Research Interests

Artificial Intelligence, Data Mining, High Performance Computing

 

Research Project

• University of Chinese Academy of Sciences

City Public Transportation Big Data. PI, funded by GuangDong Provincial Science and Technology Project, 2016-2019.

DCN Performance Analysis on GPU-based cloud. Research funded by Huawei Corporation, 2017-2018.

Multi-source Big Data based Credit Scoring for Internet Banking. PI, Research funded by National Natural Science Foundation of China, 2017-2020.

DNS Log and Registration Data Mining. PI, Research funded by China Internet Network Information Center, 2013- 2014.

Utility-based Customized Academic Literature Recommendation System. PI, Research funded by National Natural Science Foundation of China, 2013 - 2015.

DNS Stream Data Mining. PI, Research funded by China Internet Network Information Center, 2012 - 2013.

Traffic Stream Monitoring and Auditing. PI, Research funded by China Internet Center, 2012.

Cloud-enabled Scientific Simulation. PI, Research funded by Agilent Technologies Foundation, 2012 - 2013.

Cross Platform nVidia GPU Accelerated High-Performance Data Graphic Visualization. PI, Research funded by Agilent Technologies Foundation, 2010- 2011. 

High Performance Data Mining with CUDA. PI, Research funded by NVIDIA, 2009.

 

Traffic Stream Mining on Sensor Networks. PI, Research funded by Ministry of Education of China, 2009 - 2010.

Utility Mining. PI, Research funded by President Fund of Graduate University of Chinese Academy of Sciences, 2009 - 2010.

 

Models and Methods for Trustworthy Software Risk Control. Research funded by National Natural Science Foundation of China, 2008 - 2010.

 

High Performance Data Mining. Research funded by National Natural Science Foundation of China, 2007 - 2009.

 

Individual Credit Scoring. Project funded by the People's Bank of China, 2006 - 2007.

 

• Ultra-Scale Computing Laboratory, Northwestern University, USA

 (Research Assistant, September 2001 - June 2005)

Distributed Mining on Data Streams. Research funded by National Science Foundation.

Utility Mining. Research funded by National Science Foundation.

Performance Evaluation and Characterization of Scalable Data Mining Algorithms. Research funded by Intel Corporation.

 

High Performance Data Mining in Large-scale Scientific Simulations. Research funded by Department of Energy (DOE).

• Database System Group, Northwestern University, USA

  (Research Assistant, September 1999 - August 2001)

Text Classification. Research funded by National Science Foundation.

Data Warehousing. Research funded by National Aeronautics and Space Administration (NASA).

Northwestern University, Evanston, IL,USA
Ph. D. in Computer Engineering, December 2005
Dissertation: High Performance Data Mining Techniques for Large Databases
Advisor: Prof. Alok Choudhary

Northwestern University, Evanston, IL, USA 
M.S. in Computer Engineering, December 2001
Project: Using WordNet to Disambiguate Word Senses
Advisor: Prof. Peter Scheuermann

Peking University, Beijing, China
B.S. (major) in Computer Science, B.A. (minor) in Economics, July 1999

   

• School of Computer Science and Technology, University of Chinese Academy of Sciences

Professor, December 2015 - present

Associate Professor, June 2007- Nov. 2015

Assistant Professor, January 2006 - May 2007

• University of Nebraska at Omaha, Omaha, NE, USA

Visiting Scientist, July 2009 - September 2009  

• Northwestern University, Evanston, IL, USA

Research Associate, July 2005 - November 2005

Graduate Courses

Internatioal School, University of Chinese Academy of Sciences

Data Mining (September 2013- present)

School of Computer Science and Technology, University of Chinese Academy of Sciences 

Data Mining Algorithm Seminar (September 2009 - present)

High Performance Computing with CUDA (September 2009 - present)

Data Mining (September 2006 - Present)

Advanced Data Mining Techniques (February 2007- Spring 2010)

Computing and Communication Engineering College, University of Chinese Academy of Sciences

Data Mining  (March 2007- May 2007)

Undergraduate Courses

School of Computer Science and Technology, University of Chinese Academy of Sciences 

Data Mining (March 2017 - present) 

LiPei Outstanding Faculty Award, Chinese Academy of Sciences, 2022.

