Hi, I'm Ruiheng Yu.

A
PhD student in Biomedical Engineering at University of Houston, researching Graph Neural Networks and Large Language Models for biomedical applications.

About

👋 Hi, I am a Phd Student at University of Houston. My research interests lie in Artificial Intelligence, Graph Neural Networks, and Large Language model, with a focus on applying machine learning to real-world challenges, particularly in healthcare, neuroscience, and precision medicine. Feel free to explore my homepage to learn more about my projects, publications, and open-source work. I'm always open to collaboration and new ideas!

  • Languages: Python, Java, JavaScript, C, C++, HTML/CSS, Bash
  • Databases: MySQL, PostgreSQL, MongoDB
  • Libraries: NumPy, Pandas, OpenCV, Sklearn
  • Frameworks: Flask, Django, Node.js, Keras, TensorFlow, PyTorch, Bootstrap, Apache Beam
  • Tools & Technologies: Git, Docker, AWS, GCP, Heroku, JIRA

Experience

Full-Stack Engineer
  • Tasked with initial requirement analysis and detailed software design
  • Used Vue, SpringCloud, and MyBatis technology stacks to build projects and the B/S application basic architecture pattern and agile development pattern for project architecture
  • Connected front-end and back-end with RESTful API style and employed Git to control and manage the development process of the project
  • Developed corresponding back-end function points and deployed the project to the server
  • Won the excellent member title
  • Tools: Vue, SpringCloud, MyBatis, Git, RESTful API
June 2023 - September 2023 | China

Research Projects

Interpretable GNN
Interpretable & Interactive GNN

Bayesian Edge Scoring and DP Subgraph Sampling for NeurIPS 2025

Research Details
  • Status: Ongoing (March 2025 - Present)
  • Interpretable GNN architecture with Beta-Bernoulli edge mask prior and DP subgraph prior
  • Novel loss term using entropic OT (Sinkhorn) to align graph representations
  • Full variational inference formulation and ELBO derivation
  • Interactive human-in-the-loop fine-tuning with counterfactual training
  • Target: NeurIPS 2025
Brain Networks
Functional Brain Networks & GNN

Graph Neural Networks for brain connectivity analysis and cognitive task classification

Research Details
  • Status: Ongoing (November 2024 - Present)
  • Supervisors: Professor Lu Wang and Liyan
  • Built sparse brain graphs using fMRI functional connectivity
  • Applied IBGNN for age group and cognitive task classification
  • Explored dynamic and multimodal brain graphs (MEG, fMRI, DWI)
  • Prepared Cam-CAN data for adjacency matrices and classification
Brain Trigger
Brain Trigger

Cognitive assessment using game-based reaction time analysis

Research Details
  • Status: Ongoing (December 2024 - Present)
  • Supervisors: Professor Mark Chignell and Lu Wang
  • Examined reaction times and task accuracy in congruent vs non-congruent trials
  • Employed hierarchical regression to predict participant age using RTs
  • Compared BrainTagger with traditional cognitive tasks from Cam-CAN dataset
  • Investigated potential for detecting cognitive harm (post-surgery, chemotherapy)
IVF Prediction
IVF Pregnancy Prediction

Machine learning for in vitro fertilization outcome prediction

Research Details
  • Duration: April 2023 - July 2023
  • Supervisor: Chen Kuo, Associate Professor
  • Evaluated ML/DL algorithms: XGBoost, LGB, LSTM, CatBoost
  • Combined Fireworks Algorithm for parameter optimization
  • Used Genetic Algorithm for unprecedented parameter optimization
  • Applied IG and Counterfactual Explanation for feature attribution
  • Achievement: Computer Software Copyright Registration
Traffic Sign Detection
Video Traffic Sign Detection

Enhanced YOLOv8 for real-time traffic sign detection in videos

Research Details
  • Duration: November 2023 - July 2024
  • Supervisor: Chengliang Wang, Professor
  • Enhanced YOLOv8 with HS-FPN for multiscale fusion
  • Replaced CA module with ELA channel attention mechanism
  • Redesigned detection head inspired by TOOD for better task alignment
  • Applied model pruning and knowledge distillation for edge deployment
  • Achieved real-time performance with improved accuracy

Skills

Languages and Databases

Python
HTML5
CSS3
MySQL
PostgreSQL
Shell Scripting

Libraries

NumPy
Pandas
OpenCV
scikit-learn
matplotlib

Frameworks

Django
Flask
Bootstrap
Keras
TensorFlow
PyTorch

Other

Git
AWS
Heroku

Education

University of Houston

Houston, USA

Degree: PhD in Biomedical Engineering
Duration: 2024.08.28 - Present

    Research Focus:

    • Graph Neural Networks
    • Large Language Models
    • Biomedical Applications
    • Brain Network Analysis

Chongqing University of Posts and Telecommunications

Chongqing, China

Degree: Bachelor of Engineering (Honors for an Outstanding Bachelor's Degree)
Major: Software Engineering
Duration: 2020.08.26 - 2024.07.01
GPA: 3.52/4.0 (86.91/100)
Ranking: 13/461

Chongqing University

Chongqing, China

Faculty: National Elite Institute of Engineering
Minor: Intelligent Vehicle Programming
Duration: 2023.08.26 - 2024.07.01
Certificate: Exchange Learning Certificate
GPA: 3.5/4.0 (85.75/100)

Contact