Experienceedit
Research experience and affiliations.
Current affiliationedit
- PhD student, Department of Information Engineering, The Chinese University of Hong Kong, advised by Angela Yingjun Zhang.
Doctoral research in AI and networksedit
PhD student, 2026-present. Advisor: Angela Yingjun Zhang, The Chinese University of Hong Kong.
Qiao's current doctoral work is centered on data-centric ML and AI and networks, including AI for Networks and Networks for AI. The research asks how learning systems should operate when data, computation, and evaluation signals are distributed across clients, institutions, or networked infrastructure. Distributed Wasserstein barycenter computation remains one related method for constructing shared distributional references without assuming that all raw data can be pooled.
Related pages: AI and Networks, Distributed Learning, Wasserstein Geometry, Distributed Wasserstein Barycenter, and Collaborative Evaluation.
Research on data-centric ML systemsedit
M.Eng. / master's research student, 2023-03 to 2025-12. Advisor: Meng Zhang, Zhejiang University.
This line of work developed theoretically grounded approaches for data influence attribution, machine unlearning, and data-centric trade-offs in trustworthy AI. It also included cloud-edge collaborative human-space healthcare, where multimodal video, audio, and sensor signals were considered for real-time monitoring.
Related pages: Machine Unlearning, Influence Functions, Certified Data Removal, Trustworthy AI, and Data Centric ML.
Research on trustworthy LLM systemsedit
Full-time research intern, 2025-06 to 2025-12. Advisor: Pang Yan, James, NUSRI CQ.
This research line studies trustworthy model behavior and synthetic-data evaluation, including distributed Wasserstein methods for low-resource synthetic-data evaluation when real data are limited or fragmented.
Related pages: LLM Reliability, Synthetic Data, and Wasserstein Geometry.