Ke SUN, PhD
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5/13 Garden St
Eveleigh NSW 2015
|Feb 2019||I am an outstanding reviewer of ICLR 2019.|
|2019||Reviewing: ICML 2019, IJCAI 2019, UAI 2019, NeurIPS 2019|
After childhood in Inner Mongolia, I went to Tsinghua University in Beijing, where I got a B.S. degree (2005) from department of computer science and technology and a M.S. degree (2007) from department of mathematical sciences. In the period 2006 to 2009, I discontinuously worked in IBM Research (China) as a part-time contractor (0.5 years) and Chinese University of Hong Kong as a research assistant (1.7 years). From late 2010 to 2015, I did a PhD in computer science in Département d'informatique, Université de Genève in Switzerland. From 2016 to 2017, I was a postdoc in École Polytechnique in Paris and then in King Abdullah University of Science and Technology in Saudi Arabia. Since late 2017 I am a principal research scientist in Data61 (former NICTA), Australia, working closely with the MLRG. In 2017 I received the "Prix de l'excellence de l'UNIGE" from University of Geneva. I have been reviewing for mainstream machine learning conferences (ICML, NeurIPS, etc.).
I study machine learning, a sub-discipline of artificial intelligence. My general interest lies in the spectrum of unsupervised learning, Bayesian statistical learning, manifold/metric learning, and deep learning. I formulate statistical learning problems from the perspective of information geometry (think of general relativity as the curvature of spacetime; information geometry is about the curvature of information), which tackles the essence of information using elegant mathematical tools. A goal of my research is to build a geometric theory of intelligence. I like simple and profound methodologies that are (anti-)intuitive, and therefore my works are more conceptual than practical. Recently I have been focusing on machine learning on graph-structured data. I do not give presentations with explicit rules to avoid equations.