UROP Research Mentor Project Submission Portal: Submission #794

Research Mentor Information
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Primary Research Mentor Name: Yushun Dong
Research Mentor Preferred Pronouns: he/his/him
When potential research assistants are reaching out via email, what is your preferred honorific?: Dr.
Contact Email (FSU Email if affiliated): yd24f@fsu.edu
Position Title: Faculty
FSU College (if applicable): Arts and Sciences
FSU Department or Non-FSU Organization Affiliation: Department of Computer Science
Headshot (optional): https://cre.fsu.edu/system/files/webform/urop_project_proposal_portal/14596/521.jpeg

Additional Research Mentor(s)
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Overall Project Details
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Title of the Project: Inductive Recommendation on Large-Scale Social Networks
Project Keywords: Graph Neural Networks, Social Networks, Recommendation Systems, Scalable Machine Learning, Inductive Learning
Are you currently looking for research assistants?: No
Number of Research Assistants Needed : 6
Relevant Research Assistant Major(s):
Computer Science, Electrical and Computer Engineering, Data Science, Applied Mathematics, Statistics

Project Location:: On FSU Main Campus
If the project location is off campus, does the research assistant(s) need to provide their own transportation?: No, the project is remote
Please select the choice that most accurately describes your expectations for the research assistant(s):: Fully Remote
Approximately how many hours a week would the research assistant(s) need to work?: 5 - 10 hours
Roughly what time frame do you expect research assistant(s) to work?: Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Overall Research Project Description:
This project aims to develop novel graph learning frameworks to facilitate inductive and scalable recommendations on large-scale social networks. The research focuses on overcoming the limitations of existing Graph Neural Networks (GNNs) by designing a model that can be trained with limited computational costs and easily generalized to unseen social networks without retraining. The proposed framework will leverage both structural and positional encoding to achieve scalable and inductive recommendations, potentially improving the efficiency of recommendation systems on online social network platforms.

Research Tasks:
(1) Develop a scalable and inductive method for social network recommendation
(2) Design and implement a novel message-passing graph neural network model
(3) Implement and optimize the proposed graph learning framework
(4) Conduct offline evaluations using public and anonymous recommendation datasets
(5) Analyze and compare performance metrics such as NDCG and other industrial recommendation metrics with alternative models

Skills that research assistant(s) may need::
(Recommended) Strong programming skills, particularly in Python
(Recommended) Experience with machine learning frameworks (e.g., PyTorch, TensorFlow)
(Recommended) Familiarity with recommendation systems and social network analysis

Mentoring Philosophy:
As the principal investigator, I believe in fostering a collaborative and supportive research environment. Research assistants will have the opportunity to work closely with me and other team members, including PhD student Yushun Dong. We encourage creative thinking, rigorous analysis, and open communication. Research assistants will be given the opportunity to contribute to cutting-edge research in graph machine learning and recommendation systems, with the potential for co-authorship in research publications. We also value the development of practical skills through collaboration with our industry partners, bringing potential opportunities such as internships.

Please provide a link to your publications, a video clip, or a website for your research project (if applicable):: https://scholar.google.com/citations?hl=en&user=_QUhuOMAAAAJ
Please add any additional information here (if applicable)::
The project builds upon the PI's strong research experience in graph machine learning, with opportunities to work on research paper submissions and research topics that are closely related to the listed one.

Successful candidates will be able to continue working with the research group under a broader scope of collaborations leading to a track record of high-impact publications and industry collaborations.

If you are interested, please visit the site below for a toy research example. Please share your opinions with me to gain priority on working with me by reaching out to yd24f@fsu.edu.

https://yushundong.github.io/files/2024_toy_essay.pdf




Are you interested in participating in the UROP Research Mentor Roundtable?: Yes
Roundtable times and Zoom links:
Thursday, Sept. 5th from 2PM - 2:30PM ET
Zoom link: https://fsu.zoom.us/j/7153751215

Roundtable Info:
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UROP Program Elements
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Mentor Handbook, FAQs, and Communication: Yes
UROP Performance Evaluation: Yes
Materials Grant: Yes
UROP Poster Presentation: Yes

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Year: 2024
update url: https://cre.fsu.edu/urop-research-mentor-project-submission-portal?element_parents=elements/research_mentor_information/headshot_optional_&ajax_form=1&_wrapper_format=drupal_ajax&token=QtPjjPwjSrBJmnkQ3DI14Su7dBY4TPbjUCF0gGQqnIs