Pillar 2: Research
Pillars 2 Research
AASTMT’s research agenda positions AI as a catalyst for discovery and innovation. By integrating Data- driven technologies and machine intelligence into every stage of the research lifecycle, fostering interdisciplinary collaboration, and advancing integrity and transparency, the Academy aims to lead in both cutting-edge domains and socially responsible innovation.
The following goals set the direction for integrating AI across AASTMT’s research agenda while ensuring innovation remains ethical and transparent:
1. Accelerate Discovery through Advanced Research Tools.
Embed AI selectively across appropriate stages of the research lifecycle—from data ingestion and pattern analysis to modeling and simulation—tailored to disciplinary needs and ethical safeguards.
2. Advance Interdisciplinary Research.
Promote collaboration across all academic disciplines within the Academy: from engineering, computer science, to medicine, law, management, logistics, language and communications, and maritime studies — to explore how AI can address shared societal, economic, and environmental challenges through integrated research initiatives.
3. Build Research Capacity in Emerging Fields.
Invest in AASTMT’s human capital to strengthen the Academy’s leadership in next-generation domains such as explainable AI, AI for sustainability, quantum AI, and sector-specific applications aligned with regional and global priorities.
4. Detect and Deter AI-Enabled Misconduct.
Integrate advanced tools in the Academy Publishing Center to flag plagiarism, data fabrication, and unacknowledged AI-generated content.
5. Ensure Integrity of Graduate Research.
Apply vetting workflows for theses and dissertations to identify ghostwriting, manipulated data, or new forms of plagiarism.
6. Enhance Responsible Innovation in Research Practices.
Establish a research governance body to oversee ethical practices, transparency, reproducibility, and responsible integration of advanced technologies in research.
7. Promote Open Science and Transparency.
Promote open-science principles for research outputs while maintaining a flexible Intellectual Property framework to protect commercially viable innovations and sensitive data.