Xuhui (Daniel) Zhan is a Data Scientist and Machine Learning Engineer with extensive experience in NLP, computer vision, multimodal AI, and MLOps. Recently graduated with a Master’s in Data Science from Vanderbilt University (GPA: 3.98/4.0), he combines robust theoretical knowledge with practical, real-world applications.

At Vanderbilt University’s AI Negotiation Lab, as Lead AI & Data Science Researcher, Xuhui developed an LLM pipeline that auto-codes negotiation transcripts, dramatically reducing costs by over 99% while increasing human-model agreement from 30% to 80%. His work has been presented at prestigious venues including the 2025 AI Negotiation Summit (Harvard/MIT).

In his role as a Graduate Research Assistant at Vanderbilt’s Network and Data Science Lab, Xuhui designed innovative fusion frameworks integrating vision, graph, and language modalities. He refactored LLaVA to reduce compute costs by 25% while matching SOTA accuracy, and built a TGAT-LLM pipeline that aims to outperform token-level integration methods.

As a Professional Research Assistant, he boosted ancient-mortar classification accuracy from 60% to 97% using Vision Transformers and invented a vision-only provenance algorithm that reduced analysis time from months to minutes.

Prior to Vanderbilt, as an Algorithm Development Engineer, Xuhui shipped a computer vision storage-detection system to approximately 30 warehouses, increasing pick accuracy by 15% and reducing manual checks by 80%. He also optimized ROS localization algorithms and standardized deployment toolchains for company-wide rollouts.

Xuhui earned his Bachelor’s degree in Data Science with First Class Honours and Highest Distinction from Beijing Normal-Hong Kong Baptist University, showcasing his commitment to academic excellence.

“Any sufficiently advanced technology is indistinguishable from magic.”

— Arthur C. Clarke, Clarke’s Third Law