Dan-Ovidiu Graur

Dan-Ovidiu Graur

Dan-Ovidiu Graur

Student / Programme Doctorate at D-INFK

ETH Zürich

Professur für Informatik

STF G 222

Stampfenbachstrasse 114

8092 Zürich

Switzerland

Additional information

Research area

Systems for Machine Learning and Databases

Below is a brief overview of my CV. For full details please download my full CV on this page, or see my personal website.

Professional Experience

  • Nov. 2019 - present: Research Assistant @ ETH Zurich
  • Jun. 2022 - Sep. 2022: Research Intern @ Google
  • Jun. 2020 - Sep. 2020: SWE Intern @ Google
  • Apr. 2018 - Oct. 2019: Research Assistant @ TU Delft
  • Nov. 2016 - Jun. 2017: Student Researcher @ Technical University of Cluj-Napoca
  • Jul. 2016 - Aug. 2016: Intern @ Telenav Software

Education

  • 2019 - present: Doctor of Sciences @ ETH Zurich
  • 2017 - 2019: MSc in Computer Science @ ETH Zurich & TU Delft
  • 2013 - 2017: BSc in Computer Science @ Technical University of Cluj-Napoca
CV PDF

Additional information

Hi! My name is Dan Graur. I’m currently a 3rd year PhD Student in Computer Science at ETH Zürich as part of the Systems Group where I have the good fortune of being supervised by Prof. Gustavo Alonso and Prof. Ana Klimovic. My main research interests lie in Systems for Machine Learning and Database and Data Analytics Systems.

 

During my PhD I interned twice in Google: (1) in Braincall_made as part of the Flax teamcall_made, and (2) in TensorFlowcall_made as part of the tf.Data teamcall_made. Prior to the PhD, I obtained my MSc in Computer Science from TU Delftcall_made and ETH Zurich. At TU Delft I had the pleasure of working with Prof. Jan Rellermeyercall_made for my MSc thesis. During my time at TU Delft I worked as a Research Assistant as part of the Tribler research teamcall_made. Prior to this, I obtained my BSc in Computer Science from the Technical University of Cluj-Napocacall_made.

Research

This is a list of the research papers I’ve published so far:

Other Contributions

I’ve also helped develop and improve the ADL Functionality Benchmarks Index, a benchmark dedicated to bridging the gap between the High-Energy Physics and the Database communities in terms of Query Languages and Database Engines:

JavaScript has been disabled in your browser