General
Professor Hong Qiao
Email: hong.qiao@ia.ac.cn
Telephone: 010-62573736 
Address:  95 Zhongguancun East Road, BEIJING, CHINA 
Postcode: 100190 
  


Biosketch

  • Dr. Hong Qiao is a professor with Institute of Automation, Chinese Academy of Sciences. In 2004, Prof. Qiao gave up the tenure position and returned to China under the grant of the “100 Talent” Program of the Chinese Academy of Sciences. After her return, she founded the “Robotic Theory and Application” group in CASIA. In 2007, she was supported by National Science Fund for Distinguished Young Scholars. Currently she is the Core Expert of CAS Centre for Excellence in Brain Science and Intelligence Technology (CEBSIT), the Vice Director of Joint Lab Between the Institute of Automation and University of Sciences and Technology of China, and the Deputy Director & Principal Investigator of Neuro-robotics, Research Centre for Brain-inspired Intelligence, Institute of Automation, CAS. 

  • In 2014, Prof. Qiao won the Second Prize of National Natural Science Awards as the first participant. It is among the three ones themed in robotics in this award ever since. In 2012, Prof. Qiao won the First Prize of Beijing Science and Technology Award for fundamental research as the first participant. In 2015, Prof. Qiao won the Second Prize of Beijing Science and Technology Award for technology inventions as the first participant

  • For IEEE professional services, Prof. Qiao volunteers her effort and time in the global IEEE society. Currently, she is a member of the Administrative Committee (AdCom) of IEEE RAS (She is the first mainland China scholar elected to this committee, and she is successfully elected as the AdCom member for the second term in 2016). She also serves for many important committee in IEEE RAS, such as Long Range Planning Committee, Industrial Activities Board, Early Career Award Nomination Committee, Women in Engineering Committee, etc. She is also a Founding Member and Vice-President of the Beijing Chapter of IEEE RAS. For non-IEEE professional services, in 2016, Prof. Qiao was invited as Member of Global Future Councils -  The Future of Artificial Intelligence and Robotics, World Economic Forum (WEF) (25 members in this council). 

  • Prof. Qiao has long led the group in research areas of robotic “Hand-Eye-Brain”, which includes industrial robot manipulation and control (Hand), robot vision (Eye), bio-inspired and brain-like intelligent robot (Brain), and etc. She has published more than 200 papers in international journals and conferences (100+ papers are SCI Indexed). More than 60 papers have been published in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, IEEE Transactions on Cybernetics, IEEE/ASME Transactions on Mechatronics, etc. (which are rated as Q1, the top level by ISI Journal Citation Report). She is now serving as Editor-in-Chief of the international journal Assembly Automation, and the Associate Editors for several significant international journals, such as IEEE Transactions on Cybernetics, IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Cognitive and Developmental Systems

  • She has undertaken a series of national key projects, including National Science Fund for Distinguished Young Scholars, Key Project of Natural Science Foundation of China, 863 Project of Ministry of Science and Technology of China, '04 Project' of National Science and Technology Major Project, Project of intelligent equipment of National Development and Reform Commission, and etc. Prof. Qiao and her group conducted application cooperation in areas such as automobile, CNC, national defense and home service. The Group cooperates with industry and IT companies, including XCMG Group, Shanxi Qinchuan Machinery development Co.,Ltd, Huawei, Samsung, Midea Group and etc. 

  • Two industrialization bases for industrial robot has been started in Guangdong Province. In 2015, the group established CAS-Huizhou Tech Center for Advanced Manufacturing, which formed fundamental platform for large-scale application of industrial robot compliant manipulation technology and its industry chain cultivation. In 2016, the group established CAS Research Center for Intelligent Manufacturing in Dongguan.

Education

Doctor of Philosophy 1995 De Montfort University Leicester, UK  
Master of Engineering
1992 University of Strathclyde Glasgow, UK
Master of Engineering 1989 Xi'an Jiaotong University Xi'an, China
Bachelor of Engineering
1986 Xi'an Jiaotong University Xi'an, China

Professional History

2004-present, Director, Institute of Automation, Chinese Academy of Sciences (CAS)

2016-present, Dean, School of Mechanical Engineering, University of Science and Technology, Beijing (USTB)

2016-present, Director, The Beijing Key laboratory of Research and Application for Robotic Intelligence of “Hand-Eye-Brain” Interaction

2004-present, Director, Robotic Theory and Application Research Group

2015-present, Deputy Director, Neuro-robotics, Research Centre for Brain-inspired Intelligence, Institute of Automation, CAS

2015-present, Core Expert, CAS Centre for Excellence in Brain Science and Intelligence Technology (CEBSIT)

2004-present, Deputy Director, Joint Lab Between the Institute of Automation, CAS and University of Science and Technology of China

2002-2004, Lecturer (Senior Scale), School of Informatics, Manchester University, UK

1997-2002, Assistant Professor, Department of MEEM, City University of Hong Kong, Hong Kong

1995-1997, Research Fellow, Mechatronics Group, De Montfort University, Leicester, UK

1992-1995, Research Associate, Mechatronics Group, De Montfort University, Leicester, UK

1990-1992, Research Associate, Industrial Control Unit, University of Strathclyde, Glasgow, UK