ZhuLiYueHua Best Faculty Award, Chinese Academy of Sciences, 2017.

Best Paper Award, International Conference on Information Technology and Quantitative Management, Brazil, 2015

Best Poster Award, Conference on Scientific Data, Lanzhou, China, 2015

Best CUDA Teaching Center (China), Nvidia, 2014

CUDA Research Center, awarded by Nvidia, 2012

CUDA Teaching Center, awarded by Nvidia, 2012

Best Faculty Award, University of Chinese Academy of Sciences, 2009, 2013

Second Prize in Beijing Science and Technology Award, 2011

Third Prize in Beijing Science and Technology Award, 2010

Best Course Award, University of Chinese Academy of Sciences, 2008, 2010, 2011,2012

Dissertation-Year Fellowship Nomination, Northwestern University, 2004

Best Poster Award, ECE graduate students poster session, Northwestern University,2003

Research Assistantship, ECE Department, Northwestern University, 1999 - Present

Outstanding Undergraduate Award, Peking University, 1997

XI YUE Scholarship to best undergraduate students, Peking University, 1997

GE (General Electronics) China Scholarship to best undergraduate students, Peking University, 1996

Outstanding Freshmen Award, Peking University, 1995

   

•  Journal Paper

   

1. Hao Gong, Ying Liu*, Expandable Pruning: Enhancing Model Compression through Smoothness-Guided Widening, Neurocomputing, 674, 132892, Jan. 29, 2026, https://doi.org/10.1016/j.neucom.2026.132892. (SCI 2)
2. Hao Gong, Ying Liu*, Pruning-Sensitivity-Guided Adaptive Widening for Binary Neural Networks, Displays, 93, 103397, 2026/02/12, https://doi.org/10.1016/j.displa.2026.103397. (SCI 2)
3. Xiaoying Chen, Ying Liu, Cheng Wang, Multi-Domain Fusion Network for Active Jamming Recognition in Cognitive Radar, Remote Sensing, May 14, 2025, 17(10), 1723. https://doi.org/10.3390/rs17101723. (SCI 2, IF=4.05)
4. Mohammed Ali Mohammed Al-Hababi1, Ahsan Habib, Fursan Thabit, Ying Liu, “A Novel Pre-Processing Approach and Benchmarking Analysis for Faster, Robust, and Improved Small Object Detection Methods”, Remote Sensing, 10/10/2024, 16(20), 3753, https://doi.org/10.3390/rs16203753. (SCI 2，IF=4.2)
5. Qiancheng Wei, Ying Liu*, Xiaoping Jiang, Ben Zhang, Qiya Su, Muyao Yu, “DDFNet-A: Attention-Based Dual-Branch Feature Decomposition Fusion Network for Infrared and Visible Image Fusion”, Remote Sensing, 05/18/2024, 16, 1795, https://doi.org/10.3390/rs16101795. (SCI 2, IF=4.2)
6. Tajuddeen Rabiu Gwadabe, Mohammed Al-hababi, Ying Liu, “SimGNN: Simplified Graph Neural Networks for Session-based Recommendation”, Applied Intelligence,Vol. 53, pp. 22789–22802, July 3, 2023. (SCI 2, IF=5, H-Index=52)
7. Hao Gong, Ying Liu, Xiaoying Chen, Cheng Wang, “Scene Optimization of GPU‑based Back‑Projection Algorithm”, Journal of Supercomputing, https://doi.org/10.1007/s11227-022-04785-w. (SCI 3)
