Special Track on Artificial Intelligence Testing


This special track focuses on developing frameworks, methods, tools, and empirical studies for testing data-centric artificial intelligence (AI) systems, particularly on how to use state-of-the-art technology in assessment, assurance, and improvement of big data for building high-quality AI systems.


A list of particular relevant areas includes, but is not limited to:

  • Effective frameworks and strategies for testing AI systems
  • Data quality assessment, assurance, and improvement for AI applications
  • Experimental study regarding the impact of data quality to the performance of deep learning
  • Data augmentation for the enhancement of data-centric AI
  • Evaluating large language models in different AI applications
  • Responsibility, fairness, ethics, bias, trustworthiness, transparency, accountability, safety, and privacy in AI applications

SCI Special Issue

Authors of top quality papers will be invited to submit their extended versions to the following special issue:


Authors are invited to submit original unpublished research papers as well as industrial practice papers. Simultaneous submissions to other conferences are not permitted. Detailed instructions for electronic paper submission, panel proposals, and review process can be found at QRS submission.

Each submission can have a maximum of ten pages. It should include a title, the name and affiliation of each author, a 300-word abstract, and up to 6 keywords. Shorter version papers (up to six pages) are also allowed.

All papers must conform to the QRS conference proceedings format (PDF | Word DOCX | Latex) and Submission Guideline set in advance by QRS 2024. At least one of the authors of each accepted paper is required to pay the full registration fee and present the paper at the workshop. Submissions must be in PDF format and uploaded to the conference submission site. Arrangements are being made to publish extended version of top-quality papers in selected SCI journals.


Program Chair

Junhua Ding's avatar
Junhua Ding

University of North Texas, USA

Program Co-Chairs

Haihua Chen's avatar
Haihua Chen

University of North Texas, USA

Dongcheng Li's avatar
Dongcheng Li

California State Polytechnic University, Humboldt, USA

Program Committee

Name Affiliation Geographic Region
Marco Aiello University of Stuttgart German
Oum-El-Kheir Aktouf Université Grenoble Alpes France
Everton L. G. Alves Federal University of Campina Grande Brazil
Monowar Bhuyan Umea University Sweden
Alexander Bolotov University of Westminster UK
Jaganmohan Chandrasekaran Virginia Tech USA
Zhenbang Chen National University of Defense Technology China
Claudio De La Riva University of Oviedo Spain
Wensheng Dou Institute of Software Chinese Academy of Sciences China
Anurag Dwarakanath Amazon Inc. USA
Tozammel Hossain University of North Texas USA
Francesca Lonetti ISTI-CNR Italy
Katsuhisa Maruyama Ritsumeikan University Japan
Changhai Nie Nanjing University China
Andrea Polini University of Camerino Italy
Ju Qian Nanjing University of Aeronautics and Astronautics China
Daniel Rodriguez University of Alcala Spain
Weisong Sun Nanyang Technological University Singapore
Sahar Tahvili Ericsson AB Sweden
Tatsuhiro Tsuchiya Osaka University Japan
Naoyasu Ubayashi Kyushu University Japan
Peng Wu Institute of Software Chinese Academy of Sciences China
Huanhuan Zhao University of Tennessee USA