BICS 2016 Program

On Site Registration: For delegates outside China, please bring your registration form and pay by cash on site at the registration desk. Only Chinese Yuan and USD are acceptable.

Conference Venue: All the invited talks and oral sessions will be held at the 1st meeting room, 3rd floor, Intelligence Building, at Institute of Automation, Chinese Academy of Sciences.

Address: No. 95, Zhong Guan Cun East Road, Beijing, 100190  Map: Click Here


November 27, 2016(Sunday)

14:00 – 18:00


November 28, 2016(Monday)


Conference Schedule



09:00 – 09:20

Opening Ceremony

09:20 – 10:20

Keynote Talk I

Speaker:    Yingxu Wang (University of Calgary, Canada)

Title   :  Brain-Inspired Deep Learning and Cognitive Learning Systems

10:20 – 10:40  Coffee Break

10:40 – 12:00

Oral Session 1 – Learning

Shen Yuanyuan and Cheng-Lin Liu

Incremental Learning Vector Quantization for Character Recognition with Local Style Consistency

Wangli Hao and Zhaoxiang Zhang

Incremental PCANet: a lifelong learning framework to achieve the plasticity of both feature and classifier constructions

Saad Razzaq, Fahad Maqbool and Amir Hussain

Modified Cat Swam Optimization for Clustering

Summrina Kanwal, Dr.Amir Hussain, Prof. Bin Luo and Kaizhu Huang

An Investigation of Machine Learning and Neural Computation Paradigms in the Design of Clinical Decision Support Systems (CDSSs)

12:00 – 14:00   Lunch

14:00 – 15:00

Oral Session 2 – Cognitive Neuroscience

Yi Zeng, Yuxuan Zhao and Jun Bai

Towards Robot Self-Consciousness (I): Brain-inspired Robot Mirror Neuron System Model and Its Application in Mirror Self-Recognition


Guixiang Wang, Yi Zeng and Bo Xu

A Spiking Neural Network Based Autonomous Reinforcement Learning Model and Its Application in Decision Making

Fei Gao, Xiangshang Xue, Jun Wang, Jinping Sun, Amir Hussain and Erfu Yang

Visual Attention Model with a Novel Learning Strategy and Its Application to Target Detection from SAR Images

15:00 – 15:20  Coffee Break

15:20 – 16:20

Oral Session 3 – Neural Network I

Ke Chen and Zhaoxiang Zhang

An Improved Recurrent Network for Online Equality-Constrained Quadratic Programming

Cong Hu and Xiao-Jun Wu

Implicit Regularized Autoencoders (Autoencoders with Drop Strategy)

Dan Zeng, Fan Zhao and Yixin Bao

Compressing Deep Neural Network for Facial Landmarks Detection


Oral Session 4 – Neural Network II

Xuan Li, Zilan Hu and Haixian Wang

Sparse-Network Based Framework for Detecting the Overlapping Community Structure of Brain Functional Network

Dong Wang, Qiang Zhou and Amir Hussain

Deep and Sparse Learning in Speech and Language Processing: An Overview

T.Sheeba Justin and Dr.Reshmy Krishnan

An Ontological Framework of Semantic Learner Profile in an E-Learning System

November 29, 2016(Tuesday)


Conference Schedule

09:00 – 10:00

Keynote Talk II

Speaker: Yulin Qin (Shanghai Jiaotong University, China)

Title   : Herbert Simon Memorial Talk : Herbert Simon’s legacy, cognitive architecture and brain-inspired computational modeling

10:00 – 10:20  Coffee Break

10:20 – 12:00

Oral Session 5 – Analysis of Electrophysiological Data (I)

Muhammad Yousefnezhad and Daoqiang Zhang

Decoding visual stimuli in human brain by using Anatomical Pattern Analysis on fMRI images

Jinpeng Li, Zhaoxiang Zhang and Huiguang He

Implementation of EEG emotion recognition system based on hierarchical convolutional neural networks

Hongjian Bo, Haifeng Li, Lin Ma and Bo Yu

Time-Course EEG Spectrum Evidence for Music Key Perception and Emotional Effects

Min Wang, Hussein Abbass, Jiankun Hu and Kathryn Merrick

Detecting Rare Visual and Auditory Events from EEG Using Pairwise-Comparison Neural Networks

Pei-Zhen Li, Juan-Hui Li and Changdong Wang

A SVM-based EEG Signal Analysis: An Auxiliary Therapy for Tinnitus

12:00 – 14:00   Lunch

14:00 – 14:40

Oral Session 6 – Analysis of Electrophysiological Data (II)

Chunying Fang, Haifeng Li and Lin Ma

EEG brain functional connectivity dynamic programing model: a study via wavelet coherence

Zhen Zhang, Xuejun Jiao, Jin Jiang, Jinjin Pan, Yong Cao, Hanjun Yang and Fenggang Xu

Passive BCI based on Sustained Attention detection: an fNIRS study

14:40 – 15:40

Oral Session 7 – Computational Neuroscience

Ashraya Samba Shiva and Amir Hussain

A continuous time recurrent neural network model of recurrent collaterals in the CA3 regions of the hippocampus

Hui Wei, Yijie Bu and Dawei Dai

A Possible Neural Circuit for Decision Making and its Learning Process

Hani Alharbi, Khaled Aloufi and Amir Hussain

A new biologically-inspired analytical worm propagation model for mobile unstructured Peer to Peer Networks

15:40 – 16:00  Coffee Break

16:00 – 17:20

Oral Session 8– Application (I)

Xian-Shi Zhang and Yongjie Li

A Retina Inspired Model for High Dynamic Range Image Rendering

Qixin Wang, Tianyi Luo and Dong Wang

Can Machine Generate Traditional Chinese Poetry? A Feigenbaum Test

Hongmin Li, Guoqi Li and Luping Shi

Classification of Spatiotemporal Events Based on Random Forest

Youxia Cao, Bo Jiang, Zhuqiang Chen, Jin Tang and Bin Luo

Low-rank Image Set Representation and Classification

18:00 – 20:00    Banquet

November 30, 2016(Wednesday)


Conference Schedule

09:00 – 10:00

Keynote Talk III

Speaker:    Huajin Tang (Sichuan University, China)

Title   :  Neuromorphic Cognitive Computing: A Convergent Approach to Brainy Computers

10:00 – 10:20  Coffee Break

10:20 – 12:00

Oral Session 9 – Application (II)

Huiling Wang, Bin Luo and Lixiang Xu

Learning optimal seeds for salient object detection

Andrew Abel, Ricard Marxer, Amir Hussain, Jon Barker, Roger Watt, William Whitmer and Peter Derleth

A Data Driven Approach to Audiovisual Speech Mapping

Kia Dashtipour, Amir Hussain, Qiang Zhou, Alexander Gelbukh, Ahmad Y.A. Hawalah and Erik Cambria

PerSent: A Freely Available Persian Sentiment Lexicon

Liaqat Ali, Zain U. Hussain, Moiz Ali Shah, Amir Shah, Unnam Sudhakar, Jingpeng Li and Amir Hussain

A Novel Fully automated Liver and HCC Tumor segmentation system using Morphological Operations

Adam Hall, Amir Hussain and M Guftar Shaikh

Predicting Insulin Resistance In Children Using a Machine-Learning-Based Clinical Decision Support System