IEEE Transactions on Cognitive and Developmental Systems
Special Issue on Neuromorphic Computing and Cognitive SystemsHuajin Tang, Tiejun Huang, Garrick Orchard, Arindam Basu, and Jeffrey Krichmar
AIM AND SCOPE
In recent years neuromorphic computing has become an important emerging research area. There has been rapid progress in computational theory, learning algorithms, signal processing and circuit design and implementation, which have shown appealing computational advantages over conventional solutions. The low size, weight, and power of these hardware architectures shows great potential for embedded cognitive systems. Starting from emulating the computational principles and architecture found in neural systems, neuromorphic computing aims to integrate sensory coding, synaptic computing (e.g., STDP), learning and memory, and attempts to develop neuromorphic sensors and chips, and cognitive behaving systems such as robots. Neuromorphic hardware has provided a fundamentally different technique for data representation and learning, e.g., asynchronous events rather than regularly sampled frames of images. Various hardware systems leveraging on neural spikes based computing have been reported to achieve good performance with much lower power consumption. Therefore, neuromorphic computing can inform cognitive systems because the algorithms that run on this hardware must be neurobiologically inspired. A huge potential exists for applying this emerging computing framework to the next generation of cognitive systems and robotics, neuro-inspired sensors and processors, etc.
This special issue aims to report state-of-the-art approaches and recent advances on (a) learning algorithms constrained by limits of biology and neuromorphic hardware (b) neuromorphic hardware for cognitive systems and (c) applications of neuromorphic architecture or hardware to cognitive robotics. Topics relevant to this special issue include, but are not limited to
- Neuromorphic cognitive systems
- Cognitive robotics
- Brain-inspired data representation models
- STDP, Spike-based sensing and learning algorithms
- Spike based processing and methods for configuring spike-based processors
Manuscripts should be prepared according to the “Information for Authors” of the journal found at http://cis.ieee.org/publications.html and submissions should be done through the IEEE TCDS Manuscript center: https://mc.manuscriptcentral.com/tcds-ieee and please select the category “SI: Neuromorphic Computing”. More:CFP_TCDS_SI_Neuromorphic.pdf
15 June 2016 – Deadline for manuscript submission
15 Sep 2016 – Notification of authors
15 Oct 2016– Deadline for revised manuscripts
15 Nov 2016 – Final version
For further information, please contact one of the following Guest Editors.
Huajin Tang received the B.Eng. degree from Zhejiang University, Hangzhou, China, M.Eng. degree from Shanghai Jiao Tong University, Shanghai, China, and the Ph.D. degree in electrical and computer engineering from the National University of Singapore, Singapore, in 1998, 2001, and 2005, respectively. He was a System Engineer with STMicroelectronics, Singapore, from 2004 to 2006. From 2006 to 2008, he was a postdoctoral fellow with Queensland Brain Institute, University of Queensland, Queensland, Australia. Since 2008, he was with Institute for Infocomm Research, Singapore and was the Head of the Cognitive Computing Lab. Since 2014 he has been a Professor with Sichuan University, China. He has authored or co-authored over 40 international journal papers, and one monograph (Springer-Verlag, 2007). He is Program Chair of 2015 IEEE International Conference on Cybernetics and Intelligent Systems (CIS), Co-Chair of WCCI 2016 International Workshop on Neuromorphic Computing and Cyborg Intelligence, and Co-Chair of 2016 IEEE Symposium on Neuromorphic Systems and Cyborg Intelligence (IEEE SNCI'16). He is Associate Editor of the IEEE Trans. on Neural Networks and Learning Systems, and Associate Editor of the IEEE Trans. on Cognitive and Developmental Systems. Prof. Tang has won 2016 IEEE CIS Outstanding TNNLS Paper Award. His current research interests include neuromorphic computing, neuromorphic cognitive systems, and neuro-cognitive robots.
