GlobalSIP 2013 Paper Review Categories

* indicates that this line can be assigned as a paper's topic.

1:Advancing Neural Engineering Through Big Data
 1.1*:Brain Computer Interfaces
 1.2*:Wearable and Assistive devices
 1.3*:Neurological Sensor Arrays and Transduction
 1.4*:Biocompatible Interface Materials
 1.5*:Bioelectrical Signal Processing
 1.6*:Neuromotor and Neurosensory Modeling
 1.7*:Bioengineering Application of Big Data
 1.8*:Best Practices in Experimental Design
 1.9*:Annotation and Distribution Standards
 1.10*:Benchmarks and Open Source Tools
 1.11*:Invited: Advancing Neural Engineering Through Big Data
2:Bioinformatics and Systems Biology
 2.1*:High throughput sequencing data analysis
 2.2*:Big data analytics in genomics and proteomics
 2.3*:SNP/genotype/haplotype calling
 2.4*:Biomarker discovery
 2.5*:Modeling of disease dynamics
 2.6*:Drug screening and effectiveness prediction
 2.7*:Genetic network and pathway modeling and simulation
 2.8*:Dynamics and control of genetic regulatory networks
 2.9*:Functions of miRNA and non-coding RNAs
 2.10*:Invited: Bioinformatics and Systems Biology
3:Controlled Sensing For Inference: Applications, Theory and Algorithms
 3.1*:Sensor Management for tracking
 3.2*:Sensor Management for detection, estimation, and classification
 3.3*:Management of heterogeneous sensing resources
 3.4*:Data-driven and non-parametric inference methods
 3.5*:Information collection, processing and fusion
 3.6*:Fundamental limits of sensing systems
 3.7*:Applications of controlled sensing to infrastructure monitoring
 3.8*:Controlled sensing for medical imaging
 3.9*:Radar and surveillance applications
 3.10*:Controlled sensing in social networks
 3.11*:Invited: Controlled Sensing For Inference: Applications, Theory and Algorithms
4:Cyber-Security and Privacy
 4.1*:Analysis and mitigation of side channels
 4.2*:Attacks on privacy and privacy technologies
 4.3*:Fingerprinting and watermarking
 4.4*:Information-theoretic security
 4.5*:Network security and intrusion detection
 4.6*:Privacy challenges in large data
 4.7*:Secure computation framework
 4.8*:Traffic analysis
 4.9*:Biometric Security, Privacy and Authentication
 4.10*:Machine Learning in Security
 4.11*:Invited: Cyber-Security and Privacy
5:Emerging Challenges in Network Sensing, Inference, and Communication
 5.1*:Sparsity in network sensing, inference, and communication
 5.2*:Network structure inference from noisy observations
 5.3*:Network inference in the presence of missing data
 5.4*:Efficient sensing of network data
 5.5*:Energy management in networks
 5.6*:Complex network topology
 5.7*:Dynamics of networks
 5.8*:Flows on networks
 5.9*:Applications in communication networks
 5.10*:Applications in biological networks
 5.11*:Applications in social networks
 5.12*:Invited: Emerging Challenges in Network Sensing, Inference, and Communication
6:Energy Harvesting and Green Wireless Communications
 6.1*:Physical layer design for energy harvesting communications
 6.2*:Signal processing for energy harvesting communication
 6.3*:Information theory of energy harvesting communications
 6.4*:Network theoretic approaches for energy harvesting communications
 6.5*:Energy and message cooperation
 6.6*:Energy efficient MIMO
 6.7*:Design of green wireless communication systems with hybrid energy sources
 6.8*:Heterogeneous green wireless communications systems
 6.9*:Small cell networks and green communications
 6.10*:Invited: Energy Harvesting and Green Wireless Communications
7:Graph Signal Processing
 7.1*:Transforms for graph signals
