My name is Andrei Bârsan, and I’m a Computer Science PhD Student at the University of Toronto, focusing on deep learning for autonomous robotics. I started in September 2017, under the supervision of Professor Raquel Urtasun.

In parallel to this, I am also a full-time researcher at Uber Advanced Technologies Group (ATG) Toronto, working on applying my research to the challenges associated with autonomous driving in the real world.

Before starting my PhD, I completed my Master’s in Computer Science at ETH Zurich, also focusing on deep learning and computer vision, together with their applications in robotics, specifically autonomous vehicles. For my Master’s Thesis, I developed DynSLAM, a dense mapping system capable of simultaneously reconstructing dynamic and potentially dynamic objects encountered in an environment, in addition to the background map, using just stereo input. More details can be found on the DynSLAM project page.

Previously, while doing my Undergraduate at Transilvania University, in Brașov, Romania, I interned at Microsoft (2013, Redmond, WA), Google (2014, New York, NY) and Twitter (2015, San Francisco, CA), working on projects related to privacy, data protection, and data pipeline engineering.

Email me at

Find me on GitHub, StackOverflow, Twitter or LinkedIn.

My side projects include:

  • MetalNet, a small toolkit for scraping and processing metal lyrics, followed by training a language model to generate its own metal. (Source code and blog post coming soon™!)
  • Yeti, an OpenGL 3D game engine with forward and deferred rendering support, real time shadow mapping and more
  • µShell, an experimental, simple, lightweight, free POSIX shell implementation written in C++