2016 IEEE World Congress on Computational Intelligence

July 25-29, 2016 - Vancouver, Canada

International Workshop on

Neuromorphic Computing and Cyborg Intelligence

News

High quality workshop papers will be invited to submit their full studies to an upcoming special issue on IEEE Transactions on Cognitive and Developmental Systems!

CFP_NeuromorphicComputing_Workshop_WCCI2016.pdf

Overview

Emulating brain-like learning performance has been a key challenge for research in neural networks and learning systems, including recognition, memory and perception. In the last few decades, a wealth of machine learning approaches have been proposed including sparse representations, hierarchical and deep learning neural networks. While achieving impressive performance these methods still compare poorly to biological systems and the problem of reducing the amount of human supervision and computations needed for learning remains a challenge.

On the other hand, the development of novel data representation and learning approaches from recent advances in neuromorphic systems have shown appealing computational advantages. For example, using neural coding theory to represent the external sensory data, and developing spiking timing based learning algorithm have achieved real-time learning performance, either in neuromorphic computational models or hardware systems. Attributed to the new visual or auditory sensors, neuromorphic hardware has provided a fundamentally different technique for data representation, i.e., asynchronous events rather than frames of images as in main stream recognition algorithms. However, the current neuromorphic information processing algorithms are not comparable to achieve sophisticated features and power learning performance as what machine learning approaches can offer. One promising method is to develop integrated learning models that apply brain-like data presentation and learning mechanisms, e.g., implementing deep learning in neuromorphic systems. Neuromorphic systems also overlap with another framework called cyborg intelligence, combining brain functions with computational machines to achieve the best of both via brain-machine interface. The workshop will target the challenging problems in these areas by reporting new solutions, theoretical and technical advances in neuromorphic computing and cyborg intelligence from the worldwide researchers and engineers.

Technical Program Committee

Tetsuya Asai, Hokkaido University, Japan
Ryad Benosman, University of Pierre and Marie Curie, France
Badong Chen, Xi’an Jiao Tong University, China
Feng Chen, Tsinghua University, China
Jörg Conradt, Technische Universität München, Germany
Shoushun Chen, Nanyang Technolological University, Singapore
Yiran Chen, University of Pittsburgh, USA
Tomoki Fukai, RIKEN Brain Science Institute, Japan
Jun Hu, Institute for Infocomm Research, Singapore
Giacomo Indiveri, Institute of Neuroinformatics, Switzerland
Sio-Hoi Ieng, University of Pierre and Marie Curie, France
Shih-Chii Liu, Institute of Neuroinformatics, Switzerland
Garrick Orchard, National University of Singapore, Singapore
Tarek M. Taha, University of Dayton, USA
Jun Tani, KAIST, Korea
Yiwen Wang, Zhejiang University, China
Si Wu, Beijing Normal University, China
Qiang Yu, Max-Planck-Institute for Experimental Medicine, Germany
Bo Zhao, Institute for Infocomm Research, Singapore

Relevant Topics

Cognitive computing and cyborg intelligence
Neuromorphic information/signal processing
Brain-inspired data representation models
Neuromorphic learning and cognitive systems
Spike-based sensing and learning
Neuromorphic sensors and hardware systems
Intelligence for embedded systems
Cognition mechanisms for big data
Embodied cognition and neuro-robotics

Important Dates

Submission deadline: 15 January 2016
Notification of acceptance: 15 March 2016
Camera-ready deadline: 15 April 2016
Workshop date: 25 July 2016

Submission Guidelines

Prospective authors are invited to submit papers according to the IEEE format. All submissions should follow the specifications of WCCI 2016. Manuscripts will be submitted through the IEEE WCCI 2016 paper submission website and will be subject to the same peer-review procedure as the WCCI2016 regular papers. Accepted contributions will be part of the IJCNN conference proceedings, which will be available in IEEE Xplore.

