Latest move
Google DeepMind → destination not stated
Spent ten years at Google DeepMind, 2016 to October 2026, on graph neural networks, program synthesis, AlphaCode and then Gemini tool use and agents. First author of the AlphaCode paper. PhD from the University of Toronto, per the X bio.
Path
University of TorontoPhD, Computer Science2017- University of TorontoMSc, Computer Science2013
Google DeepMindResearch Scientist
Papers
- Competition-Level Code Generation with AlphaCodeScience 2022Describes AlphaCode, a system that generates many candidate programs for competitive programming problems and filters them by running them on test cases.
- Gated Graph Sequence Neural NetworksICLR 2016 2015Extends graph neural networks with gated recurrent updates so they can output sequences, tested on program verification tasks.
- Strong Generalization and Efficiency in Neural ProgramsarXiv 2020Trains neural models to learn algorithms such as sorting that keep working on inputs far larger than those seen in training.
SourcesLatest move: Xyujiali.github.ioEducation and jobs are read from their own homepage or employer's page; papers checked on arXiv. From LinkedIn only the person's own public posts are read; GitHub is a link only.