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EurasiaConferences
2nd World Conference on

Artificial Intelligence, Machine Learning and Data Science

October 19 - 20 , 2023 | Paris, France
Hotel Mercure Paris CDG Airport & Convention Roissypôle Ouest, Route de la Commune, Cedex, 95713 ROISSY CHARLES DE GAULLE, Paris, France
[email protected]

Welcome to WCAIMLDS-Paris-2023

October 19 - 20 , 2023 | Paris, France

Final Round Abstract Submission:​
30-09-2023

Mid Term Registration:
On/Before 30-09-2023

Submit Abstract Register

About WCAIMLDS-Paris-2023

The 2nd World Conference on Artificial Intelligence, Machine Learning, and Data Science  will take place during October 19-20, 2023, in Paris, France. This would be one of the leading conferences in the fields of Artificial Intelligence, Machine Learning, and Data Science. The conference aims to gather scholars from all over the world to present the latest research outcomes and advances in relevant fields and provides an ideal environment for making new scientific collaborations.

The aim of the conference is to promote quality research and create an atmosphere of true international cooperation between Software Engineers, Delivery managers, and Data Science Professionals by bringing together world-class researchers, International Communities, and Industrial heads to discuss the latest developments and innovations in the fields of Artificial Intelligence, Machine Learning, and Data Science.

The 2nd World Conference on Artificial Intelligence, Machine Learning, and Data Science will increase the opportunities for researchers to network with colleagues from across the world in more focused sessions that will feature cutting-edge presentations, special panel discussions, and live interaction with industry leaders and experts.

Keynote Speakers

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 researchers
  • 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

Keynote Sessions

Lunch Break

Speaker Sessions

Refreshment Break

Speaker Sessions

Keynote Sessions

Refreshment Break

Speaker Sessions

Lunch Break

Speaker Sessions

Refreshment Break

Poster Presentations

Prize Distribution and Closing Ceremony

Organizer

Eurasia Conferences

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