Publications

 Peer-Reviewed Journal Papers

1. Keith LeGrand, Pingping Zhu, Silvia Ferrari, "Cell Multi-Bernoulli (Cell-MB) Sensor Control for Multi-object Search-While-Tracking (SWT)," IEEE Transactions on Pattern Analysis and Machine Intelligence,  Nov. 23, 2022. DOI: 10.1109/TPAMI.2022.3223856. [Link][PDF]

2. Pingping Zhu, Chang Liu, Silvia Ferrari, "Adaptive Online Distributed Optimal Control of Very-Large-Scale Robotic Systems," IEEE Transactions on Control of Network Systems, 8, no. 2 (2021): 678-689. [Link][PDF] 

3. Bryce Doerr, Richard Linares, Pingping Zhu, and Silvia Ferrari, "Random Finite Set Theory and Optimal Control of Large Collaborative Swarms," Journal of Guidance, Control, and Dynamics, DOI: 10.2514/1.G004861, 2021 .[Link] [PDF].

4. Pingping Zhu, Silvia Ferrari, Julian Morelli, Richard Linares, and Bryce Doerr, “Scalable Gas Sensing, Mapping, and Path Planning via Decentralized Hilbert Maps,” Sensors, 19(7), pp. 1524, 2019 [Link][PDF]. 

5. Hongchuan Wei, Pingping Zhu, Miao Liu, Jonathan P. How, and Silvia Ferrari, “Automatic Pan-tilt Camera Control for Learning Dirichlet Process Gaussian Process (DPGP) Mixture Models of Multiple Moving Targets,” IEEE Transactions on Automatic Control, 2019 [Link][PDF]. 

6. Keith Rudd, Greg Foderaro, Pingping Zhu, Silvia Ferrari, “A Generalized Reduced Gradient Method for the Optimal Control of Very Large-Scale Robotic Systems,” IEEE Transactions on Robotics, 33 (5), 1226-1232, 2017. [Link][PDF]

7. Hanna Oh, Jeffrey M. Beck, Pingping Zhu, Marc A. Sommer, Silvia Ferrari, Tobias Egner, “Satisficing in split-second decision making is characterized by strategic cue discounting,” Journal of Experimental Psychology: Learning, Memory, and Cognition, 42(12), 1937-1956, 2016. [Link][PDF]

8. Songlin Zhao, Badong Chen, Zheng Cao, Pingping Zhu, Jose C. Principe, “Self-Organizing Kernel Adaptive Filtering,” EURASIP Journal on Advances in Signal Processing, 2016.1 (2016): 106. [Link][PDF]

9. Hongchuan Wei, Wenjie Lu, Pingping Zhu, Silvia Ferrari, Miao Liu, Robert H. Klein, Shayegan Omiddshafiei, Jonathan P. How, “Information value in nonparametric Dirichlet-process Gaussian-process (DPGP) mixture models,” Automatica, 74, 360-368, 2016. [Link][PDF]

10. Greg Foderaro, Pingping Zhu, Hongchuan Wei, Thomas A. Wettergren, Silvia Ferrari, “Distributed Optimal Control of Sensor Networks for Dynamic Target Tracking,” IEEE Transactions on Control of Network Systems, 2016. [Link][PDF]

11. Wenjie Lu, Pingping Zhu, and Silvia Ferrari, “A Hybrid-Adaptive Dynamic Programming Approach for the Model-free Control of Nonlinear Switched Systems,” IEEE Trans. on Automatic Control, Vol. 61 (10), 2015. [Link][PDF]

12. John D. Albertson, Tierney A. Foster-Wittig, Greg Foderaro, Pingping Zhu, Xiaochi Zhou, Silvia Ferrari, Shahrooz Amin, Mark Modrak, Halley Brantley, and Eben D. Thoma, "A Mobile Sensing Approach for Regional Surveillance of Fugitive Methane Emissions in Oil and Gas Production," Environmental Science & Technology, 50, no. 5 (2016): 2487-2497. [Link][PDF]

