I’m an AI Engineer and Computational Mathematics student at the University of Waterloo, with hands-on experience developing and optimizing deep learning systems at NVIDIA and in academic research. My background bridges both theoretical and applied machine learning, from designing adaptive neural decoding algorithms in Nengo to optimizing GPU-parallelized workloads in CUDA C++.
I’ve contributed to projects that span computer vision, generative AI, and educational tools, and I’m deeply passionate about leveraging AI to create meaningful, human-centered experiences, especially in learning and creativity. I take pride in writing clean, efficient, and scalable code, and I’m comfortable working across the full ML lifecycle: research, experimentation, model training, and deployment on cloud environments like AWS and GCP.
What sets me apart is my combination of research depth and engineering execution, I’m able to translate cutting-edge AI concepts into production-ready features that genuinely enhance user experience. I thrive in collaborative environments where innovation meets impact, and I’m excited about contributing to an AI-driven learning platform that empowers students worldwide.
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