Professor Shigang Yue

Professor Shigang Yue has wide research interests in the field of artificial intelligence, computer vision, robotics, brains, and neuroscience. He is particularly interested in biological visual neural systems, bio-inspired visual neural networks and applications to autonomous robots, vehicles and systems. He has also had research interest in medical image analysis, machine learning and swarm intelligence.

He has published more than 200 journal and conference papers in the above fields. He has chaired international conferences, seats in editorial boards and/or acts as a reviewer for several reputable international journals. He is a member of EPSRC peer review college. He is the coordinator for several EU FP7 and Horizon 2020 projects. He has examined 16 PhD thesis and 2 MSc by Research as an examiner.

Professor Shigang Yue received his PhD and MSc degrees from Beijing University of Technology (BJUT) in 1996 and 1993 respectively. Since 1996, he has worked in several universities in China and the Europe, for example, BJUT (1996-1999), City University of Hong Kong (1998-1999),  UCL (2002-2003), Newcastle University (2003-2006), the University of Cambridge (2006-2007), and the University of Lincoln (2007-2023). He was an Alexander von Humboldt Research Fellow (2000-2001) worked with Prof. Henrich in the University of Kaiserslautern, Germany. He joined the University of Leicester from Feb 2023. 

Talented students and academic visitors are welcome to contact Professor Yue directly, start with a short email, for PhD or visiting opportunities in his group. In Leicester, there are 25 CSC PhD studentship this year, more details in (CSC). Postdoc level researcher may consider Royal Society Newton Fellowships (NIF) or EU MASC Fellowships (GPF). 

Recent projects

• ULTRACEPT, ultra-layered perception with brain-inspired information processing for vehicle collision avoidance (EU Horizon 2020, project coordinator, 2018-2024, overall budget €2.2m). The primary objective of this project is to develop a trustworthy vehicle collision detection system inspired by animals visual brain via trans-institutional collaboration. Project website (ultracept).
• STEP2DYNA, spatial-temporal information processing for collision detection in dynamic environments (EU Horizon 2020, project coordinator, 2015-2021, overall budget €1.7m), project website (step2dyna).
• ENRICHME, enabling robot and assisted living environment for independent care and health monitoring of the elderly (EU Horizon 2020, CoPI of Lincoln site, 2015-2018). ENRICHME tackles the progressive decline of cognitive capacity in the ageing population proposing an integrated platform for Ambient Assisted Living (AAL) with a mobile service robot for long-term human monitoring and interaction, which helps the elderly to remain independent and active for longer. Project on Facebook (ENRICHME), short clips about the project video1, video2, video3.

