I am a simulation and modeling scientist and head of the laboratory of simulation science for complex ecosystems. I have directed several National Science Foundation funded scientific projects and international programs in cooperated with researchers from USA, Germany, Israel, Canada and Norway. The focus of my research efforts is on modeling the structures, dynamics and functions of agro-ecological systems, particularly pollination service under the influence of climate change. I believe that simulation models are critical tools to discover hidden relations and knowledge from complex agro-ecosystems where field experiments are usually very difficult or even impossible in terms of spatial and temporal cost. As an interdisciplinary research, I think the biggest challenge is to find innovative methods for automatic knowledge discovery from various data sources, and based on that, to develop a new generation of theory-driven, simulation/data-based ecological models which will be used to predict system response to environmental disturbances. My current interest is the convergence of data-based model and simulation-based model in dealing with ecological safety issues.

Area of Expertise: Ecological Modeling, Simulation-based Modeling, Predictive Modeling, Pattern-Oriented Modeling, Data Science, Machine Learning and Computational Intelligence.

Research Opportunities: My lab is hiring one or two PhD students who are specialized in machine learning or simulation modeling. Experiences in python programing and mathematical modeling are merits. They are expected to work closely with other lab members to develop deep learning methods/theories of automatic pattern discovery from ecological BIG DATA. 

Education:

1997-2001        B.S., Civil Engineering, Anhui University of Science & Technology, China

2003-2005        MSc., Computer Science, Chongqing University, China, advisor: Prof. Dr. Hegang Fu.

2006-2009        PhD, Computer Science, Chongqing University, China, advisor: Prof. Dr. Qingsheng Zhu (Exchange PhD program with Iowa State University, USA)

Professional Experience:

2001-2003        Software Engineer, Shanghai Sywiz Hi-Tech, China

2003-2008        Research Assistant; Chongqing University, China

2008-2009        Research Assistant, Iowa State University, USA

2010-2012        Associate Professor, Chongqing University of Posts & Telecommunications, China

2012-2013        Postdoc, Depart of Plant Ecology, University Tübingen, Germany

2013-                  Professor, Chongqing University of Posts & Telecommunications, China

2015-                  Senior Scientist, School of Biology and Ecology, University of Maine, USA.

Areas of expertise:

                            Simulation based modelling, Computational intelligence, Machine learning and data science

Selected research projects:

Multigranular predictive model and validation for sustainability of pollination service subject to environmental disturbance (NSFC grant No: 61871061, 2019~2022)

Multi-scale patterns emergence, identification and analysis for agro-ecosystems (NSFC grant No: 61374093, 2014~2017)                                        

Simulation and modelling of plant phenotype plasticity subject to environmental heterogeneities (NSFC grant No: 61102145, 2012~2014)

Massive Agent Coordination and Control for Industrial IOT (No: cstc2013jcyjA40014, 2013-2016)

CPS runtime anomaly detection for industrial environment v4.0 (No: cstc2017jcyjAX0453, 2017-2020)

Multi-Agents-based Functional-Structural Plant Model in Response to Environmental Heterogeneities (No: KJ110520, 2011-2014)

Professional activities:                 

2013-                 Review board of the National Natural Science Foundation of China

2013-                 Consultant and Review board of the Chongqing Science Commission

                          Reviewer for international journals: IEEE TFS, TSCVT, TII, Simulation, Simulation Modeling Practice and Theory, Ecological Modelling, International Journal on Artificial Intelligence Tools, Journal of Simulation, Complexity, ISA Transactions.

Supervision:

                            42 MSc Theses, 6 PhD Theses

Memberships:

                            Senior Member of Chinese Simulation Federation, Chinese Association of Automation, Josselyn Botanical Society of Maine

Representative publications:

1. H Qu, J Xu, Z Li, D Wei, F Wang. 2023. Effects of embedded distance measurements interacting with modeling approaches on empirical dynamical model predictions. Ecological Indicators 146, 109895.

