cv

Member of Technical Staff

Backflip AI

Building generative AI systems for CAD, spanning distributed model training, agentic evaluation, and RL environment construction

Senior Machine Learning Engineer

Cruise

Built perception systems for autonomous vehicles

• Unblocked Cruise's return to driverless operation by leading Unified Tracker V2 model release that resolved critical ultra-nearfield risks (largest perception risk area)
• Contributed multiple modelling improvements to novel Unified Tracker V1 multi-modal, temporal tracking transformer model
• Increased model flop utilization by 32%, stabilized training by analyzing model activation magnitudes, and reduced velocity flips by 20%
• Created model attention metrics leading to 11% reduction in centroid error, 12% reduction in velocity error, and increased recall of pedestrians from 95.03% to 98.33%

Autonomous Systems Software Intern

Apple

Building on device ML inference infra for autonomous vehicles

• Contributed to machine learning compiler and inference framework, using C++ and Python
• Researched & prototyped DNN quantization & sparsification pipeline, resulting in up to 40% faster runtime of deployed models

Machine Learning Intern

Cognitive Systems

Developed ML models & inference tooling for WiFi based motion detectors

• Achieved 60x improvement in neural network inference runtime by implementing im2col convolutions, vectorization and memory alignment with Eigen in C++ for ARM CPU (exceeded Tensorflow Lite baseline by 2x)
• Researched & prototyped semi-supervised GAN data augmentation to reduce false positives

BMath

University of Waterloo

Combinatorics & Optimization and Computer Science (Double Major)

• Relevant Coursework: Advanced Algorithms, Algorithms, Operating Systems, Computer Vision, Mathematical Optimization (Convex & Linear Programming), Computational Discrete Optimization, Deep Learning in Computational Discrete Optimization (graduate level), Optimization for Machine Learning (graduate level)