I am a computer vision and machine learning engineer with over five years of experience developing real-world perception systems, with a background spanning both 2D and 3D vision, classical computer vision, and deep learning. I specialize in developing novel techniques for 3D perception in dynamic environments.

I completed my MSc in Computer Science from the University of Toronto (2018-2020), where I performed research on semi-supervised machine learning in computational genomics. From 2020 to 2022, I worked at DeepX, Inc., developing vision-based deep learning for scene comprehension in complex unstructured environments. Currently, at Sony Research since 2022, I focus on vision-based deep learning for deformable object perception and manipulation.

My general interests include:

  • 2D/3D Object Recognition: Accurately identifying and localizing objects in their environment.
  • 6-DoF Pose Estimation: Determining an object's precise position and orientation in 3D space.
  • Image Restoration and Super-Resolution: Developing deep learning models for image restoration and high-resolution scaling.

Contact

github; google scholar

academic:

rachelchan [at] cs [dot] toronto [dot] edu

personal:

rcwzychan [at] gmail [dot] com