Work Experience

  • DaoAI Robotics(C++,PCL,OpenCV,VTK): I led development on computer vision software to recognize objects and align them based on features extracted from 3D point cloud data. I learned a lot about 3D and projective geometry as well as C++ development!

  • Nanotechnology Research Centre (National Research Council)(LabVIEW,Python): I built an opto-electrical setup to measure the movement of a deformable mirror using lasers. I got to work with cool scientific equipment like atomic force microscopes, scanning electron microscope, and electron-beam evaporators!

  • eTreat Medical Diagnostics(MATLAB,Python): I took charge in researching and developing an algorithm to detect and classify acne using selfie photos, which was presented at SPIE Photonics West. This is where I first discovered the beauty of the Fourier transform!

Projects

  • Triton(C++,ROS/ROS2,OpenCV,Python): I’m a Project Lead working on software for UBC Subbot’s Triton AUV (autonomous underwater vehicle). Features I’ve worked on include VO (visual odometry) using KLT feature tracking, object recognition with YOLOv3, and real-time generation of simulated underwater images for use in our Gazebo simulation.

  • tree-opt(C++,Eigen): A C++ header-only library implementing the CARTopt algorithm for objective function optimization using CARTs (classification and regression trees).

  • Ultrasonic Gesture Recognition(Python,C++,PlatformIO): First capstone project. I wrote the software which interfaces a Python program running on a PC with embedded C++ running on a Teensy microcontroller. Our device was able to detect and classify simple gestures like swiping and tapping.

  • Hi-Lo Ren(C/Arduino): An autonomous robot that can navigate an obstacle course, rescue stuffed Ewoks, and save the galaxy from the Empire! Built for the annual UBC Engineering Physics robot competition, where it placed in the quarter-finals before a blown MOSFET ended its run.

Publications

  • Mohammad Amini, Fartash Vasefi, Manuel Valdebran, Kevin Huang, Haomiao Zhang, William Kemp, Nicholas MacKinnon, “Automated facial acne assessment from smartphone images,” Proc. SPIE 10497, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVI, 104970N (22 February 2018); doi: 10.1117/12.2292506; https://doi.org/10.1117/12.2292506