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\begin{document}
\color{cvtext}
\cvname{Xinbao Qiao}
\contactline

\cvsection{Education}
\cvrowshortdate{\entrytitle{The Chinese University of Hong Kong}\hspace{5pt}\entrybodytight{Ph.D., Information Engineering. Advisor: \linkish{https://www.ie.cuhk.edu.hk/faculty/zhang-yingjun-angela/}{Angela Yingjun Zhang}.}}{\entryrighttight{Aug 2026\datesep{}present}}{}
\detail{Research Areas}{My research primarily studies lifecycle management of data in AI models, focusing on theoretical methods and practical problems that arise as data are generated, used, and deleted. My recent work aims to improve the reliability, interpretability, and controllability of AI models in heterogeneous, computation-constrained, and communication-constrained environments.}
\cvrow{\entrytitle{Zhejiang University}\hspace{5pt}\entrybody{M.Eng. in Artificial Intelligence. Advised by \linkish{https://person.zju.edu.cn/mengzhang}{Meng Zhang}.}}{\entryright{Zhejiang. Sep 2022 \datesep{} Dec 2025}}{}
\cvrow{\entrytitle{Shandong University}\hspace{5pt}\entrybody{B.Eng. in Communication Engineering.}}{\entryright{Shandong. Sep 2018 \datesep{} Jul 2022}}{}
\vspace{17.0pt}

\cvsection{Experience}
\cvrowstage{\entrytitle{Doctoral Research @ The Chinese University of Hong Kong}}{\entryright{Hong Kong. Aug 2026 \datesep{} present}}
\stagebrief{Investigates data lifecycle management in distributed AI across generation, use, deletion, and federated learning.}
\paperitem{Paper \#5}{Proposed optimal-transport federated learning with barycentric multi-prototype classification.}
\cvrowstage{\entrytitle{Research on Data-Centric ML Systems @ Zhejiang University}}{\entryright{Zhejiang. Mar 2023 \datesep{} Dec 2025}}
\stagebrief{Developed data-deletion methods for continuous influence control, certified online removal, and dynamic tree ensembles.}
\paperitem{Paper \#2}{Extended machine unlearning beyond binary erasure through continuous example weights, enabling targeted fairness and robustness interventions.}
\paperitem{Paper \#3}{Built Hessian-free online certified unlearning with recollected trajectory statistics, replacing explicit Hessian inversion for streaming deletion requests.}
\paperitem{Paper \#4}{Built exact dynamic random-forest unlearning through affected-tree updates, avoiding full retraining.}
\cvrowstage{\entrytitle{Research on Trustworthy LLM Systems @ NUSRI CQ}}{\entryright{Chongqing. Jun 2025 \datesep{} Dec 2025}}
\stagebrief{Analyzed LLM reliability failures caused by synthetic-data feedback loops and prompt patterns that trigger spurious inference.}
\paperitem{Paper \#1}{Showed how low-resource verification amplifies sample-selection bias in recursive synthetic-data training, persistently pruning tail data and precipitating model collapse.}
\paperitem{Paper \#6}{Linked illusory pattern perception to spurious LLM inference when perceived prompt patterns override evidence.}

\vspace{9.0pt}
\cvsection{Open-Source Contributions and Academic Service}
\vspace{6.6pt}
\servicerowicon{\iconlink{https://github.com/XinbaoQiao}{\icongithub{cvblue}}}{Research code releases}{public code for certified unlearning, soft-weighted unlearning, and model-collapse work.}
\servicerowicon{\iconlink{https://xinbaopedia.top/}{\iconhome{cvblue}}}{Xinbaopedia}{public academic homepage and wiki-style research archive with papers, figures, CV, and project notes.}
\servicerowicon{\iconscholar{cvblue}}{Academic service, 2026}{reviewer for ICML, NeurIPS, and AAAI.}
\servicerowicon{\iconscholar{cvblue}}{Academic service, 2025}{reviewer for NeurIPS, ICLR, AAAI, and IEEE TNNLS.}
\vspace{5.0pt}

