The IEEE International Conference on Future Machine Learning and Data Science, Sydney, 2024 (FMLDS-2024) will bring international and national experts in Artificial Intelligence, Computer Vision, Future Machine Learning Technologies and Data Science.
CONFERENCE THEMES


Future Machine Learning
• Explainable Artificial Intelligence
• Quantum Computing
• Big Data Model
• No-Code Environment
• Reinforcement Learning

Advancements of Machine Learning
• Improved Internet Search
• Chatbots
• ChatGPT
• Transportation Trends
• ML in Music, Art and Leisure

Pattern Recognition
• Fuzzy Logic, Learning Theory
• Reasoning with incomplete data
• Set Theory;
• Probabilistic Approaches Computing Paradigms
• Affective Computing
Computer Graphics
• Biometrics
• Aqua Farm
• Low- Level Vision and Image processing
Motion and Tracking
• Robotics
• Phase Array Antennae
• Applications of Radar
• Statistical Methods
• Testing and Performance Evaluation
Bioinformatics and Biomedical Image Analysis
• Bioinformatics
• Video Analysis and Event Recognition
• Signal Processing
• Support Vector Machine
• Bayesian Belief Networks
Data Classification and Regression
• Denoising
• Functional Recovery
• Interpretation and Approximation
• Spectral and Area Based Methods
• Data and Image Compression
Data Science and Big Data
• Cloud Computing
• High Performance Computing
• Scalable Computing
• Computations on GPU
• Information Retrieval
Cyber Security and Privacy for Big Data
• Cyber-attacks
• Cyber Security
Knowledge Discovery, Integration and Transformation
• Social Epidemiology, algorithms in Neuroscience
• Neuro-psychoanalysis
Social Media, Social Network and Social Data
• Classification of Diseases
• Cladistics
• Genomic Sequencing
• Developmental Biology
• Origin of Life
Financial Machine Learning and Data Mining
• Financial Engineering & Economics Applications
• Portfolio Optimization and Asset Allocation
• Algorithmic and Quantitative Trading
• Financial Data Analysis
Internet of Things
• IoT and Artificial Intelligence techniques
• IoT and Personal Data Protection
• Security and Privacy in IoT