6^th International Conference on AI, Machine Learning and Applications (AIMLA 2026)

March 21 ~ 22, 2026, Sydney, Australia

Scope & Topics

6^th International Conference on AI, Machine Learning and Applications (AIMLA 2026) serves as a premier global forum for presenting and exchanging the latest advances in Artificial Intelligence, Machine Learning, and their rapidly expanding range of real world applications. AIMLA 2026 brings together leading researchers, innovators, and industry practitioners to share breakthroughs in theory, algorithms, methodologies, and system level implementations that are shaping the future of intelligent technologies.

The conference welcomes high impact contributions across all major areas of AI and ML spanning foundational research, applied innovations, and interdisciplinary developments. By fostering collaboration between academia and industry, AIMLA 2026 aims to provide a dynamic platform for discussing emerging challenges, exploring transformative ideas, and showcasing cutting edge progress that drives the next generation of intelligent systems.

Topics of interest include, but are not limited to, the following

Foundations of AI & Machine Learning


• Machine Learning Theory & Optimization
  
• Statistical Learning & Generalization
  
• Probabilistic Modeling & Bayesian Methods
  
• Causality, Counterfactual Reasoning & Causal ML
  
• Trustworthy, Explainable & Interpretable AI (XAI)
  
• Fairness, Accountability & Ethics in AI
  
  Deep Learning & Representation Learning
  
  
• Deep Neural Architectures & Training Techniques
  
• Self Supervised, Semi Supervised & Weakly Supervised Learning
  
• Generative Models (GANs, Diffusion Models, VAEs)
  
• Foundation Models & Large Scale Pretraining
  
• Multimodal Learning (vision language, audio text, sensor fusion)
  
• Continual, Lifelong & Transfer Learning
  
  Natural Language Processing & Speech Technologies
  
  
• Large Language Models (LLMs) & Instruction Tuning
  
• Text Generation, Summarization & Reasoning
  
• Speech Recognition, Synthesis & Spoken Dialogue Systems
  
• Multilingual & Low Resource NLP
  
• Responsible & Safe Language Models
  
  Computer Vision & Perception
  
  
• Image/Video Understanding & Scene Analysis
  
• Vision Transformers & Diffusion Based Vision Models
  
• 3D Vision, Reconstruction & Robotics Perception
  
• Multimodal Vision Language Models
  
• Medical Imaging & Scientific Vision Applications
  
  Reinforcement Learning & Decision Making
  
  
• Deep RL, Offline RL & Safe RL
  
• Multi Agent Systems & Game Theoretic Learning
  
• Planning, Control & Sequential Decision Making
  
• RL for Robotics, Autonomous Systems & Real World Deployment
  
  Applied AI & Domain Specific Intelligence
  
  
• AI for Healthcare, Bioinformatics & Computational Biology
  
• AI for Finance, Climate, Sustainability & Energy
  
• AI for Education, Social Good & Public Policy
  
• Scientific Machine Learning & Physics Informed Models
  
• AI for Smart Cities, IoT & Cyber Physical Systems
  
  Robotics, Autonomous Systems & Embodied AI
  
  
• Robot Learning & Adaptive Control
  
• Embodied AI, Simulation & Digital Twins
  
• Human Robot Interaction & Assistive Robotics
  
• Autonomous Vehicles, Drones & Navigation
  
  Data Science, Knowledge Systems & Information Retrieval
  
  
• Large Scale Data Mining & Knowledge Discovery
  
• Knowledge Graphs, Semantic Reasoning & Ontologies
  
• Information Retrieval, Search & Recommender Systems
  
• Vector Databases & Embedding Based Retrieval
  
  AI Systems, Hardware & Scalability
  
  
• Distributed & Parallel Training Systems
  
• Efficient AI: Model Compression, Quantization & Pruning
  
• Edge AI, TinyML & On Device Learning
  
• Neuromorphic Computing & AI Accelerators
  
• Software/Hardware Co Design for ML Workloads
  
  Emerging Topics & Frontier Research
  
  
• AI Safety, Alignment & Robustness
  
• Adversarial ML & Secure AI Systems
  
• Synthetic Data Generation & Data Centric AI
  
• Human AI Collaboration & Cognitive Modeling
  
• Autonomous Agents & Multi Modal Reasoning
  
• Benchmarking, Evaluation & Reproducibility in AI
  

Paper Submission

Authors are invited to submit papers through the conference Submission System by January 24, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from AIMLA 2026, after further revisions, will be published in the special issue of the following journals.

• Machine Learning and Applications: An International Journal (MLAIJ)
  
• International Journal of Artificial Intelligence & Applications (IJAIA)
  
• International Journal on Soft Computing (IJSC)
  
• Advances in Vision Computing: An International Journal (AVC)
  
• International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI)
  

Important Dates

Co - Located Event

• 14^th International Conference on Database and Data Mining (DBDM 2026)
  
• 14^th International Conference on Instrumentation and Control Systems (CICS 2026)
  
• 6^th International Conference on NLP & Text Mining (NLTM 2026)
  
• 6^th International Conference on Computing and Information Technology (COIT 2026)
  
• 13^th International Conference on Computer Networks & Communications (CCNET 2026)
  
• 6^th International Conference on IOT, Big Data and Security (IOTBS 2026)
  

***** The invited talk proposals can be submitted to aimla@ccnet2026.org