International Conference on Artificial Intelligence and

Machine Learning (CAIML 2020)


May 30~31, 2020, Vancouver, Canada


SCOPE

International Conference on Artificial Intelligence and Machine Learning (CAIML 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.

Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of AI and Machine Learning.


TOPICS OF INTEREST

Artificial Intelligence

  • AI Algorithms

  • Artificial Intelligence Tools and Application

  • Automatic Control

  • Bioinformatics

  • CAD Design and Testing

  • Computational Theories of Learning

  • Computer Vision and Speech Understanding

  • Data Mining and Machine Learning Tools

  • Fuzzy Logic

  • Heuristic and AI Planning Strategies and Tools

  • Hybrid Intelligent Systems

  • Information Retrieval

  • Intelligent System Architecture

  • Knowledge Representation

  • Knowledge-based Systems

  • Mechatronics

  • Multimedia & Cognitive Informatics

  • Natural Language Processing

  • Neural Networks

  • Parallel Processing

  • Pattern Recognition

  • Pervasive Computing and Ambient Intelligence

  • Programming Languages

  • Reasoning and Evolution

  • Recent Trends and Developments

  • Robotics

  • Semantic Web Techniques and Technologies

  • Soft computing theory and Applications

  • Software & Hardware Architectures

  • Web Intelligence Applications & Search

Machine Learning

  • Applications

  • Learning in knowledge-intensive systems

  • Learning Methods and analysis

  • Learning Problems


Paper Submission

Authors are invited to submit papers through the conference Submission System by CLOSED. 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).


Selected papers from CAIML 2020, after further revisions, will be published in the special issue of the following journals


CONFERENCE PROCEEDINGS

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

INVITED TALK

Rituparna Datta

University of South Alabama, USA

COURTESY

CALL FOR PARTICIPATION

SPEAKERS

Mashael Sulaiman Maashi

King Saud University,

Kingdom of Saudi Arabia

Amir Farzad

University of Victoria,

Canada

Xiang AO

City University of Hong Kong,

Hong Kong

Grace Kobusinge

Gothenburg University,

Sweden

Nitin Khosla

Department of Home Affairs,

Australia

Tao Yan

Putian University,

China

Jacob Danovitch

Carleton University,

Canada

Rajeev Kanth

Savonia University of Applied Sciences,

Finland

Haider Khalid

University of Dublin,

Ireland

Alaidine Ben Ayed

UQAM : Montreal,

Canada

Mustapha Hedabou

VI Polytechnic University,

Morocco

Sukhwan Jung

University of South Alabama

USA

Shaodi Li

University of Science and Technology of China,

China

Courtney Foots

University of South Alabama,

USA

Krikor Maroukian

Microsoft Greece,

Greece

Salah Harb

Concordia University,

Canada

Emilia Apostolova

Language.ai,

USA

Faïza Tabbana

Military Academy,

Tunisia

Ngan-Khanh CHAU

An Giang University & Vietnam National University,

Vietnam