奖励

1. 国家优秀青年科学基金获得者

2. 中国电子学会会士

3. 英国工程技术学会会士 (Fellow of IET)

4. 英国计算机学会会士(Fellow of British Computer Society)

5. 英国皇家艺术学会会士(Fellow of Royal Society of Arts)

6. 中国计算机学会杰出会员

7. 国家人力资源和社会保障部“高层次留学人才回国资助计划”

8. 中国科协“青年人才托举工程”

9. 陕西省“第八批百人计划” - 短期项目

10. 中国工程前沿青年学者(中国工程院评选)

11. 2017年中国物联网年度人物 - 中国电子学会

12. 2018年第二届数据标准化及治理专家奖 - 中国电子标准化研究院

13. 2019年中国产学研促进奖

14. 2016年中国电子学会优秀科技工作者

15. 国家“十二五”轻工业科技创新先进个人

16. 中国物流与采购联合会科技进步一等奖,"交通运输促进中国农村物流发展战略政策研究",完成人: 高美真、陈志钢、刘驰等

17. 中国电子学会自然科学二等奖,移动行为认知与高效安全通信理论方法,第三完成人、第二完成单位

18. 中国轻工业联合会科技进步三等奖,"轻工产品大数据挖掘与全生命周期追溯关键技术研发与应用",完成人: 刘驰、丁刚毅、田甜等;第一完成单位:北京理工大学)

19. IEEE DataCom 2016 最佳论文奖

20. TridentCom'17 Best Paper Award - Runner Up,2017

21. IBM Faculty Award,2015-2020

22. IBM Champion,2020

23. 北京理工大学杰出中青年支持与资助计划,2013

24. IBM Research First Plateau - Invention Achievement Award,2012


社会兼职

1. 国家优秀青年科学基金获得者

2. 中国电子学会会士

3. 英国工程技术学会会士 (Fellow of IET)

4. 英国计算机学会会士(Fellow of British Computer Society)

5. 英国皇家艺术学会会士(Fellow of Royal Society of Arts)

6. 中国计算机学会杰出会员

7. 国家人力资源和社会保障部“高层次留学人才回国资助计划”

8. 中国科协“青年人才托举工程”

9. 陕西省“第八批百人计划” - 短期项目

10. 中国工程前沿青年学者(中国工程院评选)

11. 2017年中国物联网年度人物 - 中国电子学会

12. 2018年第二届数据标准化及治理专家奖 - 中国电子标准化研究院

13. 2019年中国产学研促进奖

14. 2016年中国电子学会优秀科技工作者

15. 国家“十二五”轻工业科技创新先进个人

16. 中国物流与采购联合会科技进步一等奖,"交通运输促进中国农村物流发展战略政策研究",完成人: 高美真、陈志钢、刘驰等

17. 中国电子学会自然科学二等奖,移动行为认知与高效安全通信理论方法,第三完成人、第二完成单位

18. 中国轻工业联合会科技进步三等奖,"轻工产品大数据挖掘与全生命周期追溯关键技术研发与应用",完成人: 刘驰、丁刚毅、田甜等;第一完成单位:北京理工大学)

19. IEEE DataCom 2016 最佳论文奖

20. TridentCom'17 Best Paper Award - Runner Up,2017

21. IBM Faculty Award,2015-2020

22. IBM Champion,2020

23. 北京理工大学杰出中青年支持与资助计划,2013

24. IBM Research First Plateau - Invention Achievement Award,2012


备注

1. 实验室每年约录取3-5名博士、20名硕士,20名本科毕设学生,请抓紧发邮件到chiliu@bit.edu.cn联系。

2. 实验室拥有NVIDIA RTX、2080Ti、XP系列显卡60余块,CPU集群一个(15台服务器),GPU服务器5台,能充分满足人工智能与大数据的科研需求。

3. 实验室常年与字节跳动、美的、美团、IBM、微软、腾讯、阿里、滴滴及诸多海外高校保持频繁的学术交流、实习生选派和博士生推荐。

4. 特别欢迎本校保研的同学提前来实验室,一起做高水平论文!

5. Last update July 2021