Honors & Distinctions

  • 2014, Prof. Qiao (as the first participant) won the Second Prize of the National Natural Science Awards (NNSA is the highest fundamental research award in China). The prize is among the only three ones themed in robotics in this award ever since
  • 2015, Prof. Qiao (as the first participant) won the Second Prize of the Beijing Science and Technology Award for Technology Inventions
  • 2012, Prof. Qiao (as the first participant) won the First Prize of the Beijing Science and Technology Award for Fundamental Research (The prize ranked first in the first-class award)
  • 2012, Prof. Qiao was selected as the State Council Expert for Special Allowance
  • 2009, Prof. Qiao was selected as the State-level Expert of New Century Hundred-Thousand-Ten Thousand Talents Project
  • 2007, Prof. Qiao won the National Science Fund for Distinguished Young Scholars, which is a prestigious award to young scholars in China

Professional Activities

Prof. Qiao has  actively participated in the work of IEEE Society. In 2013, she has been selected as the Member of the Administrative Committee of IEEE Robotics and Automation Society (Elected by ballot as one of 18 members for the governance of 14,000 society members). She is the first mainland China scholar elected to this committee, and she is successfully elected for the second term in 2016.

She is also the Co-Founder of Beijing Chapter for IEEE Robotics and Automation Society, the Vice-President of Beijing Chapter for IEEE Robotics and Automation Society and Control Systems Society.

Social Activities

IEEE Activities

Member, Administrative Committee, IEEE Robotics and Automation Society, 2014-2016, 2017-2019


Member, IEEE Medal for Environmental & Safety Technologies Committee, 2014-2017

Member, RAS Long Range Planning Committee, 2016-2017

Member, RAS Women in Engineering Committee, 2015-2016

Member, RAS Early Career Award Nomination Committee, 2014-2018 (four successive terms)

Member, RAS Most Active Technical Committee Award Nomination Committee, 2014-2015

Member, RAS Industrial Activities Board, 2014-2015


​Non-IEEE Activities

Member of Global Future Councils -The Future of Artificial Intelligence and Robotics, World Economic Forum (WEF), 2016-present




Editorial Board

Editor-in-Chief
  1. Editor in Chief, Assembly Automation 2014-present
Associate Editor
  1. Associate Editor, IEEE Transactions on Neural Networks and Learning Systems, 2017-present
  2. Associate Editor, IEEE Transactions on Cognitive and Developmental Systems, 2016-present
  3. Technical Editor, IEEE/ASME Transactions on Mechatronics, 2015-present
  4. Associate Editor, IEEE Transactions on Automation Science and Engineering, 2015-present
  5. Associate Editor, IEEE Transactions on Cybernetics, 2012-present
  6. Associate Editor, IEEE Transactions on Systems, Man and Cybernetics: Part B, 2003-2012
  7. Associate Editor, International Journal of Social Robots, 2009-present
  8. Associate Editor, International Journal of Automation and Computing, 2011-present




Other Activities

  1. Publicity Co-Chair, 2017, IEEE International Conference on Robotics and Automation (ICRA)
  2. Program Chair, 2016, World Congress on Intelligent Control and Automation (WCICA)
  3. Program Co-Chair, 2015, IEEE International Conference on Robotics and Automation (ICRA)
  4. Program Co-Chair, 2015, World Congress on Intelligent Control and Automation (WCICA)
  5. Program Co-Chair, 2014, World Congress on Intelligent Control and Automation (WCICA)
  6. Regional Chair, 2012, World Congress on Intelligent Control and Automation (WCICA)
  7. Region Chair, 2011, World Congress on Intelligent Control and Automation (WCICA)
  8. Co-organizer of Workshop, 2008, World Congress on Intelligent Control and Automation (WCICA)
  9. Program Chair, 2006 IEEE Workshop on Advanced Robots and Social Impact Service Robots
  10. Technical Tour Co-Chair, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems
  11. Award Committee Member, 2008, World Congress on Intelligent Control and Automation (WCICA)
  12. Member of the Program Committee of the 2003 IEEE International Conferences on Robotics and Automation
  13. Member of the Program Committee of the 2002 IEEE International Conferences on Robotics and Automation
  14. Member of the Program Committee of the 2001 IEEE International Conferences on Robotics and Automation
  15. Session Chair at the 2001 IEEE International Conference on Robotics and Automation
  16. Invited Session Chair in the Genetic Algorithm session of the 2000 IEEE International Conference on Electrical Industry and Instrumentation
  17. Member of the Program Committee of the International Conference on Computer Applications in Industry and Engineering, USA, 1999
  18. Invited Session Chair at the ISOMA, 1998
  19. Member of the Program Committee of Intelligent Control and Intelligent Management, The Chinese Artificial Intelligent Society
  20. Member of “Call for Proposals for Service Robots” Group, Chinese Ministry of Science and Technology, 2005
  21. Invited Speaker at the17th IEEE International Symposium on Intelligent System, 2002
  22. ​Invited Speaker at the 2000 IEEE International Conference on Electrical Industry and Instrumentation

Selected Publications

Since 2009, Prof. Qiao’s Group has published more than 200 papers in international journals and conferences (more than 120 are indexed by SCI, and most of the journals are IEEE Transactions).

