[Comp-neuro] Call for papers, IJCNN Special session on Brain inspired models of cognitive memory

Kiruthika Ramanathan (DSI) Kiruthika_R at dsi.a-star.edu.sg
Thu Nov 24 02:30:17 CET 2011

Call for papers
Special Session on Brain inspired models of cognitive memory
International Joint Conference on Neural Networks <http://www.ieee-wcci2012.org/>
(IJCNN 2012)<http://www.ieee-wcci2012.org/>
Brisbane, Australia
Current memory technologies have experienced significant progress in terms of storage capacity, operation speed, integration capability, etc. However, their functions are highly constrained in storing and transferring data in space and time, prompting the need for improvement. Is there any available memory system that has multiple functions besides only data storage? Nature gives the firm answer: yes, it is human memory.
In contrast to physical memories, the biological counterpart has versatile functions. For instance, it stores data associatively such that different modalities of data could be retrieved simultaneously; it can learn different concepts, categorize and store them in an organized manner; it can process and store data concurrently and in a distributed fashion; it can restore content even if some part is damaged; it can perceive the stimulus and predict the next event; it can adapt to the environment and perform selective storage. Functions such as adaptation, learning, perception, self-organization and prediction make human memory have distinct cognitive features. Can we change the way data is currently being stored in computational systems by building a physical memory device that has cognitive functions like human memory<http://www.dsi.a-star.edu.sg/key-rd-areas/non-volatile-memory/projects/pages/artificialcognitivememory.aspx>?
The scope of the question transcends several interdisciplinary boundaries and combines efforts in both hardware and software engineering. It has prompted us to organize the special session on brain inspired memory models, and aims to offer a meeting opportunity for researchers belonging to the various communities of computational intelligence, machine learning, cognitive modelling, as well as researchers in hardware (circuit level) implementation of cognitive systems and those working at materials level research, such as memristors and phase change materials. Research papers that focus on how these technologies can be used to develop a memory based intelligent system will contribute to this special session.
Topics of interest to the workshop include (but are not limited to):

 *   System level models of cognitive memory (associative memory, episodic memory, LTM, STM, working memory, semantic memory, etc)
 *   Neural circuits modelling and theory (Winner take all, attractors etc)
 *   Synaptic models
 *   Neural information encoding and decoding
 *   Learning mechanisms (STDP, Hebbian learning, non-associative learning etc)
 *   Artificial neural network model of memory in hardware and devices
Please follow the regular submission guidelines of IJCNN 2012<http://www.ieee-wcci2012.org/ieee-wcci2012/index.php?option=com_content&view=article&id=58&Itemid=67>. Select the correct special session AND notify the chairs of your submission by sending email to: Kiruthika_r at dsi.a-star.edu.sg<mailto:Kiruthika_r at dsi.a-star.edu.sg>
Kiruthika Ramanathan
Email: Kiruthika_r at dsi.a-star.edu.sg<mailto:Kiruthika_r at dsi.a-star.edu.sg>
Data Storage Institute, Agency for Science, Technology and Research, Singapore
Bio: Dr Kiruthika Ramanathan obtained her Bachelor's and PhD in Electrical and Computer Engineering from the National University of Singapore in 2003 and 2007 respectively. She is currently a Scientist at the Data Storage Institute, Agency for Science, Technology and Research, Singapore, where she is the with a research program on Artificial Cognitive Memory. She is also affiliated with the Computational Cognition for Social Systems (CCSS) group at the Institute of High Performance Computing (IHPC), Singapore. Her research interests include bio-inspired models of memory, machine learning, multi modal representation and cognitive systems. She has published several journal and conference papers in the fields of machine learning and cognitive systems. She is a member of IEEE.
Tang Huajin
Email: htang at i2r.a-star.edu.sg<mailto:engp1880 at nus.edu.sg>
Institute of InfoComm Research, Agency for Science, Technology and Research, Singapore

Bio: Dr. Huajin Tang received his B.Eng. degree from Zhe Jiang University in 1998, M.Eng. degree from Shanghai Jiao Tong University, China in 2001, and Ph.D. degree in electrical and computer engineering from National University of Singapore in 2005. From 2004 to 2006, he was an R&D engineer at STMicroelectronics, Singapore. From 2006 to 2008, he was a postdoctoral fellow at Queensland Brain Institute, University of Queensland. In 2008 he joined the Institute for Infocomm Research firstly as a research fellow and now a research scientist. He is the leader of the cognitive computing research group. His research interests include neural computation, machine learning, computational and biological intelligence, and neuro-cognitive robotics. He has published over twenty scientific papers in prestigious international journals and conferences and one monograph "Neural Networks: Computational Models and Applications". He is a member of IEEE, IEEE Computational Intelligence Society and Industrial Electronics Society.
Ning Ning
Email: Ning_ning at dsi.a-star.edu.sg<mailto:Ning_ning at dsi.a-star.edu.sg>
Data Storage Institute, Agency for Science, Technology and Research, Singapore
Bio: Dr Ning Ning received his Bachelor degree in Electronics and Information Engineering from Huazhong university of Science and Technology, China in 2003 and his Ph.D from National University of Singapore in 2010. From 2008 to 2010, he was a Research Fellow in Neuroengineering Lab, National University of Singapore. He is currently a Scientist at the Data Storage Institute, Agency for Science, Technology and Research, Singapore, working in the program of Artificial Cognitive Memory. His research interests include cognitive architectures, neuronal modelling, and neuromorphic systems and devices. He has over 30 publications in journals and conferences in multidisciplinary fields.
Program Committee members:

1.       Asim Roy<http://wpcarey.asu.edu/directory/stafffaculty.cfm?cobid=1039524>, Professor, Arizona State University, United States

2.       John Weng<http://www.cse.msu.edu/%7Eweng/>, Michigan State University, United States

3.       Alexander Rast<http://apt.cs.man.ac.uk/projects/SpiNNaker/>, Advanced Processor Technologies Group, University of Manchester, UK

4.       Shi Luping<http://www.dsi.a-star.edu.sg/key-rd-areas/non-volatile-memory/projects/pages/artificialcognitivememory.aspx>, Program leader, Artificial Cognitive Memory, Agency for Science, Technology and Research, Singapore

5.       Li Haizhou<http://www1.i2r.a-star.edu.sg/%7Ehli/>, Principal Scientist, Human Language Technology, Institute of Infocomm Research, Singapore,

6.       Prahlad Vadakkepat<http://www.prahlad.in/>, Associate Professor, Department of Electrical and Computer Engineering, National University of Singapore, Singapore

7.       Kenneth Kwok<http://www.temasek-lab.nus.edu.sg/program/program_cognitivesciencestaff.php?userid=tslkfkk>, Principal Scientist, Temasek Laboraties, Singapore

8.       Jin Yaochu<http://www.soft-computing.de/jin.html>, Professor and Chair in Computational Intelligence, Department of Computing, University of Surrey, UK.

9.       Jun Tani<http://www.bdc.brain.riken.go.jp/%7Etani/>, Head of Behavior and Dynamic Cognition Lab, RIKEN Brain Science Institute, Japan.

10.   Guan, Steven Sheng Uei<http://www.xjtlu.edu.cn/en/faculty/academic-subject-staff/item/90-guan-steven-sheng-uei.html>, Professor and Head of Department, Xian Jiaotong Liverpool University, China

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