8. Zhengyu Cui, Ying Liu, Wei Zhao, Cheng Wang, “Learning to Transfer Attention in Multi-level Features for Rotated Ship Detection”, Neural Computing and Applications, June, 2022, https://doi.org/10.1007/s00521-022-07491-z. (SCI 2)
9. Tajuddeen Rabiu Gwadabe, Ying Liu, “Improving graph neural network for session-based recommendation system via non-sequential interactions”, Neurocomputing, Volume 468, Jan. 2022, pp. 111-122. (SCI 2, 计算机科学顶刊), h-index=110
10. Tajuddeen Rabiu Gwadabe, Ying Liu, “IC-GAR: Item Co-occurrence Graph Augmented Session-based Recommendation”, Neural Computing and Applications, 34, pp. 7581–7596, 2022. (SCI 2)
11. Jiaxu Leng, Ying Liu, Xinbo Gao, “Selective region enlargement network for fast object detection in high resolution images”, Neurocomputing, Vol. 462, Oct. 28, 2021, pp. 402-411. (SCI 2, 计算机科学顶刊), h-index=110
12. Zhengyu Cui, Jiaxu Leng, Ying Liu, Tianlin Zhang, Pei Quan, Wei Zhao, “SKNet: Detecting Rotated Ships as Keypoints in Optical Remote Sensing Images”, IEEE Transactions on Geoscience and Remote Sensing (Print ISSN: 0196-2892, Online ISSN: 1558-0644), Feb. 2021, pp. 8826-8840, DOI: 10.1109/TGRS.2021.3053311. (SCI 1, 工程技术顶刊)，h-index=216
13. Jiaxu Leng, Ying Liu, “CrossNet: Detecting Objects as Crosses”, IEEE Transactions on Multimedia, Vol. 2, Feb. 18, 2021, pp. 861-875, (SCI 1, IF = 5.84, 计算机科学顶刊), h-index=108
14. Jiaxu Leng, Ying Liu, “Context Augmentation for Object Detection”, June 2022, Applied Intelligence, 52(3), pp. 2621–2633, 2022. (SCI 3, IF = 3.3)
15. Jiaxu Leng, Ying Liu, “Single-shot augmentation detector for object detection”, Neural Computing and Applications, Vol. 33, pp. 3583–3596, 2021, DOI: 10.1007/s00521-020-05202-0. (SCI 2, IF=4.66)
16. Tianlin Zhang, Jiaxu Leng, Ying Liu, “Deep learning for drug–drug interaction extraction from the literature: a review”, Briefings in Bioinformatics, Nov. 2019， https://doi.org/10.1093/bib/bbz087. (SCI 1, IF = 9.1)
17. Jiaxu Leng, Ying Liu, Shang Chen, “Context-aware Attention Network for Image Recognition”, Neural Computing and Applications, Vol. 31(12), June 2019, pp. 6295-6305. (SCI 2, IF=4.66)
18. Jiaxu Leng, Ying Liu, Dawei Du, Tianlin Zhang, Pei Quan, “Robust Obstacle Detection and Recognition for Driver Assistance Systems”, IEEE Transactions on Intelligent Transportation Systems, Vol. 21(4), April 2020, pp. 1560-1571. (SCI 2, IF=5.74)
19. Ying Liu, Hongyuan Cui, Renliang Zhao, “Fast Acquisition of Spread Spectrum Signals using Multiple GPUs”, IEEE Transactions on Aerospace and Electronic Systems, Vol 55(6), December 2019, pp. 3117-3125. (SCI 2, IF=2.8)
20. Jiaxu Leng, Ying Liu, Real-Time RGB-D Visual Tracking With Scale Estimation and Occlusion Handling, IEEE Access 2018，DOI: 10.1109/ACCESS.2018.2831443. (SCI 2, IF=4.1)
21. Jiaxu Leng, Ying Liu, “An enhanced SSD with feature fusion and visual reasoning for object detection”, Neural Computing and Applications, Vol. 31, 2019, pp. 6549-6558. (SCI 2, IF=4.66)
