MIN Faculty
Department of Informatics
Knowledge Technology

Junpei Zhong

Since Jan 2014, I have moved to the University of Hertfordshire as a postdoctoral research fellow.

Contact Info

New Address: E308, Embodied Emotion, Cognition and (Inter-)Action Lab School of Computer Science, University of Hertfordshire, College Lane, Hatfield, Herts AL10 9AB, United Kingdom
Email: zhong AT junpei.eu
URL: http://www.junpei.eu


Research Interests

My current research encompasses the following interrelated research themes:
    Computational Neuroscience, particularly focusing on the visual system modelling, and its relation into the affordance learning in a mirror neuron system.
    Bootstrap Learning for Visual Perception on Robots
    Developmental Psychology and its contributions to Developmental Robotics
My previous research also includes SLAM, and its biological-inspired solutions.




Short Curriculum Vitae

9.2002-7.2006 Bachelor of Engineering, Department of Control Science, South China University of Technology, Guangzhou China
9.2006-7.2007 Department of Control & Mechatronics, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen China
10.2007-10.2009 Master of Philosophy, Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong
7.2010-12.2013 PhD and Research Associate of Knowledge Technology Research Group, Department of Computer Science, University of Hamburg, Germany



Utilization and Optimization for Particle Filtering Multi-robot SLAM
Supervisor: Dr. Y.F. Fung, MPhil Thesis, Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong  



  • Zhong, J.P. and Fung, Y.F., A Biological Inspired Improvement Strategy for Particle Filters. Proceedings, IEEE 2009 International Conference on Industrial Technology (ICIT 09), Australia, pp. 1-6, 10-13 Feb 2009.
  • Zhong, J.P., Fung Y.F. and Dai M.J. Ant Colony Optimization Assisted Particle Filters. International Journal of Control, Automation, and Systems. pp. 519-526, June, 8(3), 2010.
  • Zhong, J.P., Weber, C. and Wermter S., Robot Trajectory Prediction and Recognition based on a Computational Mirror Neurons Model. In Honkela, T., Duch, W., Girolami, M., Kaski, S., editors, Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN 2011), Part II, pp. 333-340, Espoo, Finland, June 2011.
  • Zhong, J., Weber, C. Wermter, S. Restricted Boltzmann Machine with Transformation Units in a Mirror Neuron System Architecture. In Narioka, K., Nagai, Y., Asada, M., Ishiguro, H., editors, Proceedings of the IROS2011 Workshop on Cognitive Neuroscience Robotics (CNR), pp. 23-28, San Francisco, CA, USA, September 2011.
  • Zhong, J., Fung, Y.F. Case Study and Proofs of Ant Colony Optimisation Improved Particle Filter Algorithm. IET Control Theory and Applications. pp. 689-697, 6(5), 2012.
  • Zhong, J., Weber, C. Wermter, S. Learning Features and Transformations with a Predictive Horizontal Product Model. Proceedings of Sixteenth International Conference on Cognitive and Neural Systems, ICCNS 2012, Boston, USA, 2012.
  • Zhong, J., Weber, C., Wermter, S. Learning Features and Predictive Transformation Encoding Based on a Horizontal Product Model. In Villa, A.E.P., et al., editors, Proceedings of the 22nd International Conference on Artificial Neural Networks (ICANN 2012), Part I, LNCS 7552, pp. 539-546, Springer Heidelberg. Lausanne, CH, September 2012.
  • Zhong, J., Weber, C., Wermter, S. A Predictive Network Architecture for a Robust and Smooth Robot Docking Behavior. Paladyn. Journal of Behavioral Robotics. pp. 172-180, 3(4), 2012
  • Zhong, J., Cangelosi, A., Wermter, S. Towards a Self-organizing Pre-symbolic Neural Model Representing Sensorimotor Primitives. Frontiers in Behavioral Neuroscience, 8, pp. 1-11, 10.3389/fnbeh.2014.00022, 2014