Zhuhan Bao
Visiting Scholar @ Duke-NUS Medical School
Hi! I'm Zhuhan Bao (鲍竹涵), a junior undergraduate majoring in Software Engineering at Hangzhou City University. I am currently a Visiting Scholar at Duke-NUS Medical School, Singapore, and a remote visiting student at Duke University School of Medicine.
I work with Prof. Nan Liu at the Centre for Biomedical Data Science, Duke-NUS, and with Prof. Chuan Hong's research group at Duke. My current research focuses on Artificial Intelligence and Agents, including AI for Healthcare, Medical NLP, and Medical World Models.
News
- Visiting Scholar at Duke-NUS Medical School, Singapore, advised by Prof. Nan Liu.
- Second Prize at the East China Regional Final of the Service Outsourcing Innovation Competition.
- Second Prize at 2026 ASC Student Supercomputer Challenge.
- Excellent Award, 1st National Service Computing Innovation Competition.
- Visiting Student at Duke University, advised by Prof. Chuan Hong.
- Second Prize at 2025 ASC Student Supercomputer Challenge.
- Visiting Student at Zhejiang University NESA Lab, advised by Dr. Peiyu Liu.
Education
Research
Medical AI research on multilingual clinical dataset generation and multimodal diagnostic reasoning evaluation.
Clinical dialogue simulation, medical AI agents, and synthetic healthcare data generation. Leading LLM-based simulation frameworks for behaviorally grounded doctor–patient interaction modeling. Maintaining DCC computing cluster and H200 GPU benchmarking for large-scale AI research.
MCP server ecosystem security in AI-assisted code editors. Developed MCP-Collector for automated MCP Marketplace data collection and classification.
Medical multimodal dataset construction from online teaching videos. Building a bilingual (CN-EN) pathology image-text dataset and fine-tuning CLIP with LoRA for intelligent pathology diagnosis.
Publications
* Equal contribution · † Corresponding author
Projects
Accelerated UnifoLM-WMA-0 inference with mixed precision (FP16/TF32), Flash Attention, CUDA Graph, fused DDIM kernels, and pinned memory pipeline. Achieved 2.68× speedup over FP32 baseline, passing all 20 robotic evaluation scenarios at PSNR ≥ 25 dB.
Optimized RNA m5C modification site detection workflow. Automated data cleaning, alignment, deduplication, and statistical filtering. Achieved significant improvements in runtime and memory usage.
Teaching
Designed assignments, led problem-solving on MPI, OpenMP, and parallel algorithms.
Leadership
Leading the HPC team in competitions (ASC, IndySCC). Training on Slurm, parallel programming, and cluster operations.
Organized free equipment maintenance, solving 500+ problems at 98% satisfaction. Expanded service coverage and trained 25 new members.
Honors & Awards
- Second Prize East China Regional Final of the Service Outsourcing Innovation Competition
- Second Prize 2026 ASC Student Supercomputer Challenge
- Excellent Award 1st National Service Computing Innovation Competition
- Second Prize 2025 ASC Student Supercomputer Challenge