2. EY Obsie, H Qu, YJ Zhang, S Annis, F Drummond. 2023. Yolov5s-CA: An Improved Yolov5 Based on the Attention Mechanism for Mummy Berry Disease Detection. Agriculture 13 (1), 78.

3. L Li, Z Li, J Zheng, H Qu. 2022. Unsupervised dimensionality reduction by jointing dynamic hypergraph and low-rank embedding for classification and clustering. Expert Systems with Applications 208, 118225.
   

4. Z Cao, G He, S Mu, H Qu. 2023. Effects of Bee Density and Hive Distribution on Pollination Efficiency for Greenhouse Strawberries: A Simulation Study. Agronomy 13 (3), 731.

5. D Wei, J Zheng, H Qu. 2023. Anomaly detection for blueberry data using sparse autoencoder-support vector machine. PeerJ Computer Science 9, e1214.

6. H Qu, M Sun. 2022. A lightweight network for mummy berry disease recognition. Smart Agricultural Technology 2, 100044.

7. H Qu, L Li, Z Li, J Zheng, X Tang. 2022. Robust discriminative projection with dynamic graph regularization for feature extraction and classification. Knowledge-Based Systems 253, 109563

8. J Zheng, H Qu, Z Li, L Li, X Tang, F Guo. 2022. A novel autoencoder approach to feature extraction with linear separability for high-dimensional data. PeerJ Computer Science 8, e1061.

9. L Li, H Qu, Z Li, J Zheng, F Guo. 2022. Discriminative Projection Learning With Adaptive Reversed Graph Embedding for Supervised and Semi-Supervised Dimensionality Reduction. IEEE Transactions on Circuits and Systems for Video Technology 32 (12), 8688. 

10. H Qu, J Zheng, X Tang. 2022. Effects of loss function and data sparsity on smooth manifold extraction with deep model. Expert Systems With Applications 198, 116851.

11. H Qu, J Xu. 2022. Forecasts of Ecological Time Series based on Vector Similarity S-Map. Proceedings of the 14th International Conference on Computer Modeling and Simulation. 

12. J Zheng, H Qu, Z Li, L Li, X Tang. 2022. A deep hypersphere approach to high-dimensional anomaly detection. Applied Soft Computing, 109146. 

13. H Qu, Y Zheng, L Li, F Guo. 2022. An Unsupervised Feature Extraction Approach Based on Self-Expression. Big Data.

14. J Zheng, H Qu, Z Li, L Li, X Tang. 2022. An irrelevant attributes resistant approach to anomaly detection in high-dimensional space using a deep hypersphere structure. Applied Soft Computing 116, 108301.

15. F Guo, J Wang, J Zhou, K Qian, H Qu, P Liu, S Zhai. 2022. All-atom molecular dynamics simulations of the combined effects of different phospholipids and cholesterol content on electroporation. RSC advances 12 (38), 24491-24500.

16. H Qu, L Yin, X Tang. 2022. Multi-objective automatic clustering with gene rearrangement and cluster merging. Advances in Intelligent Systems Research and Innovation, 87-127.

17. H Qu, L Li, Z Li, J Zheng. 2021. Supervised discriminant isomap with maximum margin graph regularization for dimensionality reduction. Expert Systems with Applications 180, 115055. 

18. H Qu, R Xiang, EY Obsie, D Wei, F Drummond. 2021. Parameterization and calibration of wild blueberry machine learning models to predict fruit-set in the northeast china bog blueberry agroecosystem. Agronomy 11 (9), 1736.

19. H Qu, Y Li, W Liu. 2021. Robust Constrained Model Predictive Control for TS Fuzzy Uncertain System with Data Loss and Data Quantization. Complexity 2021, 1-25.

20. H Qu, L Yin, X Tang. 2021. An automatic clustering method using multi-objective genetic algorithm with gene rearrangement and cluster merging. Applied Soft Computing 99, 106929.

21. Z Cao, M Shao, L Xu, S Mu, H Qu. 2021. MaskHunter: real‐time object detection of face masks during the COVID‐19 pandemic. IET Image Processing 14 (16), 4359-4367.