13. Silvia Ferrari, Greg Foderaro, Pingping Zhu and  Thomas A. Wettergren ,“Distributed Optimal Control: A Tutorial", IEEE Control Systems Magazine,  Vol. 36 (2), 102-116. [Link][PDF]

14. Pingping Zhu, Badong Chen, Jose C. Principe, "Learning Nonlinear Generative Models of Time-Series with a Kalman Filter in RKHS", IEEE Trans. Signal Processing,  Vol. 62 (1): 141-155, 2014. [Link][PDF]

15. Songlin Zhao, Badong Chen, Pingping Zhu, Jose C. Principe, "Fixed Budget Quantized Kernel Least-Mean-Square Algorithm," Signal Processing, Vol. 93(9), 2759-2770, 2013. [Link][PDF]

16. Badong Chen, Songlin Zhao, Pingping Zhu , Jose C. Principe, "Quantized Kernel Recursive Least Squares Algorithm," IEEE Trans. on Neural Networks, Vol. 24, pp. 1484-1491,2013. [Link][PDF]

17. Pingping Zhu, Badong Chen, Jose C. Principe, "A Novel Extended Kernel Recursive Least Squares Algorithm", Neural Networks, Vol.32,349-357, 2012. [Link][PDF]

18. Badong Chen, Songlin Zhao, Pingping Zhu, Jose C. Principe, “Quantized Kernel Least Mean Squares Algorithm”, IEEE Trans. Neural Networks & Learning Systems 23(1): 22-32, 2012. [Link][PDF]

19. Badong Chen, Pingping Zhu, Jose C. Principe, "Survival Information Potential: a New Criterion for Adaptive System Training", Trans. on Signal Processing,  60(3): 1184-1194, 2012. [Link][PDF]

20. Badong Chen, Songlin Zhao, Pingping Zhu, Jose C. Principe, "Mean square convergence analysis for kernel least mean square algorithm",, Signal Processing 92(11): 2624-2632, 2012. [Link][PDF]

21. Pingping Zhu, Jianguo Liu, Shengkui Dai, “Fixed-Point IDCT without multiplications based on B. G. Lee’s algorithm”, Digital Signal Processing, Volume. 19, Issue 4, July, 2009. [Link][PDF]

22. Pingping Zhu, Jianguo Liu, Shengkui Dai, “Scaled AAN for Fixed-point Multiplier-free IDCT”, EURASIP Journal on Advances in Signal Processing, Vol. 2009. [Link][PDF]

23. Shengkui Dai, Jianguo Liu, Guoyou Wang, Pingping Zhu, “Fast Integer-DCT Implement without Multiplication”, Microelectronics & Computer, Vol. 25, No. 5. ,2008. [Link][PDF]

 Peer-Reviewed Conference Papers

1. Yunze Hu, Xuru Yang, Kangjie Zhou, Qinghang Liu, Kang Ding, Han Gao, Pingping Zhu, and Chang Liu. "SwarmPRM: Probabilistic Roadmap Motion Planning for Swarm Robotic Systems," IEEE International Conference on Intelligent Robots and Systems (IROS), 2024. [PDF]

2. Xuru Yang, Yunze Hu, Han Gao, Kang Ding, Pingping Zhu, Ying Sun, and Chang Liu. "ROVER: Risk-Aware Swarm Robotics MOtion Planner Using Conditional ValuE at Risk," IEEE International Conference on Intelligent Robots and Systems (IROS), 2004. [PDF]

3. Pingping Zhu, Chang Liu, and Peter Estephan, "A Novel Multivariate Skew-Normal Mixture Model and Its Application in Path-Planning for Very-Large-Scale Robotic Systems," American Control Conference (ACC), 2024, Toronto, Canada, [PDF]. 

