David Yue

I am currently a Ph.D. student in Computer Science at the University of Utah working in the Compiler Technology to Optimize Performance (CTOP) lab. My research interests lie in HPC/MLSys/Compilers. I am supervised by Dr. Mary Hall. Before that, I was a Machine Learning Research Engineer at Huawei and before that I was an undergraduate at the University of Toronto.

I graduated from the University of Toronto with a Honours Bachelor of Science - with Distinction doing a double major in Computer Science and Mathematics in June 2022.

• 📘 Blog
• 📑 Paper Reading List
• 📕 Cook Book
• 🌐 Vancouver Web Studio
• 👨🏻‍🏫 Tutoring

If you wish to contact me, going through email is usually best. I do not check other social platforms as often as I check my email. My email is listed at the bottom of the page.

My time at the University of Toronto was spent in their co-op program - having worked at companies like Shopify and Blackberry. I have also been a repeat Teaching Assistant for courses like

• Software Tools and Systems Programming
• Operating Systems
• Introduction to Numerical Algorithms for Computational Mathematics
• Computer and Network Security

and, of course, I also spent a great deal of time taking courses. I consider myself a Mathematician wannabe - I love the idea of doing mathematics, I lack the skill to perform. Like they say, mathematics is not a spectator sport, hence the "wannabe" qualifier.

Before joining the University of Toronto as an undergraduate, I attended Robert Alexander McMath Secondary School. I did very well in some classes like Math and Physics, wheareas other classes like English, Social Studies, or the second language class were neglected. If you were to put me back into high school today, I think results would be roughly the same.

This is Snoopie the Beagle! She was born on March 23rd 2023. Woof! Woof!

• Masrani, V., Yue, D., Rezaei, A. Akbari, M., & Zhang, Y. (2025). Task-Agnostic Language Model Watermarking via High Entropy Passthrough Layers. AAAI'25: Association for the Advancement of Artificial Intelligence, https://doi.org/10.48550/arXiv.2412.12563
• Ranjbar Alvar, S., Akbari, M., Yue, D., Chu, L., & Zhang, Y., (2025). AMUSE: Adaptive Multi-Segment Encoding for Dataset Watermarking. ICME' 25: IEEE International Conference on Multimedia & Expo 2025, https://doi.org/10.48550/arXiv.2403.05628
• Che, X., Akbari, M., Li, S., Yue, D., Zhang, Y., & Chu, L., (2024). Primary Key Free Watermarking for Numerical Dataset. ICPR '24: International Conference on Pattern Recognition https://doi.org/10.1007/978-3-031-78119-3_18
• Ranjbar Alvar, S., Akbari, M., Yue, D., & Zhang, Y. (2023). KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. https://doi.org/10.1145/3580305.3599876
• Harrington, B., Kulkarni, A., Ren, Z., Trinh, C., Gharadaghi, R., Amarouche, T., Aneel, A., Karki, A., Syed, S., & Yue, D. (2023). In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2 (SIGCSE 2023). Association for Computing Machinery, New York, NY, USA, 1342. https://doi.org/10.1145/3545947.3576288
• I try to keep this list up to date. But my Google Scholar probably will always be more accurate.

• Yue, D., Akbari, M., Che, X., Zhang, Y. (2023). Methods and Systems for Frequency Domain-based Tabular Data Watermarking (US20250131069A1)
• Ranjbar Alvar, S., Akbari, M., Yue, D., Zhang, Y. (2023) Methods and Systems for Watermarking Digital Data (US20250062911A1)
• Ranjbar Alvar, S. Akbari, M., Yue, D., Zhang, Y. (2023). Methods and Systems for Dataset Watermarking with Adaptive Multi-Segment Message Encoding