$$ \newcommand{\dint}{\mathrm{d}} \newcommand{\vphi}{\boldsymbol{\phi}} \newcommand{\vpi}{\boldsymbol{\pi}} \newcommand{\vpsi}{\boldsymbol{\psi}} \newcommand{\vomg}{\boldsymbol{\omega}} \newcommand{\vsigma}{\boldsymbol{\sigma}} \newcommand{\vzeta}{\boldsymbol{\zeta}} \renewcommand{\vx}{\mathbf{x}} \renewcommand{\vy}{\mathbf{y}} \renewcommand{\vz}{\mathbf{z}} \renewcommand{\vh}{\mathbf{h}} \renewcommand{\b}{\mathbf} \renewcommand{\vec}{\mathrm{vec}} \newcommand{\vecemph}{\mathrm{vec}} \newcommand{\mvn}{\mathcal{MN}} \newcommand{\G}{\mathcal{G}} \newcommand{\M}{\mathcal{M}} \newcommand{\N}{\mathcal{N}} \newcommand{\S}{\mathcal{S}} \newcommand{\I}{\mathcal{I}} \newcommand{\diag}[1]{\mathrm{diag}(#1)} \newcommand{\diagemph}[1]{\mathrm{diag}(#1)} \newcommand{\tr}[1]{\text{tr}(#1)} \renewcommand{\C}{\mathbb{C}} \renewcommand{\R}{\mathbb{R}} \renewcommand{\E}{\mathbb{E}} \newcommand{\D}{\mathcal{D}} \newcommand{\inner}[1]{\langle #1 \rangle} \newcommand{\innerbig}[1]{\left \langle #1 \right \rangle} \newcommand{\abs}[1]{\lvert #1 \rvert} \newcommand{\norm}[1]{\lVert #1 \rVert} \newcommand{\two}{\mathrm{II}} \newcommand{\GL}{\mathrm{GL}} \newcommand{\Id}{\mathrm{Id}} \newcommand{\grad}[1]{\mathrm{grad} \, #1} \newcommand{\gradat}[2]{\mathrm{grad} \, #1 \, \vert_{#2}} \newcommand{\Hess}[1]{\mathrm{Hess} \, #1} \newcommand{\T}{\text{T}} \newcommand{\dim}[1]{\mathrm{dim} \, #1} \newcommand{\partder}[2]{\frac{\partial #1}{\partial #2}} \newcommand{\rank}[1]{\mathrm{rank} \, #1} \newcommand{\inv}1 \newcommand{\map}{\text{MAP}} \newcommand{\L}{\mathcal{L}} \DeclareMathOperator*{\argmax}{arg\,max} \DeclareMathOperator*{\argmin}{arg\,min} $$

Agustinus's Portrait

Agustinus Kristiadi

Postdoc at the Vector Institute, Toronto

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.



Probabilistic deep learning
Riemannian geometry
AI for science


Vector Institute, Toronto

Postdoctoral Fellow, 2023-

University of Tübingen

Research Assistant, 2019-2023

University of Bonn

Part-Time Research Assistant, 2017-2019

Universitas Atma Jaya Yogyakarta

Research Assistant, 2016-2017


University of Tübingen, Germany

Ph.D., Computer Science, 2019-2023
Topic: Bayesian Deep Learning
Grade: Magna Cum Laude

University of Bonn, Germany

M.Sc., Computer Science, 2017-2019
Focus: Theoretical Computer Science, Intelligent Systems
Grade: 1.1 (3.9 GPA equivalent)

Universitas Atma Jaya Yogyakarta, Indonesia

B.Eng., Informatics Engineering, 2009-2013
Focus: Numerics, Soft Computing
Thesis: Parallel Particle Swarm Optimization for Image Segmentation
GPA: 3.9


Spotlight paper at NeurIPS 2023 (top 4%)
Spotlight paper at NeurIPS 2021 (top 3%)
Long-talk paper at UAI 2021 (top 6%)
Best reviewer at ICML 2021 (top 10%)


University of Tübingen

Madhav Iyengar, 2022
Philipp von Bachmann, 2021
Naman Deep Singh, 2021
Tobias Ludwig, 2020
Runa Eschenhagen, 2020
Marius Hobbhahn, 2019
Tutor, Numerics of Machine Learning, Winter Semester 2022-2023
Tutor, Data Literacy, Winter Semester 2021-2022
Tutor, Probabilistic Machine Learning, Summer Semester 2021
Tutor, Data Literacy, Winter Semester 2020-2021
Tutor, Probabilistic Machine Learning, Summer Semester 2020
Tutor, Data Literacy, Winter Semester 2019-2020

Universitas Atma Jaya Yogyakarta

Tutor, Advanced Data Structure, 2012
Tutor, Database, 2011


GDP Labs

Software Engineer, 2013-2015

Astra International

Software Engineering Intern, 2012


German (limited)