Verticals
AI Standards and QA for Semiconductors
Scope
This vertical section solicits and publishes technical papers and provides hot-topic discussions on AI intelligence standards and quality assurance process & metrics for AI-powered semiconductor chips, platforms, and frameworks.
Topics
- AI standardization (including industry standards) for intelligent technologies and systems in diverse topics in AI-enabled data, smart healthcare agents, healthcare-specific machine learning models, edge-based healthcare intelligence stations, and service platforms, AI-powered healthcare functions and validation.
- Intelligent semiconductor chips, platforms, and framework quality assurance process, validation methods, quality testing models, and evaluation metrics.
Organisation Team
Hiu Young Wong
San Jose State University, USA
Chris Wang
Applied Materials, USA
AI Standards and QA for Chatbots
Scope
This vertical section solicits and publishes technical papers and provides hot-topic discussions on AI intelligence standards and quality assurance process and metrics for AI-powered healthcare technologies and systems.
Topics
- AI standardization (including industry standards) for intelligent chatbot systems in diverse topics in AI-enabled data, LLM language modeling, smart chat agents, and human-link chatting service platforms.
- Quality assurance process, validation methods, quality testing models, and evaluation metrics for Intelligent chatbots, LLM models, nature language communication agents, and human-like chatting service platforms and frameworks.
Organisation Team
Ying Liu
Stanta Clara University, USA
Vassilis Katsouros
Athena Research Center, Greece
AI Standards and QA for Computer Vision
Scope
This vertical section solicits and publishes technical papers and provides hot-topic discussions on Intelligent Computer Vision standards and quality assurance process & metrics for AI-powered healthcare technologies and systems.
Topics
- AI standardization (including industry standards) for intelligent computer vision and systems in diverse topics in computer vision data, computer vision intelligence, machine learning models, intelligent computer vision service platforms.
- Intelligent computer vision system quality assurance process, validation methods, quality testing models, and evaluation metrics.
Organisation Team
Katerina Potika
San Jose State University, USA
Gang Xie
Taiyuan University of Sci. & Tech., China
George Th. Papadopoulos
Harokopio University of Athens, Greece
Yassine Himeur
University of Dubai, UAE
AI Standards and QA for Smart Grids and Clean Energy
Scope
This vertical section solicits and publishes technical papers and provides hot-topic discussions on smart grids and clean energy standards and quality assurance models, processes, and quality evaluation metrics.
Topics
- AI standardization (including industry standards) for smart grids and clean energy systems, including diverse topics in AI-enabled data, smart grids, machine learning models, clean energy stations and service platforms.
- Smart grids and intelligent clean energy system quality assurance process, validation methods, quality testing models, and evaluation metrics.
Organisation Team
Maojung Hsu
AlphaRing VP of AI
Paul Townend
Umeå University, Sweden
Jing Liu
State Grid Shanghai Electric Power Research Institute
Xiaotian Xu
Beijing Urban Construction Intelligent Control, China
AI Standards and QA for Infrastructure and Tools
Scope
This vertical section solicits and publishes technical papers and provides hot-topic discussions on AI intelligence standards and quality assurance process & metrics for intelligent infrastructures, platforms, and tools.
Topics
- AI standardization (including industry standards) for intelligent computer vision technologies and systems in diverse topics in AI enabled data infrastructure and systems, large-scale machine learning modeling platforms and supporting infrastructures, AI system engineering platforms and service tools.
- Intelligent system quality assurance process, validation methods, quality testing models, and evaluation metrics for current and future AI system infrastructures and tools.
Organisation Team
Hiroyuki Sato
National Institute of Informatics, Japan
Shuguang Qi
China Academy of Information and Communication Technology (CAICT)
Peter Yen
Microsoft, USA
Antonio Alberti
University of Leeds, UK
ESG Intelligence Standards and QA for Global Environmental, Social and Governance
Scope
Topics
- AI standardization (including industry standards) for ESG intelligence and smart ESG technologies and systems, including diverse AI topics in ESG in AI enabled data, Intelligence models, frameworks, and services.
- Intelligent ESG system and technology quality assurance process, validation methods, quality testing models, and evaluation metrics.
Organisation Team
Bo Yang
University of Santa Cruz,USA
Sen Chiao
Howard University, USA
Ying Shi
China Telecom Corp. Ltd
Anandi Dutta
Texas State University, USA
AI Standards and QA in UAV and Aerospace
Scope
This vertical section solicits and publishes technical papers and provides hot-topic discussions on AI intelligence standards and quality assurance process & metrics for UAV intelligence and AI-powered aerospace systems.
Topics
- AI standardization (including industry standards) for UAV intelligence and smart aerospace systems technologies and systems, including diverse topics in AI enabled data, smart UAV agents, intelligent UAV platforms, machine learning models, UAV connectivity, UAV service platforms.
- Intelligent UAV system and technology quality assurance process, validation methods, quality testing models, and evaluation metrics.
Organisation Team
Uzu-Kuei Hsu
Pingtung University of Sci. & Tech., Taiwan
Jun Liu
San Jose State University, USA
AI Standards and QA in Healthcare
Scope
This vertical section solicits and publishes technical papers and facilitates hot-topic discussions on AI intelligence standards, quality assurance processes, and metrics for AI-powered healthcare technologies, smart medical agents, and service systems.
Topics
- AI standardization, including industry standards for intelligent healthcare technologies and systems, covers diverse topics such as AI-enabled data, smart healthcare agents, machine learning models, intelligent healthcare systems and applications, and smart medical platforms.
- Quality assurance for intelligent healthcare systems and technologies includes quality assurance processes, validation methods, quality testing models, and evaluation metrics.
Organisation Team
Liangxiu Han
Manchester Metropolitan University, UK
Liming Chen
Dalian University of Technology, China
Yalin Zheng
University of Liverpool, UK
AI Standards and QA for Robotics and Autonomous Vehicles
Scope
This vertical section solicits and attracts technical papers and discussions focusing on AI intelligence standards and quality assurance process & metrics for intelligent robots and autonomous vehicles.
Topics
- AI standardization (including industry standards) for intelligent robots and autonomous on diverse topics, including AI enabled data, machine learning models, edge-based intelligence platforms, connectivity, AI-powered intelligent functions and validation.
- Intelligent robots and autonomous vehicles system quality assurance process, validation methods, quality testing models, and evaluation metrics.
Organisation Team
Wencen Wu
San Jose State University, USA
Yingnon Chen
Arizona State University, USA
Winncy Du
San Jose State University, USA
Arash Adoujani
Instituto Italiano di Technologia, Italy
AI Standards and QA for Agritech
Scope
This vertical section solicits and publishes technical papers and provides discussions on AI intelligence standards and quality assurance process & metrics for smart agriculture, price farming, and forestry industry.
Topics
- AI standardization (including industry standards) for smart agriculture, pricing farming, and forestry in diverse topics in AI enabled data, machine learning models, intelligence systems and platforms, connectivity, AI-powered intelligent functions and validation.
- Intelligent agriculture and forestry system intelligence quality assurance process, validation methods, quality testing models, and evaluation metrics.
Organisation Team
Young Chang
South Dakota State University, USA
Yanbo Huang
US Department of Agriculture, USA
Surya Kant
La Trobe U., Bundoora, Melbourne, Australia