Summary
Sherman Siu is an MMath (CS) student at the University of Waterloo with a decade of hands-on experience building and shipping deep learning systems across industry leaders including Apple, Huawei, and Abnormal Security. He focuses on transformer-based LLMs, computer vision, NLP, and reinforcement learning, with practical achievements ranging from improving speech recognition WER via novel relative position embeddings to boosting text-model accuracy and robustness in production settings. Sherman pairs strong research instincts with production engineering—designing deployment pipelines, automated retraining DAGs, and explainability tools (SHAP/LIME)—and has led end-to-end projects from data prep to executive demos. A Waterloo BMath graduate with minors in statistics and combinatorics & optimization (graduated with distinction), he brings both mathematical rigor and product-minded delivery to applied ML problems. An unspoken strength is his fluency across the stack—cloud orchestration, APIs, and front-end demos—enabling research prototypes to reach users.
10 years of coding experience
2 years of employment as a software developer
Marc Garneau Collegiate Institute
Master's of Mathematics in Computer Science, Deep Learning, Master's of Mathematics in Computer Science, Deep Learning at University of Waterloo