About Me

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Hi and thanks for stopping by! My name is Dan Graur. I’m a Software Engineer in Google DeepMind where I work on Gemini Multimodality.

I also hold a PhD in Computer Science from ETH Zürich where I was part of the Systems Group under the mentorship of Prof. Gustavo Alonso and Prof. Ana Klimovic. My main research interests were in Systems for Machine Learning and Data Management.

During my PhD I interned three times in Google: (1) in Brain as part of the Flax team where I worked on a wrapper over Jax meant to ease Deep Learning research and development, (2) in TensorFlow as part of the tf.Data team where I worked on scalable and efficient ML data processing, and (3) as part of the Systems Research Group where I worked on generic, adaptive indexing methods for relational databases. Prior to the PhD, I obtained my MSc in Computer Science from TU Delft and ETH Zurich where I focused on Machine Learning and Distributed Systems. At TU Delft I had the pleasure of working with Prof. Jan Rellermeyer for my MSc thesis on gradient reduction methods in distributed ML training. During my time at TU Delft I worked as a Research Assistant as part of the Tribler research team. Prior to this, I obtained my BSc in Computer Science from the Technical University of Cluj-Napoca. See my resume for more details.

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:

Teaching

During my time at ETH Zürich I’ve helped teach the following courses:

Contact

Feel free to get in touch by sending me an email at hc.zhte.fni@ruarg.nad (copying the address won’t work well). Otherwise, you can reach me at the following address:

Dan Graur
STF G 222
Stampfenbachstrasse 114
8092 Zürich
Switzerland