2018
[1] S. Liu, J. Wu, L. Feng, H. Qiao, Y. Liu, W. Luo and W. Wang, “Perceptual uniform descriptor and ranking on manifold for image retrieval,” Information Sciences, vol. 424, no. Supplement C, pp. 235-249, 2018.
2017
[2] S. Ying, Z. Wen, J. Shi, Y. Peng, J. Peng and H. Qiao, “Manifold Preserving: An Intrinsic Approach for Semisupervised Distance Metric Learning,” IEEE Transactions on Neural Networks and Learning Systems, vol. PP, no. 99, pp. 1-12, 2017.
[3] P. Yin, H. Qiao, W. Wu, L. Qi, Y. L. Li, S. Zhong and B. Zhang, “A Novel Biologically-inspired Visual Cognition Model - Automatic Extraction of Semantics, Formation of Integrated Concepts and Re-selection Features for Ambiguity,” IEEE Transactions on Cognitive and Developmental Systems, vol. PP, no. 99, pp. 1-1, 2017.
[4] X. Yang, H. Qiao and Z. Y. Liu, “An Algorithm for Finding the Most Similar Given Sized Subgraphs in Two Weighted Graphs,” IEEE Transactions on Neural Networks and Learning Systems, vol. PP, no. 99, pp. 1-6, 2017.
[5] X. Yang, H. Qiao and Z.-Y. Liu, “Point correspondence by a new third order graph matching algorithm,” Pattern Recognition, vol. 65, no., pp. 108-118, 2017.
[6] X. Yang, Z.-Y. Liu, H. Qiao and J.-H. Su, “Probabilistic hypergraph matching based on affinity tensor updating,” Neurocomputing, vol. 269, no., pp. 142-147, 2017.
[7] X. Yang, Z.-Y. Liu and H. Qiao, “Incorporating Discrete Constraints Into Random Walk-Based Graph Matching,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. PP, no. 99, pp. 1-11, 2017.
[8] J. H. Su, H. Qiao, C. K. Liu, Y. B. Song and A. L. Yang, “Grasping Objects The Relationship Between the Cage and the Form-Closure Grasp,” Ieee Robotics & Automation Magazine, vol. 24, no. 3, pp. 84-96, 2017.
[9] J. H. Su, R. Li, H. Qiao, J. Xu, Q. L. Ai and J. K. Zhu, “Study on Dual Peg-in-hole Insertion using of Constraints Formed in the Environment,” Industrial Robot: An International Journal, vol. 44, no. 6, pp. 730-740, 2017.
[10] B. Shen, Z. D. Wang and H. Qiao, “Event-Triggered State Estimation for Discrete-Time Multidelayed Neural Networks With Stochastic Parameters and Incomplete Measurements,” IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 5, pp. 1152-1163, 2017.
[11] H. Qiao, H. Zhang and F. Röhrbein, “Editorial for special issue on human-inspired computing,” International Journal of Automation and Computing, vol. 14, no. 5, pp. 501-502, 2017.
[12] C. Ma and H. Qiao, “Distributed asynchronous event-triggered consensus of nonlinear multi-agent systems with disturbances: An extended dissipative approach,” Neurocomputing, vol. 243, no. Supplement C, pp. 103-114, 2017.
[13] S. Liu, L. Feng, Y. Liu, H. Qiao, J. Wu and W. Wang, “Manifold Warp Segmentation of Human Action,” IEEE Transactions on Neural Networks and Learning Systems, vol. PP, no. 99, pp. 1-13, 2017.
[14] R. Li and H. Qiao, “Condition and Strategy Analysis for Assembly Based on Attractive Region in Environment,” IEEE/ASME Transactions on Mechatronics, vol. 22, no. 5, pp. 2218-2228, 2017.
2016
[15] X. Y. Huang, B. Zhang, H. Qiao and X. L. Nie, “Local Discriminant Canonical Correlation Analysis for Supervised PolSAR Image Classification,” IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 11, pp. 2102-2106, 2017.
[16] X. Huang, X. Nie, W. Wu, H. Qiao and B. Zhang, “SAR target configuration recognition based on the biologically inspired model,” Neurocomputing, vol. 234, no., pp. 185-191, 2017.
[17] S. Ding, X. Xi, Z. Liu, H. Qiao and B. Zhang, “A Novel Manifold Regularized Online Semi-supervised Learning Model,” Cognitive Computation, vol., no., pp., 2017.
[18] S. Ding, X. Nie, H. Qiao and B. Zhang, “A Fast Algorithm of Convex Hull Vertices Selection for Online Classification,” IEEE Transactions on Neural Networks and Learning Systems, vol. PP, no. 99, pp. 1-15, 2017.
[19] Y.-R. Zhang, X. Yang, H. Qiao, Z.-Y. Liu and C.-K. Liu, “Introducing locally affine-invariance constraints into lunar surface image correspondence,” Neurocomputing, vol. 186, no., pp. 258-270, 2016.
[20] X. Y. Xi, P. J. Yin, H. Qiao, Y. L. Li and W. S. Feng, “A biologically inspired model mimicking the memory and two distinct pathways of face perception,” Neurocomputing, vol. 205, no., pp. 349-359, 2016.
[21] J. Su, Z.-Y. Liu, H. Qiao and C. Liu, “Pose-estimation and reorientation of pistons for robotic bin-picking,” Industrial Robot: An International Journal, vol. 43, no. 1, pp. 22-32, 2016.
[22] Z. K. Qin, P. Wang, S. Jia, L. J. Yan and H. Qiao, “Precise Robotic Assembly for Large-Scale Objects Based on Automatic Guidance and Alignment,” IEEE Transactions on Instrumentation and Measurement, vol. 65, no. 6, pp. 1398-1411, 2016.