\cvsection{Selected Publications}
\pubnote{Asterisks (*) denote co-first authorship; daggers (\textdagger) denote corresponding authors.}
\vspace{-5.0pt}
\setcounter{pubnum}{0}
\pubentry{When \red{Sample Selection Bias} Precipitates \red{Model Collapse}}
{\textbf{Xinbao Qiao}\corrauthor, Xianglong Du, Wei Liu, Jingqi Zhang, Peihua Mai, Meng Zhang\corrauthor, Yan Pang\corrauthor}
{Shows how low-resource verification turns selection bias into persistent tail pruning and model collapse.}
{\iconlink{https://openreview.net/forum?id=FFXvnzM254}{\iconopenreview{cvblue}}\plinksep\iconlink{https://arxiv.org/abs/2606.13732}{\iconarxiv{cvblue}}\plinksep\iconlink{https://github.com/XinbaoQiao/When-Sample-Selection-Bias-Precipitates-Model-Collapse}{\icongithub{cvblue}}}
{ICML 2026.}
\pubentry{Beyond Binary Erasure: \red{Soft-Weighted Unlearning} for Fairness and Robustness}
{\textbf{Xinbao Qiao}, Ningning Ding, Yushi Cheng, Meng Zhang\corrauthor}
{Generalizes binary deletion into continuous influence control for targeted fairness and robustness interventions.}
{\iconlink{https://arxiv.org/abs/2505.18783}{\iconarxiv{cvblue}}\plinksep\iconlink{https://ojs.aaai.org/index.php/AAAI/article/view/39681}{\iconpaperlink{cvblue}}}
{AAAI 2026.}
\pubentry{\red{Hessian-Free} Online Certified Unlearning}
{\textbf{Xinbao Qiao}, Meng Zhang\corrauthor, Ming Tang, Ermin Wei}
{Replaces explicit Hessian inversion with recollected trajectory statistics for scalable certified deletion.}
{\iconlink{https://openreview.net/forum?id=C3TrHWanh5}{\iconopenreview{cvblue}}\plinksep\iconlink{https://arxiv.org/abs/2404.01712}{\iconarxiv{cvblue}}\plinksep\iconlink{https://github.com/XinbaoQiao/Hessian-Free-Certified-Unlearning}{\icongithub{cvblue}}}
{ICLR 2025.}
\pubentry{\red{DynFrs}: An Efficient Framework for Machine Unlearning in Random Forest}
{Shurong Wang, Zhuoyang Shen, \textbf{Xinbao Qiao}, Tongning Zhang, Meng Zhang\corrauthor}
{Updates affected tree statistics to deliver exact random-forest unlearning in dynamic environments.}
{\iconlink{https://openreview.net/forum?id=nsCOeCLR8e}{\iconopenreview{cvblue}}\plinksep\iconlink{https://arxiv.org/abs/2410.01588}{\iconarxiv{cvblue}}\plinksep\iconlink{https://github.com/shurongwang/DynFrs}{\icongithub{cvblue}}}
{ICLR 2025.}
\pubentry{\red{Federated Learning as Optimal Transport}: Barycentric Multi-Prototype Classification}
{\textbf{Xinbao Qiao}, Wenjing Yan\corrauthor, Ying-Jun Angela Zhang}
{Frames federated learning as optimal transport with barycentric multi-prototype classification under communication constraints.}
{}
{Under review.}
\pubentry{\red{Illusory Pattern Perception} Drives Spurious Inference in Large Language Models}
{Peihua Mai, Zhuoyan Shao, \textbf{Xinbao Qiao}, Meng Zhang, Xinyue Zhou\corrauthor, Yan Pang\corrauthor}
{Links perceived prompt regularities to spurious LLM inference and interpretable failure behavior.}
{}
{Under review.}

\end{document}
