Celestine Dünner originally joined the IBM Research – Zurich Laboratory in 2014 as a student intern and member of the Non-volatile Memory Systems group. Her research focused on modeling the threshold voltage signals from MLC NAND flash memory devices based on experimental data.
Since August 2015, Celestine has been a predoctoral researcher in the Analytics infrastructure group at IBM Research – Zurich and a PhD candidate in Computer Science at the Swiss Federal Institute of Technology (ETH), where she is a member of the ETH data analytics laboratory led by professor Thomas Hofmann. Her current reseach interest is optimization and large-scale machine learning with a vision to improve the interface between system and algorithm design for machine learning applications in order to improve the overall scalability and efficiency of learning algorithms.
Celestine received her Bachelor’s and Master’s degrees in Electrical Engineering and Information Technology from ETH Zurich in 2012 and 2015, respectively.