22. EY Obsie, H Qu, F Drummond. 2020. Wild blueberry yield prediction using a combination of computer simulation and machine learning algorithms. Computers and Electronics in Agriculture 178, 105778.

23. H Qu, G Liu. 2020. Threshold optimized strategy based on improved flower pollination algorithm for unbalanced data. 2020 IEEE 10th International Conference on Intelligent Systems (IS), 551-556.

24. H Qu, L Yin. 2020. An automatic clustering algorithm using nsga-ii with gene rearrangement. 2020 IEEE 10th International Conference on Intelligent Systems (IS), 503-509. 

25. H Qu, Z Li, J Wu. 2020. Integrated learning method for anomaly detection combining KLSH and isolation principles. 2020 IEEE Congress on Evolutionary Computation (CEC), 1-6.

26. H Qu, X Yao, L Yin. 2020. Parallel Computing of Multi-Agent System in Spatially-Explicit Modeling and Simulation. Journal of System Simulation 32 (3), 446. 

27. H Qu, J Wu, Z Li. 2019. A New Clustering Algorithm Inspired by Insect Pollination. 2019 Chinese Automation Congress (CAC), 1293-1298. 

28. S Wang, X Tang, L Deng, H Qu, L Tian, C Tan. 2019. Predictive control for interval type-2 fuzzy system with event-triggered scheme. Advances in Fuzzy Systems 2019.

29. T Xiao-Ming, D Li, Y Ji-Min, H Qu. 2019. Output feedback model predictive control for interval type-2 TS fuzzy networked control systems. Acta Automatica Sinica 45 (3), 604-616. 
    

30. QU H.C., QIU Z.L., TANG X.M., XIANG M., WANG P. 2018. Incorporating unsupervised learning into intrusion detection for wireless sensor networks with structural co-evolvability. Applied Soft Computing. 71: 939-951. (IF=3.907, SCI JCR Q1)

31. QU H.C., DRUMMOND F. 2018: Simulation-based Modeling of Wild Blueberry Pollination. Computers and Electronics in Agriculture, 144: 94–101. (IF=2.427, SCI JCR Q1)

32. QU H.C., SEIFAN T., SEIFAN M. 2017: Effects of plant and pollinator traits on the maintenance of a food deceptive species within a plant community. Oikos, 126: 1815–1826. (IF=4.03, SCI JCR Q1)

33. QU, H.C., SEIFAN, T., TIELBOGER, K., SEIFAN, M. 2013: A spatially explicit agent-based simulation platform for investigating effects of shared pollination service on ecological communities. Simulation Modelling Practice and Theory 37: 107. (IF=2.092, SCI JCR Q1)

34. QU H.C., WANG, Y., CAI, L., WANG, T., LU, Z. 2012: Orange tree simulation under heterogeneous environment using agent-based model ORASIM. Simulation Modelling Practice and Theory 23:19. (IF=2.092, SCI JCR Q1)

35. QU H.C., ZHU, Q., GUO, M., LU, Z. 2010: Simulation of carbon-based model for virtual plants as complex adaptive system. Simulation Modelling Practice and Theory 18: 677. (IF=2.092, SCI JCR Q1)

36. TANG, X.M, DENG, L., YU J.M., QU H.C. 2017: Output Feedback Predictive Control of Interval Type-2 T-S Fuzzy Systems with Markovian Packet Loss，IEEE Transactions on Fuzzy Systems，26(4): 2450 – 2459. (IF=8.415, SCI JCR Q1)

37. TANG, X.M, YANG S., DENG L., QU H.C., YU J.M. 2018. Improved predictive control approach to networked control systems based on quantization dependent Lyapunov function. ISA Transactions. DOI:10.1016/j.isatra.2018.07.045. (IF=3.370, SCI JCR Q1)

