Soheila Farokhi

PhD Candidate in the Department of Computer Science at Utah State University.

prof_pic.jpg

123 Science Engineering Research Building

Old Main Hill

Logan, Utah 84322

I am a Ph.D. candidate in the Department of Computer Science at Utah State University, advised by Dr. Hamid Karimi. My research focuses on machine learning with graphs, particularly Graph Neural Networks (GNNs). Before joining Utah State University, I earned my master’s degree from Sharif University of Technology in Tehran, Iran, in 2018, where I worked on computational geometry, specifically visibility graphs, under the supervision of Dr. Alireza Zarei.

My current research explores novel GNN architectures, dynamic graph representation learning, and their applications in areas such as student performance prediction and modeling social network behavior. I am particularly interested in developing explainable and efficient graph-based machine learning models.

Useful links can be found at the bottom of this page.

news

Dec 15, 2024 I presented our paper titled “Advancing Tabular Data Classification with Graph Neural Networks: A Random Forest Proximity Method” at 2024 IEEE International Conference on Big Data (BigData).
Oct 25, 2024 I successfully passed my Qualifying Exam! :sparkles:
Sep 05, 2024 I remotely presented my paper titled “EDGE-UP: Enhanced Dynamic GNN Ensemble for Unfollow Prediction in Online Social Networks” at International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

selected publications

  1. BigData
    Advancing Tabular Data Classification with Graph Neural Networks: A Random Forest Proximity Method
    Soheila Farokhi, Haozhe Chen, Kevin Moon, and 1 more author
    In 2024 IEEE International Conference on Big Data (BigData), 2024
    DOI
  2. ASONAM
    EDGE-UP: Enhanced Dynamic GNN Ensemble for Unfollow Prediction in Online Social Networks
    Soheila Farokhi, Arash Azizian Foumani, Xiaojun Qi, and 2 more authors
    In International Conference on Advances in Social Networks Analysis and Mining, 2024
    DOI
  3. DSAA
    Enhancing the performance of automated grade prediction in mooc using graph representation learning
    Soheila Farokhi, Aswani Yaramal, Jiangtao Huang, and 3 more authors
    In 2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA), 2023
    DOI
  4. Resour. Policy
    Good governance and natural resource management in oil and gas resource-rich countries: A machine learning approach
    Moosa Tatar, Javad Harati, Soheila Farokhi, and 2 more authors
    Resources Policy, 2024
    DOI