As an interdisciplinary international conference this conference welcomes ideas outside of the box, interdisciplinary collaborations as well as new topics for research which may be outside of mainstream.

Conference Tracks

(It will of course welcome papers on but by no means restricted to in existing disciplines, e.g.)

Future Machine Learning

Explainable Artificial Intelligence
Quantum Computing
Big Data Modeling
No-Code Development Environments
Reinforcement Learning

Machine Learning in Engineering Applications

Construction Engineering
Water Engineering

Computer Vision and Graphics

Biometrics
Aqua Farming Technologies
Low- Level Vision and Image Processing
Motion and Tracking Technologies

Bioinformatics and Biomedical Applications

Bioinformatics
Video Analysis and Event Recognition
Signal Processing
Support Vector Machines (SVM)
Bayesian Belief Networks

Data Classification and Regression

Denoising and Functional Recovery
Interpretation and Approximation
Spectral and Area Based Methods
Data and Image Compression

Cyber Security and Privacy for Big Data

Cyber-attacks
Cyber Security

Machine Learning in Social Media and Social Network

Classification of Diseases and Genomic Sequencing
Social Network Analysis

Machine Learning in Internet of Things (IoT)

Artificial Intelligence Techniques in IoT

Advancements of Machine Learning

Improved Internet Search
Chatbots and Conversational AI (e.g., ChatGPT)
Applications in Transportation
Applications in Music, Art and Leisure

Pattern Recognition

Fuzzy Logic, Learning Theory
Reasoning with incomplete data
Set Theory and Probabilistic Approaches Affective Computing
Statistical Methods in Motion Tracking

Robotics and Automation

Robotics Application
Testing and Performance Evaluation

Data Science and Big Data

Cloud Computing and High Performance Computing
Scalable Computing and Computations on GPU
Information Retrieval

Knowledge Discovery, Integration and Transformation

Social Epidemiology, Algorithms in Neuroscience
Neuro-psychoanalysis

Machine Learning in Finance and Data Mining

Financial Engineering & Economics Applications
Portfolio Optimization and Asset Allocation
Algorithmic and Quantitative Trading
Financial Data Analysis

Machine Learning in Language Models

Large Language Models (LLMs)
Vision Language Models (VLMs)