Thomas Doms
Papers
1
Total Citations
24
H-Index
1
About
Thomas Doms is a leading voice at the intersection of artificial intelligence and regulatory trust, focusing on the critical challenge of certifying machine learning applications. His seminal work, "Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications" (2021), which has garnered 24 citations, lays the foundational framework for ensuring that AI systems are not only powerful but also reliable, transparent, and ethically sound. Doms’ major contribution lies in bridging the gap between rapid technological advancement and the societal need for accountability, proposing concrete pathways for auditing and validating AI behavior. By addressing the core tension between innovation and public acceptance, his research provides essential guidelines for developers, policymakers, and regulators. This work is particularly notable for its forward-looking approach, anticipating the growing demand for standardized certification processes in an era where AI permeates daily life. Doms’ insights are pivotal for students and researchers seeking to build AI that earns genuine societal trust, making him a key architect of responsible AI governance.
Research Focus
Key Achievements
Top Papers
- 1