I am Machine Learning Engineer at Kindred AI working to build the wolrd’s first autonomous system for grocery fulfillment. In the past, I was a research student at University of Toronto, adviced by Dr. Jonathan Kelly where I had the opportunity to publish several papers in the field of Robotics and Artificial Intelligence. I am a receipient of the NSERC Canadian Graduate Scholarship and Vector Scholarship in AI.
I graduated from University of Waterloo with a bachelors in Mechatronics Engineering and an option in AI. I worked as a research assitant for Dr. Krzysztof Czarnecki, Dr. Mihaela Vlasea, and Dr. James Tung. For 12 months, I worked as an intern at Nvidia US where I contributed to their self-driving infrastructure. Through various co-ops and internships, I graduated with over 2 years of work experience.
Please checkout my projects and publications below.
MASc in Aerospace Engineering (Robotics), 2021
University of Toronto
BASc in Mechatronics Engineering, 2019
University of Waterloo
Worked in a team of 25 machine learning engineers, led by Dr. Urs Muller, creating an end-to-end autonomous driving solution. (Linux, C++, Git, Bash)
Worked on Nvidia’s DRIVE hardware stack, aiming to revolutionize the Automotive computing industry (C++, bash, python)
As a core member of the software development team, I worked closely with the R&D department to prototype a new application for their tool tracking system.
Completed as part of a graduate course at the University of Toronto | PyTorch. Implemented a Fully Connected Network based Road Segmentation pipeline on Audi’s A2D2 dataset using PyTorch and OpenCV.
Completed as part of a graduate course at the University of Toronto | Tensorflow, Python, OpenAI gym. Conducted a failure mode analysis on learned DDPG-based policies used to control a dexterous hand with tactile sensors, in an attempt to understand the utility of tactile information.
Completed as part of a graduate course at the University of Toronto | MATLAB. Simultaneous Localization and Mapping (SLAM) has been a highly research problem and the techniques that solve it have undergone huge improvements in the last two decades.