HYBRID EVENT: Join us in person at Rome, Italy or virtually from anywhere!

EurasiaConferences
3rd World Conference on

Artificial Intelligence, Machine Learning and Data Science

May 16 - 17 , 2024 | Rome, Italy
Rome, Italy
[email protected]

Welcome to WCAIMLDS-Rome-2024

May 16 - 17 , 2024 | Rome, Italy

First Round Abstract Submission:​
31-12-2023

Earlybird Registration:
On/Before 15-01-2024

Submit Abstract Register

About WCAIMLDS-Rome-2024

Join us at the 3rd World Conference on Artificial Intelligence, Machine Learning, and Data Science  set to unfold from May 16 to May 17, 2024, in the magnificent city of Rome, Italy! This conference is a pivotal event that brings together leading researchers, practitioners, and enthusiasts in the fields of Artificial Intelligence (AI), Machine Learning (ML), and Data Science. Hosted in Rome, a city steeped in history and culture, this international gathering provides a platform for knowledge exchange, innovation, and collaboration. Attendees can look forward to a dynamic program filled with keynote presentations, oral and poster sessions, and networking opportunities.

Rome's rich tradition of scientific inquiry and technological advancement makes it the perfect location for this conference. Whether you're an AI expert, a data scientist, a machine learning enthusiast, or simply curious about the latest trends and breakthroughs in these fields, mark your calendar for May 16-17, 2024, and join us for an unforgettable experience. This event is designed to showcase the forefront of AI, ML, and Data Science, covering topics from ethics and responsible AI to practical applications and emerging technologies.

We invite you to be a part of the 3rd World Conference on Artificial Intelligence, Machine Learning, and Data Science, where you can immerse yourself in the future of technology, gain valuable insights, and contribute to the global conversation shaping the AI and data-driven world!.

Abstract Topics

  • Deep Learning Applications in Healthcare
  • Natural Language Processing for Information Extraction
  • Image Processing and Computer Vision
  • Recommender Systems and Personalization
  • Data Mining Techniques for Big Data Analysis
  • Machine Learning for Cybersecurity
  • Reinforcement Learning in Robotics
  • Bayesian Learning for Uncertainty Estimation
  • Time Series Analysis and Forecasting
  • Predictive Analytics for Business Intelligence
  • Transfer Learning for Model Generalization
  • Generative Adversarial Networks for Image Synthesis
  • Explainable AI and Interpretability
  • Federated Learning for Collaborative Intelligence
  • Neural Networks for Speech Recognition
  • Multimodal Learning for Multimedia Processing
  • Human-Machine Interaction and Collaboration
  • Knowledge Representation and Reasoning
  • Data Privacy and Security in Machine Learning
  • Graph Mining and Network Analysis
  • Active Learning for Efficient Data Collection
  • Cognitive Computing and Intelligent Agents
  • Sentiment Analysis and Opinion Mining
  • Unsupervised Learning for Clustering
  • Data Visualization and Exploration
  • Machine Learning for Medical Imaging
  • Online Learning for Streaming Data
  • Feature Selection and Dimensionality Reduction
  • Automated Machine Learning and AutoML
  • Multi-Task and Multi-Modal Learning
  • Robustness and Adversarial Attacks in Deep Learning
  • Real-Time and Embedded Systems for AI
  • Sequential Decision Making and Planning
  • Blockchain and Distributed Ledgers for Data Privacy
  • Machine Learning for Smart Cities
  • Active Perception and Sensor Fusion
  • Speech and Language Translation
  • Meta-Learning for Model Adaptation
  • Spatial-Temporal Learning for Video Analysis
  • Causal Inference and Counterfactual Reasoning
  • Machine Learning for Time Series Forecasting
  • Edge Computing and Federated Learning
  • Explainable Recommendation Systems
  • Automated Feature Engineering and Selection
  • Auto-Encoding and Variational Autoencoders
  • Neurosymbolic Integration and Reasoning
  • Reinforcement Learning for Traffic Control
  • Machine Learning for Drug Discovery
  • Adversarial Machine Learning for Security Testing
  • Multi-Objective Optimization and Pareto Fronts

Who Can Attend?

  • AI and ML researchers
  • Data scientists and analysts
  • Big data professionals
  • Natural language processing experts
  • Computer vision specialists
  • Deep learning practitioners
  • Robotics engineers and researchers
  • Cognitive computing professionals
  • Business intelligence and analytics experts
  • Data engineers and architects
  • Software developers and programmers
  • Machine learning engineers and developers
  • Data mining and pattern recognition experts
  • Computer scientists and engineers
  • Data privacy and security experts
  • Cloud computing professionals
  • Internet of Things (IoT) specialists
  • Artificial neural networks researcher
  • Multi-agent and swarm intelligence experts
  • Computational biologists

Why to Attend?

  • Learn from experts in your field
  • Expand your professional network
  • Gain new perspectives and insights
  • Present your own research and receive feedback
  • Discover new career paths and job opportunities
  • Expose yourself to new ideas and innovations
  • Explore new cultures and countries
  • Take a break from your routine and recharge
  • Receive a certificate of participation

Conference Schedule

Our tentative program is scheduled as follows.

Registrations

Opening Ceremony

Keynote Sessions

Refreshment Break

Speaker Sessions

Lunch Break

Speaker Sessions

Refreshment Break

Speaker Sessions

Keynote Sessions

Refreshment Break

Speaker Sessions

Lunch Break

Speaker Sessions

Refreshment Break

Poster Presentations

Closing Ceremony

Organizer

Eurasia Conferences

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