Conference Information
ICTAI 2020: International Conference on Tools with Artificial Intelligence
Submission Date:
2020-07-01 Extended
Notification Date:
Conference Date:
Baltimore, Maryland, USA
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Conference Location
Call For Papers
Aim & Scope

ICTAI 2020: The annual IEEE International Conference on Tools with Artificial Intelligence (ICTAI) provides a major international forum where the creation and exchange of ideas related to artificial intelligence are fostered among academia, industry, and government agencies.

The conference facilitates the cross-fertilization of these ideas and promotes their transfer into practical tools, for developing intelligent systems and pursuing artificial intelligence applications.

The ICTAI encompasses all technical aspects of specifying, developing and evaluating the theoretical underpinnings and applied mechanisms of the AI-based components of computer tools such as algorithms, architectures and languages.


ICTAI 2020 is accepting full length submissions (up to 8 pages). They should present original and technically sound research. All accepted papers, which will be registered and presented at the conference, will be included at the ICTAI 2020 proceedings published by IEEE. Authors of selected and relevant papers will be invited to submit an extended version to:

    International Journal on Artificial Intelligence Tools
    International Journal of Monitoring and Surveillance Technologies Research
    Interaction Studies Journal

Topics of Interest include (but are not limited to):

AI Foundations 	
Machine Learning and Data Mining
Evolutionary computing, Bayesian and Neural Networks 	
Pre-processing, Dimension Reduction and Feature Selection
Decision/Utility Theory and Decision Optimization 	
Learning Graphical Models and Complex Networks
Search, SAT, and CSP 	
Active, Cost-Sensitive, Semi-Supervised, Multi-Instance, Multi-Label and Multi-Task Learning
Description Logic and Ontologies 	
Transfer/Adaptive, Rational and Structured Learning
AI in Domain-specific Applications 	
Preference/Ranking, Ensemble, and Reinforcement Learning
AI in Computational Biology, Medicine and Biomedical Applications 	
Knowledge Representation, Reasoning and Cognitive Modelling
AI in WWW, Communication, Social Networking, Recommender Systems, Games and E-Commerce 	
Knowledge Representation, Reasoning
AI in Finance and Risk Management 	
Knowledge Extraction, Management and Sharing
AI in Computer Systems 	
Case-based Reasoning and Knowledge-based Systems
AI in Robotics, Computer Vision and Games 	
Cognitive Modelling and Semantic Web
AI in Natural Language Processing 	
AI and Decision Systems
AI in Software Engineering, Real-Time and Embedded Applications, and Sensor Networks 	
Decision Guidance and Support Systems
AI in Cloud Computing, Data-Intensive Applications and Online/Streaming and Multimedia Systems 	
Optimization-based Recommender Systems
AI in Web Search and Information Retrieval 	
Group, Distributed, and Collaborative Decisions
AI in Computer Security, Data Privacy, and Information Assurance 	
Crowd-sourcing and Collective Intelligence Decision-making
AI in Data Analytics and Big Data 	
Strategic, Tactical and Operational-level Decisions
Visual Analytics for Big Data 	
Decision-making in Social and Mobile Networks
Computational Modeling for Big Data 	
Uncertainty in AI
Large-scale Recommendation and Social Media Systems 	
Uncertainty and Fuzziness Representation and Reasoning
Cloud/Grid/Stream Data Mining for Big Velocity Data 	
Approximate/Exact Probabilistic Inference
Semantic-based Big Data Mining 	
Knowledge Discovery and Data Mining for Uncertain Data
AI in Smart Cities 	
AI and Societal Impact
Healthcare, Traffic, Transportation, Environment, etc. 	
AI Fairness, Accountability and Transparency
AI interpretability and explanability
Ethical and Trustworthy AI
Last updated by Dou Sun in 2020-06-25
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