22. Ying Liu, Guoyu Ou, “Real-Time Vehicular Traffic Violation Detection in Traffic Monitoring Stream”, Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Vol. 22, (1) 2018, pp.53-64. (SCI 3, IF=2.57)
23. Ying Liu, Haixin Zheng, Renliang Zhao, Liheng Jian, “Design and Evaluation of Multi-GPU enabled Multiple Symbol Detection Algorithm”, Journal of Supercomputing, Vol. 72(6), 2016.6, pp. 2111-2131, DOI 10.1007/s11227-015-1475-z.
24. Zhongya Wang, Ying Liu, Jiajun Yang, Zheng Zheng, Kaichao Wu, “A Personalization-Oriented Academic Literature Recommendation Method”, Data Science Journal, 2015, DOI: http://doi.org/10.5334/dsj-2015-017.
25. Hongyuan Cui, Jiajun Yang, Ying Liu, Zheng Zheng, Kaichao Wu, “Data Mining-based DNS Log Analysis”, Annals of Data Science, DOI: 10.1007/s40745-014-0023-7.
26. Zhongya Wang, Ying Liu, Steve Chiu, “An Efficient Parallel Collaborative Filtering Algorithm on Multi-GPU Platform”, Journal of Supercomputing, Vol. 72(6), 2016.6, pp 2080-2094, DOI:10.1007/s11227-014-1333-4.
27. Yuwei Wang, Yuanchun Zhou, Ying Liu, “A Grid-Based Clustering Algorithm for Wild Bird Distribution”, Frontiers of Computer Science, Vol. 7(4), 2013, pp. 475-485. DOI:10.1007/s11704-013-2223-2.
28. Liheng Jian, Ying Liu, Weidong Yi, “CU-Simulator: A Parallel Scalable Simulation Platform for Radio Channel in Wireless Sensor Networks”, Ad Hoc & Sensor Wireless Networks, Vol.24, pp. 109-134.
29. Liheng Jian, Cheng Wang, Ying Liu, Shenshen Liang, Weidong Yi, Yong Shi, "Parallel Data Mining on Graphics Processing Unit with Compute Unified Device Architecture (CUDA)", Journal of Supercomputing, Vol. 64(3), 2013, pp. 942-967.
30. Ying Liu, Lingling Zhang, Yuehua Zhang, Yong Shi, " Bug Detection in Source Code in Process Monitoring", Journal of Computational Information System, Vol. 8(2), 2012, pp. 591-601.
31. Ying Liu, Jianwei Li, Wei-keng Liao, Alok Choudhary, Yong Shi, “High Utility Itemsets Mining”, International Journal of Information Technology & Decision Making (IJITDM), Volume No.09, Issue No. 6, November 2010, pp. 905-934.
32. Yuejin Zhang, Lingling Zhang, Ying Liu, Yong Shi, "Mining Intelligent Knowledge from a Two-phase Association Rules Mining", International Journal of Data Mining, Modeling and Management, Vol. 2, No. 4, 2010, pp. 403-418.
33. Lian Duan, Lida Xu, Ying Liu and Jun Lee, “Cluster-based Outlier Detection”, Annals of Operations Research, Vol. 168, No. 1, April 2009, pp. 151-168.
34. Guangli Nie, Lingling Zhang, Ying Liu, Xiuyu Zheng, Yong Shi, "Decision analysis of data mining project based on Bayesian risk", Journal of Expert Systems with Applications, Vol. 36, Issue 3, Part 1, April 2009, pp. 4589–4594.
35. Cheng Wang, Ying Liu, Liheng Jian, Peng Zhang, "An Efficient Approach for Mining Web Content Sensitivity", International Journal of Knowledge and Web Intelligence, Vol. 1, Nos. 1/2, 2009, pp. 95-109.