I am a software engineer and researcher at Lorica Cybersecurity, where I design, implement, and deploy state-of-the-art privacy-preserving machine learning (ML) products. I have over five years of experience in the ML space, with a focus on privacy-enhancing technologies such as fully homomorphic encryption (FHE). I have a Master of Applied Science (MASc) degree in Electrical and Computer Engineering (ECE) at the University of Toronto, where I conducted individual research on enabling large-scale privacy-preserving attention-enabled recurrent neural networks with FHE. My thesis has been published at https://hdl.handle.net/1807/130355. I presented my thesis work at the International Cryptography Module Conference (ICMC) in 2023.My goal is to protect the privacy of all actors within ML applications, such as users and model-owners, and to contribute to the development of innovative and secure solutions for various domains and applications. I am passionate about learning new technologies and skills, and sharing my knowledge and experience with others. Ask me about my musical alter-ego!