This conference presents excellent, novel, and contemporary papers covering all aspects of Data – including Scientific Theory and Technology-Based Applications. New data analytic algorithms, technologies, and tools are sought for data management in the face of hardware, software, and/or bandwidth constraints; to construct models yielding important data insights; and, to create visualizations to aid in presenting and understanding the data. System development and integration need to adapt to these new algorithms, technologies, tools, and needs. This conference and its constituents support the development of science and technology to improve the human condition.
Furthermore, IRI addresses the representation, cleansing, generalization, validation, and reasoning strategies for the scientifically sound and the cost-effective advancement of all systems and systems of systems (SoS) – including all software and hardware aspects. These non-trivial tasks lead to challenging research problems – for example, how to optimally select the information/data sets for reuse and how to optimize the integration of existing information/knowledge with new, developing information/knowledge sources!
The IEEE IRI conference serves as a forum for researchers and practitioners from academia, industry, and government to present, discuss, and exchange ideas that address real-world problems with real-world solutions. Theoretical and applied papers are both welcome. The conference program will include several plenary speeches from academia, industry, and government; special sessions, open forum workshops, and panels.
The conference includes, but is certainly not limited to, the areas listed below:
Applications – Autonomous Vehicles, Business, Education, Engineering, Healthcare and Medical Informatics, the Internet of Things, Math, Military, Multimedia, NLP, Robotics, Science, Security, Social Networking, Space, Vision, etc.
Brain-Computer Interface: Applications and Algorithms
Contemporary as well as Novel Data Mining Techniques
Data & Knowledge Representation and Management
Data Science & Technologies – Heuristic Acquisition
Data Science and Software Engineering – Identify Security Bugs, Code Reviews, Adaptive Systems, Testing, etc.
Machine Learning & AI
Heuristics, and Explanation-Based Learning vs. neural networks which are intractable
AI and Security
Predictive Data Analysis & Intelligence
Information Science & Theory