Awa Dieng

Hi! I am a research associate on the Google Brain team in Montreal and a graduate student in Computer Science at Mila and Université de Montréal co-advised by Laurent Charlin and Hugo Larochelle. I am also the initiator and co-organizer of the Algorithmic Fairness through the lens... workshop series at NeurIPS (

My research interest is at the intersection of machine learning and causality with a focus on improving fairness, interpretability and reliability properties of ML models and treatment effect estimation methods.

contact: awaydieng {at} gmail {dot} com | google scholar | twitter


  • Excited to organize a 3rd edition of our workshop on Algorithmic Fairness at NeurIPS 2022 (details at Algorithmic Fairness through the lens of Causality and Privacy)!

  • I am Program Chair for the Montreal AI Symposium 2022. Looking forward to helping organize this great conference!

  • Honoured to be invited to participate in the Interpretable Machine Learning program at the Simons Institute for the Theory of Computing, UC Berkeley this summer.

  • The proceedings at PMLR for the Algorithmic Fairness through the lens of Causality and Robustness workshop is out!

  • New review paper on transportability of causal effects using RCT and observational data!

  • Excited to co-organize a second edition of the AFCI workshop at NeurIPS 2021. This year's edition will highlight work at the intersection of fairness with causality and robustness. More information at

  • Joined the SAMSI (Statistical and Applied Mathematical Sciences Institute) working group on Causal Inference and Missing Data!!

  • I am co-organizing a workshop on "Algorithmic Fairness through the lens of Causality and Interpretability " at NeurIPS 2020. Check for more details.

  • I am happy to share my "Path to Google" interview with the Google blog.

  • Joined the first cohort of AI residents in the Google Brain team in Accra, Ghana!

Publications: see google scholar