[23] H. Qiao, Y. L. Li, F. F. Li, X. Y. Xi and W. Wu, “Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning,” IEEE Transactions on Cybernetics, vol. 46, no. 10, pp. 2335-2347, 2016.
[24] H. Qiao, C. Li, P. Yin, W. Wu and Z. Y. Liu, “Human-inspired motion model of upper-limb with fast response and learning ability - A promising direction for robot system and control,” Assembly Automation, vol. 36, no. 1, pp. 97-107, 2016.
[25] D. H. Qian, T. S. Chen, H. Qiao and T. Tang, “Iterative Point Matching via multi-direction geometric serialization and reliable correspondence selection,” Neurocomputing, vol. 197, no., pp. 171-183, 2016.
[26] D. Qian, T. S. Chen and H. Qiao, “Geodesic-like features for point matching,” Neurocomputing, vol. 218, no., pp. 401-410, 2016.
[27] D. Qian, T. S. Chen and H. Qiao, “Background of shape contexts for point matching,” Pattern Recognition Letters, vol. 84, no., pp. 114-119, 2016.
[28] X. L. Nie, B. Zhang, Y. J. Chen and H. Qiao, “A New Algorithm for Optimizing TV-Based PolSAR Despeckling Model,” IEEE Signal Processing Letters, vol. 23, no. 10, pp. 1409-1413, 2016.
[29] X. L. Nie, H. Qiao, B. Zhang and X. Y. Huang, “A Nonlocal TV-Based Variational Method for PolSAR Data Speckle Reduction,” IEEE Transactions on Image Processing, vol. 25, no. 6, pp. 2620-2634, 2016.
[30] W. Y. Li, P. Wang and H. Qiao, “Top–down visual attention integrated particle filter for robust object tracking,” Signal Processing: Image Communication, vol. 43, no., pp. 28-41, 2016.
[31] C. Li, Z.-Y. Liu, X. Yang, H. Qiao and J.-H. Su, “Stitching contaminated images,” Neurocomputing, vol. 214, no., pp. 829-836, 2016.
[32] R. Jiang, H. Qiao and B. Zhang, “Efficient Fisher Discrimination Dictionary Learning,” Signal Processing, vol. 128, no., pp. 28-39, 2016.
[33] X. Y. Huang, H. Qiao and B. Zhang, “SAR Target Configuration Recognition Using Tensor Global and Local Discriminant Embedding,” IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 2, pp. 222-226, 2016.
[34] W. S. Feng, H. Qiao and Y. J. Chen, “Poisson Noise Reduction with Higher-Order Natural Image Prior Model,” SIAM Journal on Imaging Sciences, vol. 9, no. 3, pp. 1502-1524, 2016.
[35] M. Y. Fan, X. Q. Zhang, H. Qiao and B. Zhang, “Efficient isometric multi-manifold learning based on the self-organizing method,” Information Sciences, vol. 345, no., pp. 325-339, 2016.
2015
[36] X. Yang, H. Qiao and Z. Y. Liu, “Outlier robust point correspondence based on GNCCP,” Pattern Recognition Letters, vol. 55, no., pp. 8-14, 2015.
[37] X. Yang, H. Qiao and Z. Y. Liu, “Feature correspondence based on directed structural model matching,” Image and Vision Computing, vol. 33, no. 0, pp. 57-67, 2015.
[38] J. H. Su, H. Qiao, Z. C. Ou and Z. Y. Liu, “Vision-Based Caging Grasps of Polyhedron-Like Workpieces With a Binary Industrial Gripper,” IEEE Transactions on Automation Science and Engineering, vol. 12, no. 3, pp. 1033-1046, 2015.
[39] J. H. Su, Z. C. Ou and H. Qiao, “Form-closure caging grasps of polygons with a parallel-jaw gripper,” Robotica, vol. 33, no. 06, pp. 1375-1392, 2015.
[40] H. Qiao, X. Y. Xi, Y. L. Li, W. Wu and F. F. Li, “Biologically Inspired Visual Model With Preliminary Cognition and Active Attention Adjustment,” IEEE Transactions on Cybernetics, vol. 45, no. 11, pp. 2612-2624, 2015.
[41] H. Qiao, M. Wang, J. H. Su, S. X. Jia and R. Li, “The Concept of "Attractive Region in Environment" and its Application in High-Precision Tasks With Low-Precision Systems,” IEEE/ASME Transactions on Mechatronics, vol. 20, no. 5, pp. 2311-2327, 2015.
[42] H. Qiao, R. Li and P. J. Yin, “Robotics and Automation Activities in China [Industrial Activities],” Robotics & Automation Magazine, IEEE, vol. 22, no. 3, pp. 14-17, 2015.
[43] X. L. Nie, H. Qiao and B. Zhang, “A Variational Model for PolSAR Data Speckle Reduction Based on the Wishart Distribution,” IEEE Transactions on Image Processing, vol. 24, no. 4, pp. 1209-1222, 2015.
[44] Y. K. Luo, P. Wang, W. J. Zhu and H. Qiao, “Sparse-Distinctive Saliency Detection,” Signal Processing Letters, IEEE, vol. 22, no. 9, pp. 1378-1382, 2015.
[45] S. L. Liu, L. Feng and H. Qiao, “Scatter Balance: An Angle-Based Supervised Dimensionality Reduction,” Neural Networks and Learning Systems, IEEE Transactions on, vol. 26, no. 2, pp. 277-289, 2015.
[46] F. Lin, S. L. Liu, Y. Xiao, H. Qiao and B. Wu, “A novel CBIR system with WLLTSA and ULRGA,” Neurocomputing, vol. 147, no. 0, pp. 509-522, 2015.
