Bio


Abdoul Jalil Djiberou Mahamadou, PhD is a Postdoctoral Fellow at the Center for Biomedical Ethics working on the identification of ethical, social, and legal considerations arising in the context of AI and the drug discovery and development process in partnership with GSK.ai. Part of his current work focuses on developing new techniques to account for unobserved variables such as cultural factors in algorithmic fairness under changing environments. Prior to his appointment at Stanford, Dr. Djiberou completed a Mitacs Industrial Postdoctoral Fellowship at Simon Fraser University where he worked on the identification of lifestyle factors contributing to successful cognitive aging in older adults’ population using Machine Learning techniques. He holds a Ph.D. and an M.Sc. in Computer Science and an M.Eng. in Applied Mathematics from Université Clermont Auvergne, and a B.Sc. in Applied Mathematics from Sidi Mohamed Ben Abdellah University. His Ph.D. dissertation focused on the development of new unsupervised machine learning models and their applications to health data mining. In 2019, Dr. Djiberou was named the best Nigerien student in France based on academic performance by the Réseau des Etudiants Nigériens de France.

Honors & Awards


  • Mitacs Accelerate Industrial Posdoctoral Fellow Grant, Mitacs (2022)
  • Start-up funding, eTakara Niger and IsDB (2019, 2021)
  • Best Nigerien Student in France, Réseau des Etudiants Nigériens de France (2019)
  • Ph.D. Funding, French National Agency of Research (2018)

Professional Education


  • Doctor of Philosophy, Universite De Clermont (2021)
  • Master of Science, Universite De Clermont (2019)
  • Engineer, Universite De Clermont (2018)
  • Ph.D., Clermont Auvergne University, Computer Science (2021)
  • M.Sc, Clermont Auvergne University, Computer Science (2018)
  • M.Eng, Clermont Auvergne University, Applied Mathematics (2018)
  • B.Sc, Sidi Mohamaed Ben Abdellah University, Applied Mathematics (2015)

Stanford Advisors


Current Research and Scholarly Interests


Identify ethical, legal, and social considerations arising in the context of AI in the drug discovery process.