Dake Zhang

Hi, I’m a PhD candidate in Computer Science at the University of Waterloo, advised by Professor Mark D. Smucker and a member of the Data Systems Group.

My research focuses on trustworthy AI, with an emphasis on Retrieval-Augmented Generation (RAG). I collaborate closely with Professors Charles L. A. Clarke and Robin Cohen, whose expertise informs and strengthens my independent research. I’ve led large-scale community efforts (TREC 2024 Lateral Reading and TREC 2025 DRAGUN) and shipped production-level AI at Amazon, Microsoft, Huawei, and ByteDance.

I hold a Master’s in Computer Science from the University of Waterloo and a Bachelor’s in Software Engineering from Wuhan University.

News

Oct 01, 2025	Expected to graduate in 2026, I’m pursuing Applied Scientist and Research Scientist roles focused on building and evaluating reliable, user-aligned RAG/LLM systems at scale. Happy to connect!

Selected Publications

To Appear

Overview of the TREC 2025 DRAGUN Track

Dake Zhang, Mark D. Smucker, and Charles L. A. Clarke

In Text REtrieval Conference (TREC), 2025

Code Website

Unrefereed

Overview of the TREC 2024 Lateral Reading Track

Dake Zhang, Mark D. Smucker, and Charles L. A. Clarke

In Text REtrieval Conference (TREC), 2024

Bib PDF Data Website

@inproceedings{zhang2024overview,
  title = {Overview of the TREC 2024 Lateral Reading Track},
  author = {Zhang, Dake and Smucker, Mark D. and Clarke, Charles L. A.},
  booktitle = {Text REtrieval Conference (TREC)},
  year = {2024},
  data = {https://pages.nist.gov/trec-browser/trec33/lateral/data/}
}

Unrefereed
ReadProbe: A Demo of Retrieval-Enhanced Large Language Models to Support Lateral Reading

Dake Zhang, and Ronak Pradeep

In arXiv preprint arXiv:2306.07875, 2023

Hackathon Winner Bib PDF Code

First place at the 2023 Canadian #AI Misinformation Hackathon hosted by TMU Social Media Lab: https://socialmedialab.ca/events/hackathon/
@inproceedings{zhang2023readprobe, title = {ReadProbe: A Demo of Retrieval-Enhanced Large Language Models to Support Lateral Reading}, author = {Zhang, Dake and Pradeep, Ronak}, booktitle = {arXiv preprint arXiv:2306.07875}, year = {2023} }

Refereed Short

Learning Trustworthy Web Sources to Derive Correct Answers and Reduce Health Misinformation in Search

Dake Zhang, Amir Vakili Tahami, Mustafa Abualsaud, and Mark D. Smucker

In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 2022

DOI Bib PDF Code

@inproceedings{zhang2022learning,
  title = {Learning Trustworthy Web Sources to Derive Correct Answers and Reduce Health Misinformation in Search},
  author = {Zhang, Dake and Tahami, Amir Vakili and Abualsaud, Mustafa and Smucker, Mark D.},
  booktitle = {Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  year = {2022},
  isbn = {9781450387323},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3477495.3531812},
  doi = {10.1145/3477495.3531812},
  pages = {2099–2104},
  numpages = {6},
  location = {Madrid, Spain},
  series = {SIGIR '22}
}