Dan-Ovidiu Graur
Dan-Ovidiu Graur
Student / Programme Doctorate at D-INFK
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
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:
- Graur, D., Aymon, D., Kluser, D., Albrici, T., Thekkath, C. and Klimovic, A., Cachew: Machine Learning Input Data Processing as a Servicecall_made, 2022, Proceedings of the USENIX Annual Technical Conference (ATC)
- Graur, D., Müller I., Proffitt M., Fourny G., Watts G. T., and Alonso G., Evaluating Query Languages and Systems for High-Energy Physics Datacall_made, 2022, Proceedings of the VLDB Endowment
- Graur, D., Bruno, R. and Alonso, G., Specializing Generic Java Data Structurescall_made, 2021, 18th ACM International Conference on Managed Programming Languages & Runtimes
- Graur, D., Aymon, D., Thekkath, C. and Klimovic, A., Machine Learning Input Data Processing as a Service, 2021, EuroSys Doctoral Workshop 2021
- Graur, D., Bruno, R., Bischoff, J., Rieser, M., Scherr, W., Hoefler, T. and Alonso, G., Hermes: Enabling efficient large-scale simulation in MATSimcall_made, 2021, Procedia Computer Science, 184, pp.635-641
- Rellermeyer J. S., Khorasani S. O., Graur D. and Parthasarathy A., The Coming Age of Pervasive Data Processingcall_made, 2019, 18th International Symposium on Parallel and Distributed Computing (ISPDC), Amsterdam, 2019
- Graur D., Maris R. A., Potolea R., Dinsoreanu M. and Lemnaru C., Complex Localization in the Multiple Instance Learning Contextcall_made, 2018, New Frontiers in Mining Complex Patterns. Springer International Publishing, Cham, 93–106
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:
- Proffitt M., Müller I., Graur D., Adamec M., David P., Guiraud E., and Binet S., iris-hep/adl-benchmarksindex: ADL Functionality Benchmarks Indexcall_made. Version v0.1. 2021. DOI: 10.5281/zenodo.5131287call_made