Organizers

  • Huajin Tang, Sichuan University, Chengdu, China (htang@scu.edu.cn )
  • Gang Pan, Zhejiang University, China (gpan@zju.edu.cn)
  • Arindam Basu, Nanyang Technological University, Singapore (arindam.basu@ntu.edu.sg)
  • Luping Shi, Tsinghua University, China (lpshi@mail.tsinghua.edu.cn)
Huajin Tang

Huajin Tang received the B.Eng. degree from Zhejiang University, Hangzhou, China in 1998, the M.Eng. degree from Shanghai Jiao Tong University, Shanghai, China in 2001, and the Ph.D. degree in electrical and computer engineering from the National University of Singapore, Singapore, in 2005. He was a System Engineer with STMicroelectronics, Singapore, from 2004 to 2006, and then a Post-Doctoral Fellow with the Queensland Brain Institute, University of Queensland, Brisbane, QLD,1045 Australia, from 2006 to 2008. He has been a Research Scientist and Head of the Cognitive Computing Group with the Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore since 2008. He is currently a Professor with College of Computer Science, Sichuan University, China. He has authored one monograph (Springer-Verlag, 2007) and over 30 international journal papers. His current research interests include neural computation, neuromorphic cognitive systems, neurocognitive robots, and machine learning. Prof. Tang serves as an Associate Editor of the IEEE Transactions on Neural Networks and Learning Systems, and an Editorial Board Member of Frontiers in Robotics and AI. He is Program Chair of IEEE CIS-RAM 2015, and Chair of IEEE CIS Summer School subcommittee.


Gang Pan

Gang Pan is a professor of the College of Computer Science and Technology at Zhejiang University. He received the B.S. and Ph.D. degrees both in Computer Science from Zhejiang University in 1998 and 2004. From 2007 to 2008, he was with the University of California, Los Angeles as a visiting researcher. His interests include pervasive computing, computer vision, and artificial intelligence. He has co-authored more than 100 refereed papers, and has 16 patents granted. He is a recipient of Microsoft Fellowship Award, New Century Excellent Talents in University, and Distinguished Young Scholars of Natural Science Fund of Zhejiang. Dr. Pan is the secretary of the Technical Committee on Pervasive Computing of China Computer Federation (CCF) and vice-chair of ACM Hangzhou Chapter. He has served as program committee members for more than twenty prestigious international conferences, such as ICCV, CVPR, IJCAI, and UIC. He is an associate editor of IEEE Systems Journal. He won two IEEE Best Paper Awards, and Honorable Mention Award of ACM UbiComp 2015. His homepage: http://www.cs.zju.edu.cn/~gpan


Arindam Basu

Arindam Basu received the B.Tech and M.Tech degrees in Electronics and Electrical Communication Engineering from the Indian Institute of Technology, Kharagpur, in 2005, and the M.Sc. degree in Mathematics and the Ph.D. degree in Electrical and Computer Engineering from the Georgia Institute of Technology, Atlanta, GA, USA, in 2009 and 2010, respectively. In June 2010, he joined Nanyang Technological University, Singapore, as an Assistant Professor. His research interests include bio-inspired neuromorphic circuits, non-linear dynamics in neural systems, low power analog IC design, and programmable circuits and devices. Dr. Basu received the JBNSTS Award in 2000 and the Prime Minister of India Gold Medal in 2005 from the Indian Institute of Technology, Kharagpur. He received the best student paper award, Ultrasonics Symposium, 2006; best live demonstration, ISCAS 2010; and a finalist position in the best student paper contest at ISCAS 2008. He was awarded MIT Technology Reviews inaugural TR35@ Singapore award in 2012 for being among the top 12 innovators under the age of 35 in SE Asia, Australia, and New Zealand.


Prof. Luping Shi

Prof. Luping Shi, National 1000 talent distinguish professor, director of center for brain inspired computing research, director of optical memory national engineering research center , Tsinghua university, China, SPIE fellow. He received a Doctor of Science from University of Cologne, Germany in 1992. From 1996 to Mar.2013 he worked in data storage institute, Singapore as a senior scientist and division manager and led nonvolatile solid-state memory (NVM), artificial cognitive memory (ACM) and optical storage researches. His main research areas include Brain inspired computing, NVM, ACM, optical data storage, and integrated opto-electronics. He has published more than 150 papers in prestigious journals including Science, Nature Photonics, filed and granted more than 10 patents and conducted more than 60 keynote speech or invited talks during last 10 years. He is the recipient of the National Technology Award 2004 Singapore.