 7.2*:Estimation, denoising, and compression for graph signals
 7.3*:Sparse representations of graph signals
 7.4*:Multi-scale analysis on graphs
 7.5*:Graph signal downsampling and simplification
 7.6*:Uncertainty principles for graph signals
 7.7*:Estimating graph structure from data point-clouds
 7.8*:Graph signal processing in machine learning
 7.9*:Applications of graph signal processing
 7.10*:Invited: Graph Signal Processing
8:Information Processing in the Smart Grid
 8.1*:Smart Grid Communication Networks
 8.2*:Demand Side Management Systems
 8.3*:Smart Grid Cyber-Security and Privacy
 8.4*:Architectures and Models for the Smart Grid
 8.5*:Smart Grid Large Data Sets: Modeling, Analysis, Communications, Compression, Storage and Security
 8.6*:Distributed Data Processing and Decision-making in the Grid
 8.7*:Smart Metering Networks and Data Processing
 8.8*:Communication and Data Processing for Phasor Measurement Units
 8.9*:Renewable and Storage Integration Challenges in Smart Grid Cyber Systems
 8.10*:Real-Time Electricity Market Interactions
 8.11*:Secure Power System State Estimation and Monitoring
 8.12*:Invited: Information Processing in the Smart Grid
9:Information Processing over Networks
 9.1*:Advances in network science
 9.2*:Bio-inspired distributed processing
 9.3*:Biological networks
 9.4*:Distributed adaptation
 9.5*:Distributed control mechanisms
 9.6*:Distributed detection and inference
 9.7*:Distributed estimation and filtering
 9.8*:Distributed game-theoretic strategies
 9.9*:Distributed information processing
 9.10*:Distributed learning
 9.11*:Distributed optimization
 9.12*:Graphical models
 9.13*:Signal processing over graphs
 9.14*:Social networks
 9.15*:Random graph representations
 9.16*:Sparse graph representations
 9.17*:Invited: Information Processing over Networks
10:Low-Dimensional Models and Optimization in Signal Processing
 10.1:Dimensionality Reduction
  10.1.1*:Linear dimensionality reduction and compressive sensing
  10.1.2*:Nonlinear dimensionality reduction and manifold learning
  10.1.3*:Subsampling, inpainting, and partial observations
  10.1.4*:Adaptive sensing
  10.1.5*:Active learning
  10.1.6*:Experimental design
  10.1.7*:Information scalability
 10.2:Algorithms for Signal Processing
  10.2.1*:Optimization Algorithms
  10.2.2*:Greedy Algorithms
  10.2.3*:Optimization Solvers
 10.3:Signal Models
  10.3.1*:Subspaces and unions of subspaces
  10.3.2*:Sparsity and structured sparsity
  10.3.3*:Low-rank matrices
  10.3.4*:High-dimensional tensors
  10.3.5*:Nonlinear manifolds
 10.4:Signal Processing
  10.4.1*:Detection and classification
  10.4.2*:Estimation and inference
  10.4.3*:Supervised learning
  10.4.4*:Clustering and unsupervised learning
 10.5:Compressive Sensing
  10.5.1*:Compressive sensor architectures and hardware
  10.5.2*:Computationally efficient recovery and estimation algorithms
  10.5.3*:Practical considerations
  10.5.4*:Distributed sensing and sensor networks
 10.6*:Invited: Low-Dimensional Models and Optimization in Signal Processing
11:Low-Power Systems and Signal Processing
 11.1*:Speech, Audio and Signal Processing
 11.2*:Vision and Image Processing
 11.3*:Bio-Medical Signal Processing
 11.4*:Sensor Analytics
 11.5*:Sensor Fusion
 11.6*:Distributed Sensor Networks
 11.7*:Body Area Networks
 11.8*:Invited: Low-Power Systems and Signal Processing
12:Millimeter Wave Imaging and Communications
 12.1*:Millimeter Wave Coherent Imaging and Signal Processing
 12.2*:Holographic Millimeter-wave Imaging, Automotive Radars, and Remote Sensing
