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

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

Selected Publications

Resources for Automated Evaluation of Assistive RAG Systems that Help Readers with News Trustworthiness Assessment

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

In Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2026

Bib PDF Code

@inproceedings{zhang2026resources,
  title = {Resources for Automated Evaluation of Assistive RAG Systems that Help Readers with News Trustworthiness Assessment},
  author = {Zhang, Dake and Smucker, Mark D. and Clarke, Charles L. A.},
  booktitle = {Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  year = {2026},
  eprint = {2602.24277},
  archiveprefix = {arXiv},
  primaryclass = {cs.IR},
  url = {https://arxiv.org/abs/2602.24277},
}

Simulating the Lateral Reader for News Trustworthiness Reports with an Iterative Multi-Agent RAG System

Dake Zhang, and Mark D. Smucker

In Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2026

Bib PDF Code

@inproceedings{zhang2025baseline,
  title = {Simulating the Lateral Reader for News Trustworthiness Reports with an Iterative Multi-Agent RAG System},
  author = {Zhang, Dake and Smucker, Mark D.},
  booktitle = {Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  year = {2026},
}

Overview of the TREC 2025 DRAGUN Track: Detection, Retrieval, and Augmented Generation for Understanding News

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

In Text REtrieval Conference (TREC), 2025

Bib PDF Code Website

@inproceedings{zhang2025overview,
  title = {Overview of the TREC 2025 DRAGUN Track: Detection, Retrieval, and Augmented Generation for Understanding News},
  author = {Zhang, Dake and Smucker, Mark D. and Clarke, Charles L. A.},
  booktitle = {Text REtrieval Conference (TREC)},
  year = {2025},
}

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/}
}

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} }