Call for Graduate/Undergrad Research Participation

We are excited to offer 2 graduate or undergraduate students the opportunity to participate in cutting-edge research in the field of graph machine learning. This project aims to advance our understanding of graph dynamics and develop innovative solutions to complex real-world problems.


  • Graduate or Junior student
  • Prerequisite skills: Python


  • hour rate will be discussed
  • Commitment of 10 hours per week during calendar year of 2024.

Project Task Description:

1. Flow over Higher-order and Multilayer Networks

  • Focus: Developing visualization system for graph flow over higher-order and multilayer networks.
  • Responsibilities: Learn network science, and develop visualization with Python visualization framework such as Dash.
  • Outcomes: Visualization system, Python package.

2. LLM for Graph Flow

  • Focus: Developing LLM application for graph flows.
  • Responsibilities: Create an online demo, user interface of customized LLM
  • Outcomes: customized LLMs with user interface.

Application Process:

Assistant Professor

My research interests include graph learningwith particular interest in graph dynamics.