• Engineer

Rachel Chan

I received my MSc in March 2020, from the Department of Computer Science at the University of Toronto. During my masters, I performed research on semi-supervised genome annotation using epigenetic data. I primarily focussed on probabilistic models, but studied deep learning and statistical learning theory as well. Prior to this, I received my BASc in 2018 from the Engineering Physics program at the University of British Columbia, with a specialization in pure/applied mathematics. In this program, I studied a wide range of topics within electrical (eg. embedded systems, control theory) and mechanical engineering, maths (eg. PDEs, real/complex analysis, chaos, differential geometry), and physics (eg. statistical mechanics, optics, quantum and EM theory).


Through my studies, I have always wanted to work on issues which have tangible impact on the betterment of human society. I joined DeepX because I believe the goal to “automate any machine using artificial intelligence” is a vital and important mission for both human society today and in the future. This is because the labor shortage faced by Japan due to declining birthrate is not unique to Japan. It is a global problem that will require new technology to solve. And it is clear that automation using artificial intelligence is one of the most promising strategies to relieve this issue. As the pace of research and development of machine learning systems grows faster and faster with every passing year, it seems that now is the perfect time to seize the momentum of this movement to bridge the gap between theoretical research and practical application of these systems on real machines. Though technically challenging, this type of research and development will allow artificial intelligence to be applied to all manner of machines and minimize human involvement in dull, dirty, and dangerous tasks. Through my work at DeepX, I hope to be part of such a revolutionary development.



  • Application of machine learning to real-world physical systems
  • Design of robotic systems and control
  • Computer vision


  • I began studying piano and violin at a fairly young age. Even though I don’t play very much anymore (and am not very good), I still enjoy the sense of teamwork that comes with playing with others. I participated in a university community orchestra during my masters and would eagerly do it again.

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