Agustinus Kristiadi is a postdoctoral fellow at the Vector Institute, working primarily with Alán Aspuru-Guzik and Pascal Poupart. He obtained his PhD from the University of Tuebingen in Germany, advised by Philipp Hennig and Matthias Hein. His research interests are in probabilistic deep learning methods for uncertainty quantification, their Riemannian-geometric aspects, and their applications in broader science such as chemistry. His work has been recognized in the form of best PhD thesis award and multiple spotlight papers along with best reviewer award from top machine learning conferences. His contributions to the scientific society include mentoring underrepresented students in Canada under the IBET PhD Project and co-developing the Laplace-Torch open-source library, democratizing Bayesian neural networks to general audiences.