BUDAPEST 3rd International Congress on Applications of Artificial Intelligence Technologies: BAAT-27

Call for papers/Topics

All Abstracts, Reviews, short articles, Full articles, Posters are welcomed related with any of the following research fields:

Core Methods & Learning Paradigms

• Machine Learning

  • Supervised Learning

  • Unsupervised Learning

  • Reinforcement Learning

  • Semi-Supervised & Self-Supervised Learning

• Deep Learning & Neural Architectures

  • Convolutional Neural Networks

  • Recurrent & Transformer Networks

  • Generative Adversarial Networks

  • Deep Reinforcement Learning

• Symbolic & Knowledge-Based AI

  • Expert Systems

  • Knowledge Graphs & Ontologies

  • Automated Reasoning & Logic Programming

• Hybrid Systems

  • Neuro-Symbolic AI

  • Physics-Informed Machine Learning

Perceptual & Cognitive AI Technologies

• Natural Language Processing & Generation

  • Large Language Models

  • Machine Translation

  • Speech Recognition & Synthesis

  • Sentiment Analysis & Text Mining

• Computer Vision & Image Processing

  • Object Detection & Tracking

  • Facial Recognition

  • Image & Video Segmentation

  • 3D Scene Reconstruction

• Robotics & Spatial AI

  • Autonomous Navigation & SLAM

  • Robotic Process Automation

  • Kinematics & Manipulation Control

Industry & Sector Applications

• Healthcare & Life Sciences

  • Diagnostic Imaging Analysis

  • Drug Discovery & Molecular Modeling

  • Predictive Patient Analytics

  • Personalized Medicine

• Finance & Commerce

  • Algorithmic Trading

  • Fraud Detection & Anti-Money Laundering

  • Credit Risk Assessment

  • Personalized Recommendation Engines

• Transportation & Logistics

  • Autonomous Vehicles & Flight Systems

  • Traffic Flow Optimization

  • Supply Chain Forecasting

• Cybersecurity & IT Operations

  • Threat Detection & Anomaly Recognition

  • Automated Incident Response

  • AI-Assisted Software Development

Cross-Cutting Application Domains

• Edge & Embedded AI

  • On-Device Inference

  • Microcontroller Machine Learning

• Generative & Creative Technologies

  • Synthetic Data Generation

  • Automated Code Generation

  • Multimodal Content Creation

• Ethics, Governance & Operational Control

  • Explainable AI

  • AI Safety & Alignment

  • Bias Mitigation & Fairness Frameworks

Interrelations Across Fields

• Deep Learning powers Computer Vision (via Convolutional Architectures) and Natural Language Processing (via Transformers), forming the underlying engines for industry solutions like Diagnostic Imaging in Healthcare and Autonomous Navigation in Transportation.

• Symbolic AI combines with Deep Learning to create Neuro-Symbolic AI, improving Explainable AI and adding safety constraints to domain applications such as Algorithmic Trading and Automated Incident Response.

• Edge AI optimizes Machine Learning models to run on physical hardware, enabling real-time execution in Robotics, On-Device Inference, and low-latency Cybersecurity Threat Detection