[47] Y. L. Li, W. Wu, B. Zhang and F. F. Li, “Enhanced HMAX model with feedforward feature learning for multiclass categorization,” Frontiers in Computational Neuroscience, vol. 9, no., pp. 1-14, 2015.
[48] W. Y. Li, P. Wang, R. Jiang and H. Qiao, “Robust object tracking guided by top-down spectral analysis visual attention,” Neurocomputing, vol. 152, no. 0, pp. 170-178, 2015.
[49] R. Li, W. Wu and H. Qiao, “The compliance of robotic hands–from functionality to mechanism,” Assembly Automation, vol. 35, no. 3, pp. 281-286, 2015.
[50] R. Jiang, H. Qiao and B. Zhang, “Speeding Up Graph Regularized Sparse Coding by Dual Gradient Ascent,” Signal Processing Letters, IEEE, vol. 22, no. 3, pp. 313-317, 2015.
[51] W. S. Feng, H. Lei and H. Qiao, “Synthetic aperture radar image despeckling via total generalised variation approach,” IET Image Processing, vol. 9, no. 3, pp. 236-248, 2015.
[52] Y. Tang, Z. D. Wang, H. J. Gao, H. Qiao and K. Jurgen, “On Controllability of Neuronal Networks With Constraints on the Average of Control Gains,” IEEE Transactions on Cybernetics, vol. 44, no. 12, pp. 2670-2681, 2014.
[53] T. Tang and H. Qiao, “Improving invariance in visual classification with biologically inspired mechanism,” Neurocomputing, vol. 133, no. 0, pp. 328-341, 2014.
2014
[54] J. H. Su, E. H. Cao and H. Qiao, “Optimization of fixture layouts of glass laser optics using multiple kernel regression,” Applied Optics, vol. 53, no. 14, pp. 2988-2997, 2014.
[55] H. Qiao, Y. L. Li, T. Tang and P. Wang, “Introducing Memory and Association Mechanism Into a Biologically Inspired Visual Model,” IEEE Transactions on Cybernetics, vol. 44, no. 9, pp. 1485-1496, 2014.
[56] Z. Y. Liu, H. Qiao, X. Yang and S. C. H. Hoi, “Graph Matching by Simplified Convex-Concave Relaxation Procedure,” International Journal of Computer Vision, vol. 109, no. 3, pp. 169-186, 2014.
[57] Z. Y. Liu, H. Qiao, L. H. Jia and L. Xu, “A graph matching algorithm based on concavely regularized convex relaxation,” Neurocomputing, vol. 134, no. 0, pp. 140-148, 2014.
[58] Z. Y. Liu and H. Qiao, “GNCCP - Graduated NonConvexity and Concavity Procedure,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 36, no. 6, pp. 1258-1267, 2014.
[59] C. K. Liu, H. Qiao, J. H. Su and P. Zhang, “Vision-Based 3-D Grasping of 3-D Objects With a Simple 2-D Gripper,” Systems, Man, and Cybernetics: Systems, IEEE Transactions on, vol. 44, no. 5, pp. 605-620, 2014.
[60] M. Y. Fan, N. N. Gu, H. Qiao and B. Zhang, “Dimensionality reduction: An interpretation from manifold regularization perspective,” Information Sciences, vol. 277, no., pp. 694-714, 2014.
[61] Y. J. Chen, W. S. Feng, R. Ranftl, H. Qiao and T. Pock, “A Higher-Order MRF Based Variational Model for Multiplicative Noise Reduction,” Signal Processing Letters, IEEE, vol. 21, no. 11, pp. 1370-1374, 2014.
[62] X. Yang, H. Qiao and Z. Y. Liu, “Partial correspondence based on subgraph matching,” Neurocomputing, vol. 122, no. 0, pp. 193-197, 2013.
2013
[63] D. Wang, H. Qiao, B. Zhang and M. Wang, “Online Support Vector Machine Based on Convex Hull Vertices Selection,” Neural Networks and Learning Systems, IEEE Transactions on, vol. 24, no. 4, pp. 593-609, 2013.
[64] D. C. Ren, P. Wang, H. Qiao and S. W. Zheng, “A biologically inspired model of emotion eliciting from visual stimuli,” Neurocomputing, vol. 121, no. 0, pp. 328-336, 2013.
[65] H. Qiao, P. Zhang, W. Di and B. Zhang, “An Explicit Nonlinear Mapping for Manifold Learning,” IEEE Transactions on Cybernetics, vol. 43, no. 1, pp. 51-63, 2013.
2012
[66] J. H. Su, H. Qiao, Z. C. Ou and Y. R. Zhang, “Sensor‐less insertion strategy for an eccentric peg in a hole of the crankshaft and bearing assembly,” Assembly Automation, vol. 32, no. 1, pp. 86-99, 2012.
[67] J. H. Su, H. Qiao, C. K. Liu and Z. C. Ou, “A new insertion strategy for a peg in an unfixed hole of the piston rod assembly,” The International Journal of Advanced Manufacturing Technology, vol. 59, no. 9-12, pp. 1211-1225, 2012.
[68] Z. C. Ou, P. Wang, J. H. Su and H. Qiao, “Sub-pattern bilinear model and its application in pose estimation of work-pieces,” Neurocomputing, vol. 83, no. 0, pp. 176-187, 2012.
[69] Z. Y. Liu, H. Qiao and L. Xu, “An Extended Path Following Algorithm for Graph-Matching Problem,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 34, no. 7, pp. 1451-1456, 2012.
[70] W. Liu, P. Wang and H. Qiao, “Part-based adaptive detection of workpieces using differential evolution,” Signal Processing, vol. 92, no. 2, pp. 301-307, 2012.
[71] W. Liu, T. S. Chen, P. Wang and H. Qiao, “Pose Estimation for 3D Workpiece Grasping in Industrial Environment Based on Evolutionary Algorithm,” Journal of Intelligent & Robotic Systems, vol. 68, no. 3-4, pp. 293-306, 2012.
