Ke Sun (Preferred)
Ke Sun
CSIRO's Data61 and Australian National University
Names
How do you usually write your name as author of a paper? Also add any other names you have authored papers under.
Emails
Enter email addresses associated with all of your current and historical institutional affiliations, as well as all your previous publications, and the Toronto Paper Matching System. This information is crucial for deduplicating users, and ensuring you see your reviewing assignments.
****@gmail.com
, ****@ieee.org
, ****@data61.csiro.au
Personal Links
Add links to your profiles on other sites. (Optional)
Education & Career History
Enter your education and career history. The institution domain is used for conflict of interest detection and institution ranking. For ongoing positions, leave the end field blank.
Researcher
CSIRO's Data61 and Australian National University (anu.edu.au)
2021 – Present
Researcher
CSIRO's Data61 (csiro.au)
2017 – Present
Postdoc
King Abdullah University of Science and Technology (kaust.edu.sa)
2016 – 2017
Postdoc
Ecole polytechnique (polytechnique.edu)
2016 – 2016
PhD student
University of Geneva (unige.ch)
2010 – 2015
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Coauthor
Marcel Keller
****@data61.csiro.au
2019 – Present
Coauthor
Pitor Koniusz
****@data61.csiro.au
2018 – Present
Coauthor
Richard Nock
****@data61.csiro.au
2017 – Present
Coauthor
Frank Nielsen
****@lix.polytechnique.fr
2016 – Present
Postdoc Advisor
Xiangliang Zhang
****@kaust.edu.sa
2016 – 2017
Coauthor
Alexandros Kalousis
****@hesge.ch
2013 – 2015
PhD Advisor
Stephane Marchand-Maillet
****@unige.ch
2010 – 2015
Expertise
For each line, enter comma-separated keyphrases representing an intersection of your interests. Think of each line as a query for papers in which you would have expertise and interest. For example: deep learning, RNNs, dependency parsing
Graph neural networks
Present
Deep learning
Present
Dimensionality reduction
Present
Manifold learning
Present
Machine learning
Present
Information geometry
Present
Optimization
Present
Riemannian geometry
Present