4. Xuru Yang, Han Gao, Pingping Zhu, and Chang Liu, "Risk-Aware Motion Planning for Very-Large-Scale Robotics Systems Using Conditional Value-at-Risk," In International Conference on Intelligent Robotics and Applications (pp. 513-525). Singapore: Springer Nature Singapore, 2023. [PDF]  

5. Pingping Zhu and Jose Principe, "Kernel Nonlinear Dynamic System Identification Based on Expectation-Maximization Method, " IEEE World Congress on Computational Intelligence (IEEE WCCI) - International Joint Conference on Neural Networks (IJCNN), 2022. [PDF][PPT]

6. Hengye Yang, Usama Bin Sikandar, Pingping Zhu, Simon Sponberg, Silvia Ferrari, "Regression-based Spike Train Decoding in a Comprehensive Motor Program for Insect Flight," IEEE World Congress on Computational Intelligence (IEEE WCCI) - International Joint Conference on Neural Networks (IJCNN), 2022.

7. Cong Pu and Pingping Zhu, "Mitigating Routing Misbehavior in the Internet of Drones Environment," IEEE Vehicular Technology Conference, 2022. [Link]

8. Cong Pu and Pingping Zhu, "Defending against Flooding Attacks in the Internet of Drones Environment," IEEE GLOBECOM 2021. [Link]

9. Keith LeGrand, Pingping Zhu, Silvia Ferrari, "A Random Finite Set Control Approach for Vision-based Multi-object Search-While-Tracking," IEEE 24th International Conference on Information Fusion (FUSION) 2021, [Link][PDF]

10. Junyi Dong, Pingping Zhu, Silvia Ferrari, "Oriented Interaction Inference for Autonomous Pedestrian Trajectory Prediction and Tracking," American Control Conference (ACC), 2020. [Link][PDF]

11. Julian Morelli, Pingping Zhu, Bryce Doerr, Richard Linares, and Silvia Ferrari, “Integrated Mapping and Path Planning for Very Large-Scale Robotic (VLSR) Systems,” International Conference on Robotics and Automation (ICRA), 2019. [Link][PDF]

12. Stojanovski, Zvonimir, Pingping Zhu, Keith LeGrand, and Silvia Ferrari. Distributed Pursuit-Evasion Games for Mobile Monitoring and Surveillance. No. SAND2019-5803C. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2019. [PDF]

13. Shi Chang, Jason Isaacs, Bo Fu, Jaejeong Shin, Pingping Zhu, and Silvia Ferrari, “Confidence Level Estimation in Multi-target Classification Problems,” SPIE Defense + Commercial Sensing, 2018. [Link][PDF]

14. Pingping Zhu, Jason Isaacs, Bo Fu, Silvia Ferrari, “Deep Learning Feature Extraction for Target Recognition and Classification in Underwater Sonar Images,” IEEE Conference on Decision and Control (CDC), 2017. [Link][PDF]

15. Pingping Zhu, Julian Morelli, Silvia Ferrari, “Value Function Approximation for Multiscale Dynamical Systems,” IEEE Conference on Decision and Control (CDC), 2016. [Link][PDF]

16. Pingping Zhu,Wenjie Lu, HongchuanWei, Silvia Ferrari, "Multi-Kernel Probability Distribution Regressions," IEEE International Joint Conference on Neural Networks (IJCNN), 2015. [Link][PDF]

17. Hongchuan Wei, Wenjie Lu,  Pingping Zhu, Guoquan Huang, John Leonard, Silvia Ferrari, "Optimized Visibility Motion Planning for Target Tracking and Localization," Intelligent Robots and Systems (IROS) IEEE/RSJ International Conference on, 2014. [Link][PDF]

18. Hongchuan Wei, Wenjie Lu,  Pingping Zhu, Silvia Ferrari, Robert Klein, Shayegan Omidshaei, Patrick How, "Camera Control for Learning Nonlinear Target Dynamics Via Bayesian Nonparametric Dirichlet Process Gaussain Process (DP-GP) Models," Intelligent Robots and Systems (IROS) IEEE/RSJ International Conference on, 2014. [Link][PDF]

19. Pingping Zhu, Jose C. Principe, "Analysis on Extended Kernel Recursive Least Squares Algorithm", International Joint Conference on Neural Networks (IJCNN), 2013. [Link][PDF]

