Objective of the conference

ICCSMLBD provides a leading forum for the presentation of new advances and research results in the fields of Computer Science, Machine Learning, and Big Data. The conference will bring together leading researchers, engineers, and scientists in the domain of interest from around the world.

Conference Interest Topics

Topics of interest for submission include, but are not limited to:

Computer Science

• Communication and Networking
• Database Systems, Data Warehousing, and Data Mining
• Information Assurance
• Web Services and Technologies
• Software Engineering
• Multimedia Processing
• Mobile and Cloud Computing
• Human-Centred Computing
• Distributed and Parallel Computing
• Programming Languages
• Artificial Intelligence and Machine Learning
• E–Systems and Computer Systems
• Analog and Mixed-Signal IC Design and Testing
• RF IC Design and Testing
• Digital IC Design and Testing
• Technology CAD
• Ge Microelectronics
• Integrated circuits manufacturing and Reliability
• Electronic Devices, Compound Semiconductors, Si-Ge Heterostructures
• MEMS and Microsystems
• Solar Cells and Photonics
• Wireless Communication and Sensor Networks
• Optical Communication
• Satellite Communication
• MIMO, OFDM and Smart Antennas
• Image and Video Processing
• Pattern Recognition and Image Understanding
• Biomedical Signal Processing
• Biomedical Instrumentation and Sensors
• Multimedia Coding and Communication
• Speech and Audio Signal Processing
• Adaptive Signal Processing
• Embedded Systems
• Computer Networks
• Network Coding and Information Theory

Machine learning

• Deep and Reinforcement learning
• Pattern recognition and classification for networks
• Machine learning for network slicing optimization
• Machine learning for 5G system
• Machine learning for user behavior prediction
• New innovative machine-learning methods
• Optimization of machine learning methods
• Performance analysis of machine learning algorithms
• Experimental evaluations of machine learning
• Data mining in heterogeneous networks
• Machine learning for multimedia
• Machine learning for the Internet of Things
• Machine learning for security and protection
• Distributed and decentralized machine learning algorithms
• Intelligent cloud-support communications
• Intelligent ressource allocation
• Intelligent energy-aware/green communications
• Intelligent software-defined networks
• Intelligent cooperative networks
• Intelligent positioning and navigation systems
• Intelligent wireless communications
• Intelligent wireless sensor networks
• Intelligent underwater sensor networks

Big-Data Engineering

• Innovative Cloud infrastructure for Big Data
• Green, energy-efficient models and sustainability issues for Big Data
• Resource scheduling, SLA, Fault tolerance, and reliability for Big Data
• Data Models for Big Data Analytics
• Machine Learning techniques for Big Data
• Index Structures for Big Data Analytics
• Interaction Design for Exploratory Analytics
• Large-scale recommendation systems and graph analysis
• Big data security, privacy, and services
• Big Data applications on heterogeneous architectures such as healthcare, surveillance and sensing, e-commerce, etc