[72] W. Y. Li, P. Wang and H. Qiao, "Double Least Squares Pursuit for Sparse Decomposition," Intelligent Information Processing VI, pp. 357-363, 2012.
[73] N. N. Gu, M. Y. Fan, H. Qiao and B. Zhang, “Discriminative Sparsity Preserving Projections for Semi-Supervised Dimensionality Reduction,” Signal Processing Letters, IEEE, vol. 19, no. 7, pp. 391-394, 2012.
2011
[74] S. W. Zheng, H. Qiao, B. Zhang and P. Zhang, “Tracking uncooperative person using a dynamic vision platform,” Transactions of the Institute of Measurement and Control, vol. 33, no. 7, pp. 823-845, 2011.
[75] P. Zhang, H. Qiao and B. Zhang, “An improved local tangent space alignment method for manifold learning,” Pattern Recognition Letters, vol. 32, no. 2, pp. 181-189, 2011.
[76] Y. W. Xu, X. B. Cao and H. Qiao, “An Efficient Tree Classifier Ensemble-Based Approach for Pedestrian Detection,” Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, vol. 41, no. 1, pp. 107-117, 2011.
[77] P. Wang and H. Qiao, “Online Appearance Model Learning and Generation for Adaptive Visual Tracking,” Circuits and Systems for Video Technology, IEEE Transactions on, vol. 21, no. 2, pp. 156-169, 2011.
[78] M. Wang, H. Qiao and B. Zhang, “A New Algorithm for Robust Pedestrian Tracking Based on Manifold Learning and Feature Selection,” Intelligent Transportation Systems, IEEE Transactions on, vol. 12, no. 4, pp. 1195-1208, 2011.
[79] H. Qiao, P. Zhang, B. Zhang and S. W. Zheng, “Tracking feature extraction based on manifold learning framework,” Journal of Experimental & Theoretical Artificial Intelligence, vol. 23, no. 1, pp. 23-38, 2011.
[80] Z. Y. Liu and H. Qiao, “Investigation on the skewness for independent component analysis,” Science China-Information Sciences, vol. 54, no. 4, pp. 849-860, 2011.
[81] C. K. Liu, H. Qiao and B. Zhang, “Stable Sensorless Localization of 3-D Objects,” Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, vol. 41, no. 6, pp. 923-941, 2011.
[82] M. Y. Fan, N. N. Gu, H. Qiao and B. Zhang, “Sparse regularization for semi-supervised classification,” Pattern Recognition, vol. 44, no. 8, pp. 1777-1784, 2011.
2010
[83] S. H. Ying and H. Qiao, “Lie group method: A new approach to image matching with arbitrary orientations,” International Journal of Imaging Systems and Technology, vol. 20, no. 3, pp. 245-252, 2010.
[84] D. Wang, B. Zhang, P. Zhang and H. Qiao, “An online core vector machine with adaptive MEB adjustment,” Pattern Recognition, vol. 43, no. 10, pp. 3468-3482, 2010.
[85] H. Qiao, P. Zhang, B. Zhang and S. W. Zheng, “Learning an Intrinsic-Variable Preserving Manifold for Dynamic Visual Tracking,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 40, no. 3, pp. 868-880, 2010.
Before 2010
[86] S. Y. Zhang, C. Tjortjis, X. J. Zeng, H. Qiao, I. Buchan and J. Keane, “Comparing data mining methods with logistic regression in childhood obesity prediction,” Information Systems Frontiers, vol. 11, no. 4, pp. 449-460, 2009.
[87] S. H. YING, J. G. PENG, S. Y. DU and H. QIAO, “LIE GROUP FRAMEWORK OF ITERATIVE CLOSEST POINT ALGORITHM FOR n-D DATA REGISTRATION,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 23, no. 06, pp. 1201-1220, 2009.
[88] S. H. Ying, J. G. Peng, S. Y. Du and H. Qiao, “A Scale Stretch Method Based on ICP for 3D Data Registration,” Automation Science and Engineering, IEEE Transactions on, vol. 6, no. 3, pp. 559-565, 2009.
[89] P. Wang and H. Qiao, “Adaptive probabilistic tracking with reliable particle selection,” Electronics Letters, vol. 45, no. 23, pp. 1160-1161, 2009.
[90] H. Qiao and S. Y. Li, “A Fast Algorithm in Collision Detection and Motion Analysis of 3D Polyhedral Parts and its Application in Industry,” INTELLIGENT AUTOMATION AND SOFT COMPUTING, vol. 15, no. 1, pp. 13-28, 2009.
[91] Z. Y. Liu and H. Qiao, “Multiple ellipses detection in noisy environments: A hierarchical approach,” Pattern Recognition, vol. 42, no. 11, pp. 2421-2433, 2009.
[92] M. Y. Fan, H. Qiao and B. Zhang, “Intrinsic dimension estimation of manifolds by incising balls,” Pattern Recognition, vol. 42, no. 5, pp. 780-787, 2009.
[93] X. B. Cao, Y. W. Xu, D. Chen and H. Qiao, “Associated evolution of a support vector machine-based classifier for pedestrian detection,” Information Sciences, vol. 179, no. 8, pp. 1070-1077, 2009.
[94] X. B. Cao, H. Qiao and J. Keane, “A Low-Cost Pedestrian-Detection System With a Single Optical Camera,” Intelligent Transportation Systems, IEEE Transactions on, vol. 9, no. 1, pp. 58-67, 2008.
