About

I am an incoming PhD student in AI of Health & Life Science at City University of Hong Kong (Sept 2026 – Jun 2030), supervised by Prof. Jun Yan. I am currently a Research Assistant at HKAI-Sci and have completed my MSc in Data Science at CityU.

Research focus

  • AI for health & life sciences — trustworthy AI systems for clinical data, biomedical discovery, and health decision support.
  • Medical large language models — privacy-preserving EHR transformation, clinical text generation, and knowledge-grounded reasoning.
  • Medical knowledge graphs — multi-relational knowledge graph refinement for robust prediction and biomedical reasoning.
  • AI safety — safety, uncertainty, robustness, and efficient model collaboration in LLM systems.

PhD advisor: Prof. Jun YAN. Current collaborators and advisors: Prof. Maolin WANG, Senior Engineer Yao WANG.

Before this, I had the privilege of being mentored by Prof. Xiangyu ZHAO in the Department of Data Science at City University of Hong Kong.

News

Received a CityU PhD offer in AI of Health & Life Science, supervised by Prof. Jun Yan.

A Serial Two-Stage Framework accepted at ACM SIGKDD 2026 (CCF-A).

Joined HKAI-Sci as a Research Assistant (AI for Science), supervised by Prof. Jun Yan.

GRAND accepted at TheWebConf 2026 (Web4Good, CCF-A). Privacy-preserving EHR work available on arXiv:2603.22954.

SIGIR 2026 (Perspectives Track): “Rethinking Semantic–Collaborative Integration” — accepted (in production).

Education

PhD in AI of Health & Life Science

City University of Hong Kong · Sept 2026 – Jun 2030 (expected)

Incoming PhD student. Advisor: Prof. Jun Yan.

MSc in Data Science

City University of Hong Kong · Aug 2025 – Jun 2026

Graduated with distinction (First Class Honours). Research training in data science, AI for Science, medical AI, and reproducible machine learning.

Bachelor's in Business Studies

Lancaster University

Training in analytics, business research, and data-driven decision making.

Experience

Research Assistant, AI for Science

HKAI-Sci, City University of Hong Kong · Jan 2026 – Present

AI-for-Science with emphasis on health and life sciences, including medical LLMs, privacy-preserving clinical data, medical knowledge graphs, and AI safety. Model implementation, experiments, and support for paper writing and reproducible code. (Supervisor: Prof. Jun Yan.)

Large Language Model Intern

Tencent (WeChat Search / Hunyuan) · Dec 2024 – Mar 2025 · Beijing, China

Text preprocessing for medical/legal documents; prompt and synthetic-data pipelines; improved retrieval efficiency and labeling consistency.

Data Operations Intern

Joy Media · Jul 2023 – Sept 2023 · Hangzhou, China

KOL live-stream and short-video analytics; benchmarking and competitive analysis to guide content strategy and operations.

Data Research Intern

Beijing International Big Data Exchange Co., Ltd. · Aug 2022 – Sept 2022

Industry and competitor research; data-driven reports for product planning and marketing strategy.

Publications

Published & accepted

Conference

A Serial Two-Stage Framework for Robust Multimodal Fake News Detection via Adaptive Reasoning

Maolin Wang, Ziting Mai, Zichun Liu, Beining Bao*, Hongyu Chen, Junjie Liu, Yunbo Zhang, Bingkun Zhao, Tianshuo Wei, Jian Liu, Chenbin Zhang, Haoran Yang

ACM SIGKDD 2026, CCF-A, accepted.

DOI

Conference

GRAND: A Robust Diffusion Framework for Multi-Granularity Graph Anomaly Detection in Web Platforms

Maolin Wang, Beining Bao*, Hongyu Chen, Zichun Liu, Lang Fu, Jun Chu, Langzhang Liang, Zenglin Xu

The ACM Web Conference 2026 (TheWebConf 2026), Web4Good Track, CCF-A, accepted.

DOI

Preprint

Privacy-Preserving EHR Data Transformation via Geometric Operators: A Human–AI Co-Design Technical Report

Maolin Wang†, Beining Bao*†, Gan Yuan, Hongyu Chen, Bingkun Zhao, Baoshuo Kan, Jiming Xu, Qi Shi, Yinggong Zhao, Yao Wang, Wei-Ying Ma, Jun Yan

arXiv preprint arXiv:2603.22954, 2026.

arXiv

Conference

Rethinking Semantic–Collaborative Integration: Why Alignment Is Not Enough

Maolin Wang, Dongze Wu, Jianing Zhou, Hongyu Chen, Beining Bao*, Yu Jiang, Chenbin Zhang, Chang Wang, Jian Liu, Lei Sha

ACM SIGIR 2026, Perspectives Paper Track, CCF-A, accepted.

arXiv

Conference

Housing Rental Information Management and Prediction System Based on CatBoost Algorithm — A Case Study of Halifax Region

Shuangrun Shao, Bingxi Zhao, Xiangen Cui, Yihong Dai, Beining Bao*

Rough Sets (LNCS, Vol. 14840, Springer), IJCRS 2024, CCF-B, accepted.

Conference

Deep Tensor Factorization for Modeling Non-Uniform Temporal Dynamics with Adaptive Temporal Smoothing

Hongyu Chen, Beining Bao*, Zichun Liu, Tianshuo Wei, Maolin Wang, Xiaopeng Li, Hing Cheung So

IEEE Statistical Signal Processing Workshop (IEEE SAM 2026), accepted for presentation, Shenzhen, China, Jul 13–16, 2026.

Conference

Projects & honours

Housing Rental Information Management & Prediction (Halifax)

Jul 2024 · IJCRS 2024 conference paper · Third place, IJCRS data mining competition

CatBoost + Tableau system for rental information management and prediction; interactive dashboards for non-expert users.

Intelligent Elderly Care Matching Platform (YangLaoTong)

Nov 2024 – May 2025

Fuzzy matching, TF-IDF, and CatBoost over 26,000+ nursing homes (Gaode Map API); IBM Watson dialogue for health risk assessment; 2,086 questionnaires with NLP-driven rule refinement.

Honours

Third place, IJCRS International Data Mining Competition final (2024); Best Project Award, MSc in Data Science (2026); Excellence Award, National College Student Data Analysis Popular Science Knowledge Competition (Oct 2023).

Skills

Python PyTorch scikit-learn CatBoost Transformers Graph ML Medical LLMs Medical knowledge graphs AI safety LLM prompting & data generation Reproducible pipelines