38. TANG, X.M, QU H.C., WANG, P., ZHAO, M. 2015: Constrained off-line synthesis approach of model predictive control for networked control systems with network-induced delays. ISA Transactions 55:135. (IF=3.370, SCI JCR Q1)

39. LI, C.Y., ZUG, C., QU H.C., SCHLUESENER H., ZHANG, Z.Y., 2015: Hesperidin ameliorates behavioral impairments and neuropathology of transgenic APP/PS1 mice. Behavioural Brain Research, 281:32~42. (IF=3.173, SCI JCR Q1)

40. TANG, X.M, YANG S., YU J.M., QU H.C., 2018. Guaranteed Cost Control of Networked Control Systems with Bounded Packet Loss Based on Quantization Dependent Lyapunov Function. 自动化学报/Acta Automatic Sinica. 44(8): 1381-1390. (CAA-A)

41. DENG L., TANG, X.M, YU J.M., QU H.C., 2018. Output Feedback Model Predictive Control for Interval Type-2 T-S Fuzzy Networked Control Systems with Bounded Disturbance. 自动化学报/Acta Automatic Sinica. AAS-CN-2017-0554 (CAA-A)        

42. QU H.C., Lei L.B., TANG X.M., WANG P. 2018. A Lightweight Intrusion Detection Method Based on Fuzzy Clustering Algorithm for Wireless Sensor Networks. Advances in Fuzzy Systems. DOI:10.1155/2018/4071851, Article ID 4071851. (SCI, IDS:GK0GP, WOS:000435787300001)

43. QU H.C., ZOU K.D., ZHONG D.D., YIN L., TANG X.M. 2018. A Simulation Approach to Understanding the Effect of Mimicry on Prey’s Flourishing When Predators Decline Due to Environmental Disturbance. Journal of Environmental Accounting and Management. DOI:10.5890/JEAM.2018.9.005 (SCI, IDS: GW5SO, WOS: 000446997900005)

44. QU H.C., QIU, Z.L., TANG, X.M., XIANG, M., WANG, P. 2017. An Adaptive Intrusion Detection Method for Wireless Sensor Networks. International Journal of Advanced Computer Science and Applications. 8(11):27-36 (SCI, IDS:FP9RJ, WOS:000417985900004).

45. TANG, X.M, QU H.C., XIE H.F., WANG, P. 2013: Model predictive control of linear systems over networks with state and input quantizations. Mathematical Problems in Engineering Article ID 492804. (SCI, IDS:279PE, WOS:000328971100001)

46. CAI, L.Q., YANG, Z., YANG, S.X., QU H.C., 2013. Modelling and Simulating of Risk Behaviours in Virtual Environments Based on Multi-Agent and Fuzzy Logic. International Journal of Advanced Robotic Systems. Article Number: 387. (SCI, IDS:250OV, WOS:000326863200001)

47. QU H.C., ZHU, Q., FU, H.G., ZENG, L.Q., GUO, M.W., LU, Z. Automatic L-System Discovery for Virtual Plants by Branching Pattern Analysis of Unfoliaged Trees. Journal of Computational and Theoretical Nanoscience. 2010, 7(5):900-910 (SCI, IDS:595MR, WOS:000277615300015)

48. QU H.C., CAI, L.Q., LU, Z., WANG Y.L. Automatic extraction of ramification pattern for living plants: A review. Scientific Research and Essays. 2010, 5(23): 3550-3563 (SCI, IDS:709IT, WOS:000286432400001).

49. QU H.C., ZHU, Q., GUO, M., LU, Z. 2009: An intelligent learning approach to l-grammar extraction from image sequences of real plants. International Journal on Artificial Intelligence Tools 18: 905. (SCI, IDS:541OM, WOS:00027273425700005)

50. QU H.C., ZHU, Q., FU, H.G., DENG, Q.Q., GE, L. 2007. Modelling and Constructing of Intelligent Physiological Engine Merging Artificial Life for Virtual Plants. Journal of Computational and Theoretical Nanoscience. 4(7):1405-1411 (SCI, IDS:595MR, WOS: 000252406200033).