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

March 21 ~ 22, 2026, Sydney, Australia


Hybrid -- Registered authors can present their work online or face to face New

Scope & Topics


6th 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 February 14, 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 Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).

Submit

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

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Important Dates

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Third Batch : (Submissions after January 31, 2026)

Submission Deadline : February 14, 2026

Authors Notification : March 07, 2026

Registration & Camera-Ready Paper Due : March 14, 2026

Courtesy

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Invited Talk





Supported by

IJCSIT

Other Conferences


Proceedings


Hard copy of the proceedings will be distributed during the Conference. The softcopy will be available on AIRCC Digital Library





Speakers



Menglong Guo
Chinese University of Hong Kong
China

Ulugbek Shernazarov
Telecom SudParis
France

Contact Us

aimla@ccnet2026.org

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