Tiejun Huangreceived the Ph.D. degree in pattern recognition and intelligent system from the Huazhong (Central China) University of Science and Technology in 1998, and the Master’s and Bachelor’s degrees in computer science from the Wuhan University of Technology in 1995 and 1992, respectively. He is a Professor with the School of Electronic Engineering and Computer Science, the Chair of Department of Computer Science and the Director of the Institute for Digital Media Technology, Peking University. Professor Huang’s research areas include video coding and image understanding, especially neural coding inspired information coding theory in last years. Professor Huang received the National Science Fund for Distinguished Young Scholars of China in 2014. He is a member of the Board of the Chinese Institute of Electronics, the Board of Directors for Digital Media Project and the Advisory Board of IEEE Computing Now.
Garrick OrchardGarrick Orchard is a Senior Research Scientist at Temasek Laboratories and the Singapore Institute for Neurotechnology (SINAPSE) at the National University of Singapore. He holds a B.Sc. degree (with honours, 2006) in electrical engineering from the University of Cape Town, South Africa and M.S.E. (2009) and Ph.D. (2012) degrees in electrical and computer engineering from Johns Hopkins University, Baltimore, USA. He was named a Paul V. Renoff fellow in 2007, a Virginia and Edward M. Wysocki Sr. fellow in 2011, and a Temasek Research Fellow in 2015. He received the Johns Hopkins University Applied Physics Lab’s Hart Prize for Best Research and Development Project, and won the best live demonstration prize at the IEEE Biomedical Circuits and Systems conference 2012. His research focuses on developing neuromorphic vision algorithms and systems for real-time sensing on mobile platforms. His other research interests include mixed-signal very large scale integration (VLSI) design, compressive sensing, spiking neural networks, visual perception, and legged locomotion.
Arindam Basureceived the B.Tech and M.Tech degrees in Electronics and Electrical Communication Engineering from the Indian Institute of Technology, Kharagpur in 2005, the M.S. degree in Mathematics and PhD. degree in Electrical Engineering from the Georgia Institute of Technology, Atlanta in 2009 and 2010 respectively. Dr. Basu received the Prime Minister of India Gold Medal in 2005 from I.I.T Kharagpur. He joined Nanyang Technological University as an Assistant professor in June 2010. He is currently an Associate Editor of IEEE Sensors journal (2015-17) and IEEE Transactions on Biomedical Circuits and Systems (2016-18). He is also Guest Editor of two Special Issues in IEEE Trans. on Biomedical Circuits and Systems for selected papers from ISCAS 2015 and BioCAS 2015 conferences. Dr. Basu received the Industry Choice Award at BioCAS 2015, best student paper award at Ultrasonics symposium, 2006, best live demonstration at ISCAS 2010 and a finalist position in the best student paper contest at ISCAS 2008. He was awarded MIT Technology Review's 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. His research interests include bio-inspired neuromorphic circuits, non-linear dynamics in neural systems, low power analog IC design and programmable circuits and devices.
Jeffrey L. Krichmarreceived a B.S. in Computer Science in 1983 from the University of Massachusetts at Amherst, a M.S. in Computer Science from The George Washington University in 1991, and a Ph.D. in Computational Sciences and Informatics from George Mason University in 1997. He spent 15 years as a software engineer on projects ranging from the PATRIOT Missile System at the Raytheon Corporation to Air Traffic Control for the Federal Systems Division of IBM. In 1997, he became an assistant professor at The Krasnow Institute for Advanced Study at George Mason University. From 1999 to 2007, he was a Senior Fellow in Theoretical Neurobiology at The Neurosciences Institute. Currently, he is a Professor at the University of California, Irvine, in the Department of Cognitive Sciences, with a joint appointment in the Department of Computer Science. He leads the Cognitive Anteater Robotics Laboratory (CARL) at UC Irvine where they test computational models of nervous system function on robotic platforms and large-scale, highly detailed models of neuronal circuits. He has been involved in these fields, which are known as neuromorphic engineering and neurorobotics, for over 15 years. He has published nearly 100 articles and holds seven patents.