Research output per year
Research output per year
Personal profile
Biography
Dr Yanqiu (Autumn) Wu joined School of Computing at Macquarie University in January 2024 as a Lecturer in Artificial Intelligence (AI). Before she joined Macquarie University, Yanqiu was a CERC Postdoctoral Research Fellow at data61, CSIRO. Prior to that, Yanqiu received her PhD in Computer Science from New York University (NYU) and her B.S. degree (with Honors) from New York University Shanghai (NYUSH).
Her research interests include Markov Decision Processes, off-policy and off-line Deep Reinforcement Learning and Quantum Machine Learning with a focus on Quantum Adversarial Machine Learning. Her research works have been published in top conferences and journals such as ICML, NeurIPS and IMC. She served on program committee for SecTL 2023 and is a regular reviewer for prestigious venues, e.g., ICML, ICLR, NeurIPS and IJCAI.
Research interests
If you are interested in doing a PhD or MRes at Macquarie under my supervision, and are eligible to apply for any of the scholarships listed here, and please contact me in advance of the closing dates.
Teaching
COMP8221 Advanced Machine Learning
Education/Academic qualification
Computer Science, PhD, New York University
1 Sept 2017 → 26 Sept 2022
Award Date: 26 Sept 2022
Computer Science, Bachelor, New York University Shanghai
1 Sept 2013 → 27 May 2017
Award Date: 27 May 2017
Fingerprint
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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A survey of progress in LLM alignment from the perspective of reward design
Ji, M., Wu, Y., Wu, Z., Wang, S., Yang, J., Dras, M. & Naseem, U., Jul 2026, In: IEEE Transactions on Artificial Intelligence. 7, 7, p. 3688-3702 15 p.Research output: Contribution to journal › Review article › peer-review
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Quantum-Inspired Machine Learning: a survey
Huynh, L., Hong, J., Mian, A., Suzuki, H., Wu, Y. & Camtepe, S., 22 Aug 2023, (Submitted) (arXiv).Research output: Working paper › Preprint
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Radio signal classification by adversarially robust quantum machine learning
Wu, Y., Adermann, E., Thapa, C., Camtepe, S., Suzuki, H. & Usman, M., 13 Dec 2023, (Submitted) ( arXiv).Research output: Working paper › Preprint
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Aggressive Q-learning with ensembles: achieving both high sample efficiency and high asymptotic performance
Wu, Y., Chen, X., Wang, C., Zhang, Y. & Ross, K., 2022, (Accepted/In press) Deep Reinforcement Learning Workshop NeurIPS 2022.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
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Spatio-temporal incentives optimization for ride-hailing services with offline deep reinforcement learning
Wu, Y., Li, Q. & Qin, Z. T., 6 Nov 2022, (Submitted) (arXiv).Research output: Working paper › Preprint
Activities
- 8 Publication Peer-review
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40th International Conference on Machine Learning, ICML 2023 (Event)
Wu, Y. (Reviewer)
2023Activity: Peer-review and editorial of research outputs › Publication Peer-review
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The 2023 ACM Web Conference (Event)
Wu, Y. (Reviewer)
2023Activity: Peer-review and editorial of research outputs › Publication Peer-review
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28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2022 (Event)
Wu, Y. (Reviewer)
2022Activity: Peer-review and editorial of research outputs › Publication Peer-review
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36th Conference on Neural Information Processing Systems, NeurIPS 2022 (Event)
Wu, Y. (Reviewer)
2022Activity: Peer-review and editorial of research outputs › Publication Peer-review
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38th International Conference on Machine Learning, ICML 2021 (Event)
Wu, Y. (Reviewer)
2021Activity: Peer-review and editorial of research outputs › Publication Peer-review