Dr Alexandru-Adrian Tantar leads the Trustworthy AI Research Group at the Luxembourg Institute of Science and Technology (LIST), since 2022, previously having been responsible for the Business Analytics Group. He received his PhD in Computer Science summa cum laude from the University of Lille I in 2009 and later completed MIT Sloan’s Executive Programme on Artificial Intelligence: Implications for Business Strategy.

Dr Tantar’s research portfolio ranges from leading AI benchmarking in the European Defence Fund’s STORE project to situational-awareness AI solutions for defence within the European Defence Agency’s 3D-4Land initiative. Dr Tantar helps shape Europe’s agenda on AI risk management via his involvement with EU’s General-Purpose AI Code of Practice, also representing Luxembourg in international and European standardisation bodies (ISO/IEC JTC 1/SC 42 & WG 13, CEN-CENELEC JTC 21). He co-founded and chaired the EVOLVE international conference series, hosted by leading universities and research centers in France, Mexico, the Netherlands, China, Romania, and Luxembourg. His keynote and executive-training engagements span academia, industry and the public sector, including addresses at Horton Conway’s (Princeton University) Doctor Honoris Causa ceremony, the European Lighthouse on Secure and Safe AI (ELSA), HEC Liège/LHoFT lecture series, AHK debelux, UMons InforTech’Days AI workshop, or the Institut Luxembourgeois des Administrateurs (ILA). In the private sector, Dr Tantar served as Vice-President for Research & Innovation at Black Swan Lux S.A., guiding the start-up to Luxembourg’s Healthcare Startup of the Year 2016 award, and a semi-finalist spot in Accenture’s global HealthTech London Innovation Challenge.

At LIST, his interdisciplinary team is focused on applied AI solutions for high-risk domains like finance, healthcare, defence, or in areas such as astrophotography. Among others, the Trustworthy AI team is involved with delivering a full-stack benchmarking and MLOps framework with built-in support for explainability and robustness, aligning to the EU AI Act.