Haochang Hao

Haochang Hao

Ph.D. Student in Computer Science, University of Illinois Chicago

About

I am a Ph.D. student in Computer Science at the University of Illinois Chicago (UIC), advised by Dr. Lu Cheng. Prior to this, I obtained my Master's degree from the Shanghai Advanced Research Institute, University of Chinese Academy of Sciences (UCAS), under the supervision of Prof. Jun Huang, and my Bachelor's degree from Soochow University.

My research broadly focuses on building trustworthy and interpretable machine learning systems. My current research interests include:

Uncertainty Quantification LLM Safety & Hallucination Graph Neural Networks Data Mining

Education

Ph.D. in Computer Science
University of Illinois Chicago (UIC), Chicago, IL, USA
Aug. 2025 – Present  |  Advisor: Dr. Lu Cheng
M.Eng. in Electronic & Information Engineering
Shanghai Advanced Research Institute, University of Chinese Academy of Sciences, Shanghai, China
Sept. 2022 – June 2025  |  Advisor: Prof. Jun Huang
B.Eng. in Computer Science & Technology
Soochow University, Suzhou, China
Sept. 2018 – June 2022

Publications

Heterogeneous Graph Multi-level Semantics Extraction for Node Classification
Haochang Hao, Jun Huang, Shuzhen Rao
Neural Computing & Applications, 37, 11821–11841 (2025)
Progressive Alternating Attribute-Structure Optimization for Multiplex Heterogeneous Graphs
Haochang Hao, Jun Huang, Shuzhen Rao
Expert Systems with Applications, 312, 131495 (2026)

Invention Patents

J. Huang & H. Hao. “Node Classification Method, Device, Terminal, and Medium Based on Multi-level Semantic Representation of Heterogeneous Knowledge Graphs.” Approved.

Project Experience

Traditional Chinese Medicine (TCM) Terminology Corpus

Processed ~200,000 TCM text segments stored in MongoDB and MySQL; designed an efficient index-based retrieval system using Elasticsearch. Developed a Named Entity Recognition (NER) module with Jiayan tokenization. Built a full-stack visualization platform using Java (SpringBoot + MyBatisPlus backend, ElementUI frontend) with gRPC communication.

Voice Chatbot for Taoyangli Scenic Area, Jingdezhen

Constructed a knowledge graph from Jingdezhen porcelain data and built a voice-based QA chatbot. Designed knowledge graph extraction algorithms to retrieve relevant information from user queries and generate accessible responses. The system is deployed and available to tourists at the scenic area.

Awards & Honors

Multiple “Three Good Student” awards at the University of Chinese Academy of Sciences and Soochow University for outstanding academic and overall performance.