 12.3*:Compressive Sensing in Radars and Imaging
 12.4*:MIMO Radars
 12.5*:Millimeter Phased Arrays
 12.6*:Quasi-Optical Techniques
 12.7*:THz Imaging
 12.8*:Millimeter Wave Communication Systems and Applications
 12.9*:Signal Processing Techniques for Impairments in Millimeter Wave Systems
 12.10*:Invited: Millimeter Wave Imaging and Sensing
13:Mobile Imaging
 13.1*:Multimedia processing on mobile devices
 13.2*:Mobile computational photography
 13.3*:Augmented reality
 13.4*:Image enhancement for mobile devices
 13.5*:Mobile visual search
 13.6*:Mobile imaging system design
 13.7*:Mobile image quality
 13.8*:User experience and interaction on mobile devices
 13.9*:Invited: Mobile Imaging
14:Network Theory
 14.1*:Wireless networking
 14.2*:Distributed signal processing
 14.3*:Social Networks
 14.4*:Biological networks
 14.5*:Network information theory
 14.6*:Network coding
 14.7*:Distributed storage systems
 14.8*:Multi-agent systems
 14.9*:In-network computations
 14.10*:Networked control systems
 14.11*:Invited: Network Theory
15:New Sensing and Statistical Inference Methods
 15.1*:Active learning and adaptive sampling
 15.2*:Compressive-sensing-inspired systems
 15.3*:Computational imaging systems
 15.4*:Computational methods for "big data"
 15.5*:Data-adaptive representation theory/Dictionary learning
 15.6*:Distributed statistics/machine learning
 15.7*:High-dimensional statistical inference
 15.8*:Manifold-based signal processing
 15.9*:New sensing paradigms in medical imaging
 15.10*:Information processing in social networks
 15.11*:Robust statistical inference
 15.12*:Sensing/inference for biological processes
 15.13*:Sensing/processing of hyperspectral data
 15.14*:Statistical inference in graphical models
 15.15*:Invited: New Sensing and Statistical Inference Methods
16:Optimization in Machine Learning and Signal Processing
 16.1*:Models and estimation
 16.2*:Sparsity, Low-rank and other methods in high-dimensional statistics
 16.3*:Large-scale convex optimization: algorithms and applications
 16.4*:Graphical models: inference, structure learning etc.
 16.5*:Optimization for clustering, classification, regression etc.
 16.6*:Non-convex and iterative methods
 16.7*:Invited: Optimization in Machine Learning and Signal Processing
17:Signal and Information Processing in Finance and Economics
 17.1*:Portfolio analysis: modeling and estimation of statistical dependence, sparse portfolios, robust portfolios, portfolio replication and tracking
 17.2*:Risk analysis and modeling
 17.3*:Term structure modeling
 17.4*:Market microstructure analysis and order book modeling
 17.5*:Market making and inventory management
 17.6*:Technical analysis
 17.7*:Algorithmic trading and optimal order execution
 17.8*:Financial networks and systemic risk
 17.9*:Behavioral finance and prospect theory
 17.10*:Pricing and hedging of derivatives
 17.11*:Smart order routing algorithms
 17.12*:Spectrum markets
 17.13*:Electricity markets and Smart Grid
 17.14*:Economics of social networks
 17.15*:Business analytics
 17.16*:Invited: Signal and Information Processing in Finance and Economics
18:Software Defined and Cognitive Radios
 18.1*:Algorithm and architecture co-optimization
 18.2*:Platforms and architectures for SDR and CR
 18.3*:RF/analog architectures for SDR
 18.4*:Design methodologies and tools
 18.5*:Baseband processing techniques
 18.6*:Software for SDR and cognitive radios
 18.7*:Cognitive radio technologies
 18.8*:Dynamic spectrum access technologies
 18.9*:Invited: Software Defined and Cognitive Radios