[95] H. Qiao, Y. G. Wang and B. Zhang, “A simple decomposition algorithm for support vector machines with polynomial-time convergence,” Pattern Recognition, vol. 40, no. 9, pp. 2543-2549, 2007.
[96] Z. Y. LIU, H. QIAO and L. XU, “INVESTIGATION ON MULTISETS MIXTURE LEARNING BASED OBJECT DETECTION,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 21, no. 08, pp. 1339-1351, 2007.
[97] X. B. Cao, H. Qiao and Y. W. Xu, “Negative selection based immune optimization,” Advances in Engineering Software, vol. 38, no. 10, pp. 649-656, 2007.
[98] Y. W. Xu, X. B. Cao, H. Qiao and F. Y. Wang, "Fast Pedestrian Detection Using Color Information," Intelligence and Security Informatics, Lecture Notes in Computer Science, pp. 627-632, 2006.
[99] A. H. Wan, M. S. Wang, J. G. Peng and H. Qiao, “Exponential stability of Cohen–Grossberg neural networks with a general class of activation functions,” Physics Letters A, vol. 350, no. 1–2, pp. 96-102, 2006.
[100] A. H. Wan, H. Qiao, J. G. Peng and M. S. Wang, “Delay-independent criteria for exponential stability of generalized Cohen–Grossberg neural networks with discrete delays,” Physics Letters A, vol. 353, no. 2–3, pp. 151-157, 2006.
[101] Z. Y. Liu, H. Qiao and L. Xu, “Multisets mixture learning-based ellipse detection,” Pattern Recognition, vol. 39, no. 4, pp. 731-735, 2006.
[102] Z. Y. Liu and H. Qiao, "Hidden Markov Model Based Intrusion Detection," Intelligence and Security Informatics, Lecture Notes in Computer Science, pp. 169-170, 2006.
[103] D. Chen, X. B. Cao, H. Qiao and F. Y. Wang, "A Multiclass Classifier to Detect Pedestrians and Acquire Their Moving Styles," Intelligence and Security Informatics, Lecture Notes in Computer Science, pp. 758-759, 2006.
[104] H. Qiao, F. Y. Wang and X. B. Cao, "Application of a Decomposed Support Vector Machine Algorithm in Pedestrian Detection from a Moving Vehicle," Intelligence and Security Informatics, Lecture Notes in Computer Science, pp. 662-663, 2005.
[105] J. G. Peng, Z. B. Xu, H. Qiao and B. Zhang, “A critical analysis on global convergence of Hopfield-type neural networks,” Circuits and Systems I: Regular Papers, IEEE Transactions on, vol. 52, no. 4, pp. 804-814, 2005.
[106] X. B. Cao, H. Qiao, F. Y. Wang and X. Z. Zhang, "Application of cooperative co-evolution in pedestrian detection systems," Intelligence and Security Informatics, pp. 664-665, 2005.
[107] Z. B. Xu, H. Qiao, J. G. Peng and B. Zhang, “A comparative study of two modeling approaches in neural networks,” Neural Networks, vol. 17, no. 1, pp. 73-85, 2004.
[108] Z. D. Wang and H. Qiao, “H ∞ Reliable Control of Uncertain Linear State Delayed Systems,” Journal of Dynamical and Control Systems, vol. 10, no. 1, pp. 55-76, 2004.
[109] X. Zhu and H. Qiao, “Obstacle avoidance for kinematically redundant manipulators using polyhedral approximations,” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 217, no. 5, pp. 533-542, 2003.
[110] H. Qiao, J. G. Peng, Z. B. Xu and B. Zhang, “A reference model approach to stability analysis of neural networks,” Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, vol. 33, no. 6, pp. 925-936, 2003.
[111] H. Qiao, L. Y. Kang, M. Cardei and D. Z. Du, “Paired-domination of Trees,” Journal of Global Optimization, vol. 25, no. 1, pp. 43-54, 2003.
[112] H. Qiao, “Two- and three-dimensional part orientation by sensor-less grasping and pushing actions: Use of the concept of 'attractive region in environment',” International Journal of Production Research, vol. 41, no. 14, pp. 3159-3184, 2003.
[113] L. Y. Kang, H. Qiao, E. F. Shan and D. Z. Du, “Lower bounds on the minus domination and k-subdomination numbers,” Theoretical Computer Science, vol. 296, no. 1, pp. 89-98, 2003.
[114] Z. D. Wang, H. Qiao and B. K. J., “On stabilization of bilinear uncertain time-delay stochastic systems with Markovian jumping parameters,” Automatic Control, IEEE Transactions on, vol. 47, no. 4, pp. 640-646, 2002.
[115] Z. D. Wang and H. Qiao, “Robust filtering for bilinear uncertain stochastic discrete-time systems,” Signal Processing, IEEE Transactions on, vol. 50, no. 3, pp. 560-567, 2002.
[116] H. Qiao, Q. S. Li and G. Q. Li, “Vibratory characteristics of flexural non-uniform Euler–Bernoulli beams carrying an arbitrary number of spring–mass systems,” International Journal of Mechanical Sciences, vol. 44, no. 4, pp. 725-743, 2002.
[117] H. Qiao, Q. S. Li and G. Q. Li, “Torsional Vibration of Non-Uniform Shafts Carrying an Arbitrary Number of Rigid Disks,” Journal of Vibration and Acoustics, vol. 124, no. 4, pp. 656-659, 2002.
[118] H. Qiao and Q. S. Li, “Stability of Tapered Columns Under End-Concentrated and Variably Distributed Follower Forces,” AIAA Journal, vol. 40, no. 6, pp. 1250-1252, 2002.