Selected recent publication

• Wang Hongxin, Zhong Zhiyan, Lei Fang, Peng Jigen, Yue Shigang. (2023). Bio-inspired small target motion detection with spatio-temporal feedback in natural scenes. IEEE Transactions on Image Processing. published online 27 Dec 2023. DOI: 10.1109/TIP.2023.3345153
• Sun Xuelong, Fu Qinbing, Peng Jigen, Yue Shigang. (2023). An insect-inspired model facilitating autonomous navigation by incorporating goal approaching and collision avoidance. Neural Networks. 165, 106-118. DOI: 10.1016/j.neunet.2023.05.033
• Luan Hao, Hua Mu, Zhang Yicheng, Yue Shigang, Fu Qinbing. (2023). A BLG1 neural model implements the unique looming selectivity to diving target. Optoelectronics Letters, 19(2), 112-116. DOI: 10.1007/s11801-023-2095-0
• Zhang Yifan, Li Xu, Wei Baoguo, Li Lixin, Yue Shigang. (2023). A Fast Hyperspectral Tracking Method via Channel Selection. Remote Sensing, 15(6), 1157, DOI: 10.3390/rs15061557
• Wang Hongxin, Zhao Jiannan, Wang Huatian, Peng Jigen, Yue Shigang. (2022). Attention and prediction guided motion detection for low-contrast small moving targets. IEEE Transactions on Cybernetics (in press). DOI: 10.1109/TCYB.2022.3170699
• Lei Fang, Peng Zhiping, Liu Mei, Peng Jigen, Cutsuridis Vassilis, Yue Shigang. (2022). A robust visual system for looming cue detection against translating motion. IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2022.3149832
• Luan Hao, Fu Qinbing, Zhang Yicheng, Mu Hua, Chen Shengyong, Yue Shigang. (2022). A looming dpatial localization neural network Inspired by MLG1 neurons in the crab neohelice. Frontier in Neuroscience 15:787256. DOI:10.3389/fnins
• Zhao Jiannan, Wang Hongxin, Bellotto Nicola, Hu Cheng, Peng Jigen, Yue Shigang. (2021). Enhancing LGMD's looming selectivity for UAV with spatial-temporal distributed pre-synaptic connections. IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2021.3106946
• Wang H, Wang H, Zhao J, Hu C, Peng J, Yue S (2021). A Time-Delay Feedback Neural Network for Discriminating Small, Fast-Moving Targets in Complex Dynamic Environments. IEEE Transactions on Neural Networks and Learning Systems. DOI: 10.1109/TNNLS.2021.3094205
• Liu Tian, Sun Xuelong, Hu Cheng, Yue Shigang. (2021). A multiple pheromone communication system for swarm intelligence. IEEE Access, 9, 148721-148737. DOI: 10.1109/ACCESS.2021.3124386
• Sun Xuelong, Yue Shigang, Mangan Michael. (2021). How the insect central complex could coordinate multimodal navigation. eLife, 10, e73077
• Isakhani H, Bellotto N, Fu Q, Yue S. (2021). Generative design and fabrication of a locust-inspired gliding wing prototype for micro aerial robots. Journal of Computational Design and Engineering, 8(5), 1191-1203
• Isakhani H, Yue S, Xiong C, Chen W. (2021). Aerodynamic analysis and optimization of gliding locust wing using Nash genetic algorithm. AIAA Journal, 59(10), 4002-4013
• Isakhani H, Xiong C, Cheng W, Yue S. (2021). Towards locust-inspired gliding wing prototypes for micro aerial vehicles applications. Royal Society Open Science, 8(6), 202253
• Fu Qinbing, Sun Xuelong, Liu Tian, Hu Cheng, Yue Shigang. (2021). Robustness of bio-inspired visual systems for collision prediction in critical robot traffic. Frontier in Robotics and AI. 245. DOI: 10.3389/frobt.2021.529872
• Na Seongin, Qiu Yiping, Turgut Ali E, Ulrich Jiri, Krajnik Tomas, Yue Shigang, Lennox Barry, Arvin Farshad. (2021). Bio-inspired artificial pheromone system for swarm robotics applications. Adaptive Behavior, 29(4), 295-415.
• Andreakos N, Cutsuridis V, Yue S. (2021). Modelling the effects of the perforant path in the recall performance of a CA1 microcircuit with excitatory and inhibitory neurons. Journal of Computational Neuroscience, 49(suppl 1), s200-s201
• Wang Huatian, Fu Qinbing, Wang Hongxin, Baxter Paul, Peng Jigen, Yue Shigang. (2021). A bioinspired angular velocity decoding neural network model for visually guided flights. Neural Networks, 136, pp.180-193. DOI: 10.1016/j.neunet.2020.12.008
• Sun Xuelong, Yue Shigang, Mangan Michael. (2020) A decentralised neural model explaining optimal integration of navigational strategies in insects. eLife, 9:e54026. DOI: 10.7554/eLife.54026
• Coşar Serhan, Fernandez-Carmona Manuel, Agrigoroaie Roxana, Pages Jordi, Ferland François, Zhao Feng, Yue Shigang, Bellotto Nicola, Tapus Adriana. (2019). ENRICHME: Perception and Interaction of an Assistive Robot for the Elderly at Home. International Journal of Social Robotics, 12(3), pp.779-805.
• Fu Qinbing, Hu Cheng, Peng Jigen, Rind F Claire, Yue Shigang. (2019). A Robust Collision Perception Visual Neural Network with Specific Selectivity to Darker Objects. IEEE Transactions on Cybernetics, 50(12), pp.5074-5088. DOI: 10.1109/TCYB.2019.2946090
• Fu Qinbing, Wang Hongxin, Hu Cheng, Yue Shigang. (2019). Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review. Artificial Life, 25(3), pp.263-311.
• Liu Daqi, Bellotto Nicola, Yue Shigang. (2019). Deep spiking neural network for video-based disguise face recognition based on dynamic facial movements. IEEE Transactions on Neural Networks and Learning Systems, 31(6), pp.1843-1855. DOI: 10.1109/TNNLS.2019.2927274