20. Jongmin Lee, Pingping Zhu, Jose C. Principe, "A Parameter-free Kernel Design Based on Cumulative Distribution Function for Correntropy," International Joint Conference on Neural Networks (IJCNN), 2013. [Link][PDF]

21. Pingping Zhu, Jose C. Principe, "Kernel Recurrent System Trained by Real-Time Recurrent Learning Algorithm", Acoustics, Speech, and Signal Processing (ICASSP), International Conference on, 2013. [Link][PDF]

22. Pingping Zhu, Badong Chen, Jose C. Principe, "Extended Kalman Filter Using a Kernel Recursive Least Squares Observer", International Joint Conference on Neural Networks (IJCNN), pp. 1402-1408, Jul. 2011. [Link][PDF]

23. Pingping Zhu, Chao Pan, Jianguo Liu, Chen Hu, “Efficient Fast Algorithm of the Forward MDCT”, the 14th National Conference on Image and Graph, Fuzhou China, 2008. [Link][PDF]

24. Pingping Zhu, Jianguo Liu, Shengkui Dai, “Scaled AAN for Fixed-point Multiplier-free IDCT without Multiplication”, the 14th National Conference on Image and Graph, Fuzhou China, 2008. [Link][PDF]

25. Pingping Zhu, Jianguo Liu, Shengkui Dai, “Fixed-point B.G. Lee IDCT without multiplication”, Proc. of SPIE Vol. 6789 67891W-1, 2007. [Link][PDF]

 Peer-Reviewed Conference Abstracts

1. Hanna Oh, Pingping Zhu, Kim Rafie, Silvia Ferrari, Jerey Beck, Tobias Egner, M. A. Sommer, “Measuring and manipulating satisficing decision strategies in models, humans, and monkeys,” Neuroscience 2014, Washington, DC, November 2014.

2. Hanna Oh, Pingping Zhu, Kim Rafie, Marc A. Sommer, Silvia Ferrari, Jerey Beck, and Tobias Egner, “Satisficing decisionmaking under time pressure,” Cognitive Neuroscience Society Annual Meeting, Boston, MA, April 2014. [PDF]

 Dissertation and Thesis

1. Pingping Zhu, "Kalman Filtering in Reproducing Kernel Hilbert Spaces", University of Florida, 2013. [PDF]

2. Pingping Zhu, "Study of Discrete Cosine Transform Fast Algorithms", Huazhong University of Science and Technology, 2008. [PDF]

 Chinese National Invention Patents

1. Jianguo Liu, Guoyou Wang, Shengkui Dai, Dengpan Ye, Pingping Zhu, Xinjian Meng, Jianhua Zheng, "DCT Method and Application, No. 101046886.

2. Jianguo Liu, Guoyou Wang, Shengkui Dai, Dengpan Ye, Pingping Zhu, Xinjian Meng, Jianhua Zheng, "IDCT Method and Application, No. 101047849

3. Shengkui Dai, Jianguo Liu, Guoyou Wang, Pingping Zhu, Xinjian Meng, Jianhua Zheng, Shijuan Shu, Mingcheng Han, "An Implementation of Data Decoding Method and Device", No. 101420608.

 Manuscripts under Review or in Preparation

1. Pingping Zhu, "Online Adaptive Path-Planning for Very-Large-Scale Robotic Systems Based on Multivariate Skew-Normal Mixture Model," IEEE Transactions on Robotics, under preparation.  

2. Chang Liu, Pingping Zhu, Silvia Ferrari, "Analysis and Optimization of Sampling Times for Learning Spatio-Temporal Processes Modeled by Gaussian Processes," IEEE Transactions on Systems, Man and Cybernetics: Systems, submitted.

3. Bo Fu, Ziliang Mao, Shan Zhou, Yu Yan Cui, Pingping Zhu, John D. Albertson, Jaejeong Shin, "Real-Time Infrared Methane Emissions Surveillance  (RIMES) for Oil and Natural Gas Production Sites", Environmental Science & Technology Letters, submitted.

All of the published papers can be found at my google scholar website

If you cannot find my papers, please email me at zhup@marshall.edu.