[119] H. Qiao, “Attractive regions formed by the environment in configuration space: The possibility of achieving high precision sensorless manipulation in production,” International Journal of Production Research, vol. 40, no. 4, pp. 975-1002, 2002.
[120] H. Qiao, “The Combination of Attractive Regions and Pre-images in Motion Planning,” Journal of Manufacturing Science and Engineering, vol. 124, no. 2, pp. 341-350, 2002.
[121] W. H. Qian and H. Qiao, “An efficient algorithm for computing object poses in a modular fixture or gripper,” Journal of Robotic Systems, vol. 19, no. 3, pp. 99-114, 2002.
[122] J. G. Peng, H. Qiao and Z. B. Xu, “A new approach to stability of neural networks with time-varying delays,” Neural Networks, vol. 15, no. 1, pp. 95-103, 2002.
[123] Q. Tao, T. J. Fang and H. Qiao, “A novel continuous-time neural network for realizing associative memory,” Neural Networks, IEEE Transactions on, vol. 12, no. 2, pp. 418-423, 2001.
[124] Q. Tao, J. D. Cao, M. S. Xue and H. Qiao, “A high performance neural network for solving nonlinear programming problems with hybrid constraints,” Physics Letters A, vol. 288, no. 2, pp. 88-94, 2001.
[125] H. Qiao, J. S. Zhang and Z. B. Xu, “A new data processing method based on a biological model of the compound eye: direction quantization representation,” Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, vol. 31, no. 3, pp. 238-245, 2001.
[126] H. Qiao, J. G. Peng and Z. B. Xu, “Nonlinear measures: a new approach to exponential stability analysis for Hopfield-type neural networks,” Neural Networks, IEEE Transactions on, vol. 12, no. 2, pp. 360-370, 2001.
[127] W. H. Qian, H. Qiao and S. K. Tso, “Synthesizing two-fingered grippers for positioning and identifying objects,” Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, vol. 31, no. 4, pp. 602-615, 2001.
[128] X. W. Ma, X. L. Li and H. Qiao, “Fuzzy neural network-based real-time self-reaction of mobile robot in unknown environments,” Mechatronics, vol. 11, no. 8, pp. 1039-1052, 2001.
[129] H. Qiao and B. Zhang, “Combination of strategy investigation and utilization of sensor signals in robotic assembly,” Proceedings of The Institution of Mechanical Engineers Part B-journal of Engineering Manufacture, vol. 214, no. 8, pp. 657-669, 2000.
[130] H. Qiao, Y. H. Ren and B. Zhang, “Approximate Solution of a Class of Radiative Heat Transfer Problems,” Journal of Heat Transfer, vol. 122, no. 3, pp. 606-612, 2000.
[131] H. Qiao, “The Foster Adoption of Manufacturing Strategies,” Informatics, vol. 3, no. 1, pp. 97-114, 2000.
[132] Y. H. Ren, B. Zhang and H. Qiao, “A simple Taylor-series expansion method for a class of second kind integral equations,” Journal of Computational and Applied Mathematics, vol. 110, no. 1, pp. 15-24, 1999.
[133] H. Qiao and S. K. Tso, “Three-step precise robotic peg-hole insertion operation with symmetric regular polyhedral objects,” International Journal of Production Research, vol. 37, no. 15, pp. 3541-3563, 1999.
[134] H. Qiao and S. K. Tso, “Strategy investigation of precise robotic assembly operations with symmetric regular polyhedral objects,” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 212, no. 7, pp. 571-589, 1998.
[135] H. Qiao, P. Moore and J. Knight, “A model and strategy analysis of the peg-hole system in the search process associated with robotic assembly operations without chamfers,” Robotica, vol. 14, no. 06, pp. 647-658, 1996.
[136] H. Qiao, B. S. Dalay and J. A. G. Knight, “Robotic Assembly Operation Strategy Investigation Without Force Sensors Through the Research on Contact Point Location and Range of Peg Movement,” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 210, no. 5, pp. 471-485, 1996.
[137] H. Qiao, B. S. Dalay and R. M. Parkin, “Fine Motion Strategies for Robotic Peg-Hole Insertion,” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 209, no. 6, pp. 429-448, 1995.
[138] H. Qiao, B. S. Dalay and R. M. Parkin, “A novel and practical strategy for the precise chamferless robotic peg hole insertion,” Robotica, vol. 13, no. 01, pp. 29-35, 1995.
[139] H. Qiao, B. S. Dalay and R. M. Parkin, “Precise Robotic Chamferless Peg-Hole Insertion Operation Without Force Feedback and Remote Centre Compliance (RCC),” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 208, no. 2, pp. 89-104, 1994.
[140] H. Qiao, B. S. Dalay and R. M. Parkin, “Robotic Peg-Hole Insertion Operations using a Six-Component Force Sensor,” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 207, no. 5, pp. 289-306, 1993.