Pengqian Lu

Pengqian Lu A friendly man. Ph.D. Student Australian Artificial Intelligence Institute (AAII) University of Technology Sydney 📧 pengqian.lu@foxmail.com GitHub | LinkedIn | Blog

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About Me

Aloha! I am a Ph.D. student at the University of Technology Sydney (UTS), under the supervision of Prof. Jie Lu. I am conducting my research at the Australian Artificial Intelligence Institute (AAII), a world-leading research institute in artificial intelligence.

Previously, I obtained my Master of Philosophy (M.Phil.) degree from the University of Sydney, where I was supervised by Dr. Tongliang Liu.

My primary research interests include:

• Learning with Concept Drift
• LLM Hallucination Detection
• Learning with Label Noise

Outside of academia, I enjoy reading historical books, solving challenges, and chatting with interesting people.

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🎓 Education

• University of Technology Sydney
  • Doctor of Philosophy in Computer Science
  • September 2022 - Present
• The University of Sydney
  • Master of Philosophy in Computer Science
  • March 2021 - September 2022
• Hangzhou Dianzi Univeristy
  • Master’s Degree in Computer Science
  • September 2017 - June 2020
  • Dropped
• Hangzhou Dianzi University
  • Bachelor’s Degree in Computer Science
  • September 2013 - June 2017

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🏆 Honors & Awards

• 2022: ARC Discovery Project Scholarship
• 2022: International Research Scholarship
• 2021: Postgraduate Research Scholarship in Robust Graph Learning
• 2018: National Scholarship for Postgraduates
• 2018: Huawei Scholarship for Postgraduates

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📝 Publications

1. Lu, P., Lu, J., Liu, A., & Zhang, G. (2025). Early concept drift detection via prediction uncertainty. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 39, No. 18, pp. 19124-19132). [PDF] [CODE] AAAI, CCF-A, CORE Ranking A*
2. Zhou, M., Lu, J., Lu, P., & Zhang, G. (2024). Dynamic graph regularization for multi-stream concept drift self-adaptation. IEEE Transactions on Knowledge and Data Engineering, 36(11), 6016-28. TKDE, CCF-A, CORE Ranking A*
3. Xia, X., Lu, P., Gong, C., Han, B., Yu, J., & Liu, T. (2023). Regularly truncated m-estimators for learning with noisy labels. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(5), 3522-3536. [PDF][CODE] TPAMI, CCF-A, CORE Ranking A*, Co-first author
4. Li, Z., Zhang, J., Gan, J., Lu, P., Gao, Z., & Kong, W. (2019). Large-scale trip planning for bike-sharing systems. Pervasive and Mobile Computing, 54, 16-28.
5. Lu, P., Zhang, J., Zheng, S., & Zhang, T. (2019). Local ratio based distributed bike-dock pair allocation in public bike system. In Proceedings of the ACM Turing Celebration Conference-China (pp. 1-5).
6. Zhang, J., Lu, P., Li, Z., & Gan, J. (2018). Distributed trip selection game for public bike system with crowdsourcing. In IEEE INFOCOM 2018-IEEE Conference on Computer Communications (pp. 2717-2725). IEEE. INFOCOM, CCF-A, CORE Ranking A*

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_{Page maintained by Pengqian Lu. Last updated: August 2025.}