• Wang Hongxin, Peng Jigen, Zheng Xuqiang, Yue Shigang. (2019). A Robust Visual System for Small Target Motion Detection against Cluttered Moving Backgrounds. IEEE Transactions on Neural Networks and Learning Systems, 31(3), pp.839-853. DOI: 10.1109/TNNLS.2019.2910418
• Attar Rahman, Xie Xiang, Wang Zhihua, Yue Shigang. (2019). 2D reconstruction of small intestine's interior wall. Computers in biology and medicine, 105, pp.54-63. DOI: 10.1016/j.compbiomed.2018.12.001
• Yu Yongchao, Peng Jigen, Yue Shigang. (2019). A new nonconvex approach to low-rank matrix completion with application to image inpainting. Multidimensional Systems and Signal Processing, 30(1), pp.145-174. DOI: 10.1007/s11045-018-0549-5
• Wang Hongxin, Peng Jigen, Yue Shigang. (2018). A directionally selective small target motion detector in visual cluttered backgrounds. IEEE Trans. Cybernetics, 50(4), pp.1541-1555. DOI: 10.1109/TCYB.2018.2869384
• Fu Qinbing, Hu Cheng and Yue Shigang. (2018). Shaping the collision selectivity in a looming sensitive neuron model with parallel ON and OFF pathways and spike frequency adaptation. Neural Networks, 106, pp.127-143. DOI: 10.1016/j.neunet.2018.04.001
• Liu Daqi and Yue Shigang (2018). Event-Driven Continuous STDP Learning With Deep Structure for Visual Pattern Recognition. IEEE Trans. on Cybernetics, 49(4), pp.1377-1390. DOI: 10.1109/TCYB.2018.2801476
• Chen W, Xiong C, Chen W, Yue S. (2018). Mechanical adaptability analysis of under-actuated mechanisms. Robotics and Computer-Integrated Manufacturing, 49, pp.436-447.
• Zheng X, Zhang C, Lv F, Zhao F, Yuan S, Yue S, Wang Z, Li F, Wang Z . (2017). A 40-Gb/s quarter-rate SerDes transmitter and receiver chipset in 65-nm CMOS, IEEE Journal of Solid-State Circuits, 52 (11), pp.2963-2978.
• Chen Yingtong, Yue Shigang, PengJigen. (2017). Preconditioning for Orthogonal Matching Pursuit with Noisy and Random Measurements: The Gaussian Case. Circuits Syst Signal Process, published online: 22 December 2017. DOI: 10.1007/s00034-017-0730-3
• Gao Yi, Peng Jigen, Yue Shigang. (2017). Stability and robustness of the l 2/lq-minimization for block sparse recovery. Signal Processing, 137, pp.287-224.
• Wang Dongdon, Hou Xinwen, Xu Jiawei, Yue Shigang, Liu Cheng-Lin. (2017). Traffic sign detection using a cascade method with fast feature extraction and saliency test. IEEE Transactions on Intelligent Transportation Systems, 18(2), pp.3290-3302. DOI: 10.1109/TITS.2017.2682181
• Liu Daqi. and Yue Shigang. (2017). Unsupervised Learning for Visual Pattern Recognition using Spiking Time Dependent Plasticity. Neurocomputing, 249, pp.212-224. DOI: 10.1016/j.neucom.2017.04.003
• Xu, Jiawei, Yue, Shigang, Fedrica Mechillini. and Guo Kun. (2017). What has been missed in modeling human attention systems in driving? PeerJ, Published 1 February 2017, DOI: 10.7717/peerj.2946
• Hu Bin, Yue Shigang and Zhang ZhuHong. (2017). A rotational motion perception neural network base on asymmetric spatiotemporal visual information processing. IEEE Transactions on Neural Networks and Learning Systems, 28(11), pp.2803-2821. DOI: 10.1109/TNNLS.2016.2592969
• Zheng Xuqiang, Yuan Shuai, Zhao Feng, Zhang Chun, Wang Ziqiang, Yue Shigang, Li Fule, Wang Zhihua. (2016). A 14-bit 250 MS/s IF sampling pipelined ADC in 180 nm CMOS process. IEEE Transactions on Circuits and Systems I, 63(9), pp.1381-1392. DOI: 10.1109/ESSCIRC.2016.7598303
• Zheng Xuqing, Li Fule, Wang Zhijun, Li Weidao, Jia Wen, Wang Zhihua, Yue Shigang. (2016). An S/H circuit with parasitic optimized for IF-sampling. Journal of Semiconductors, 6, 162-166
• Xiong Caihua, Chen Wenrui, Sun Baiyang, Liu Mingjin, Yue Shigang and Chen Wenbin. (2016). Design and implementation of anthropomorphic hand for replicating human grasping functions. IEEE Transactions on Robotics, 32(3), pp.652-671. DOI: 10.1109/TRO.2016.2558193
• Hu Cheng, Arvin Farshad, Xiong Caihua and Yue Shigang. (2016). Bio-inspired embedded vision system for autonomous micro-robots. IEEE Transactions on Cognitive and Developmental Systems, 9(3), pp.241-254. DOI: 10.1109/TCDS.2016.2574624
• Arvin Farshad, Turgut Ali Emre, Krajnik Tomas, and Yue Shigang (2016). Investigation of cue-based aggregation in static and dynamic environments with a mobile robot swarm. Adaptive Behavior, 24 (2), pp.102-118. DOI: 10.1177/1059712316632851

Full publication list please see google scholar. 

Current first supervision

• Yicheng Zhang, PhD student, thermal image processing for driving safety (to transfer)
• Mu Hua, PhD student, motion sensitive visual neural systems modelling and verification
• Mingshuo Xu, PhD student, (topic to be confirmed)
• Zhiqiang Yan, visiting PhD student (to join)

Potential PhD students and academic visitors are welcome to contact me directly. There are 25 CSC fully funded PhD studentships in Leicester, deadline is 7th Jan, details see (CSC studentship).

• CO1101 Computing Fundamentals
• CO1106 Requirements Engineering and Professional Practice

• Member of AIDAM Leicester
• Senior member of IEEE, member of ISBE, INNS
• Editorial Board of IEEE TNNLS, IEEE TCDS, IJARS, AIMS EEE, JCSSB
• Peer Review College of EPSRC

•  Alexander von Humboldt Research Fellow, 2000-2001

PhD and MSc (BJUT), BEng (QDUT)