GraLNA 2024


REU Site: Graph Learning and Network Analysis: from Foundations to Applications
May-July 2024, Greensboro, NC

GraLNA (Graph Learning and Network Analysis, from Foundations to Applications) is a Research Experiences for Undergraduates (REU) Site at UNC Greensboro. It will provide 8-week paid summer research opportunity in the foundations of graph machine learning and network analysis and their concrete applications in real-life networks such as Internet of Things, brain networks, and online social networks.

Highlights

  • Cutting-edge research experience in graph machine learning, federated learning, differential private graph analysis, 5G network security, brain network analysis and brain disease diagnosis.
  • Professional development in responsible conduct of research and graduate program application process
  • Field trips to Duke and UNC-CH within the Research Triangle Park (RTP) in NC
  • $700/week stipend, paid housing (arranged by the program), meal plan, one round trip to and from campus

Interested in joining the cohort of 2024?

Apply Now: https://etap.nsf.gov/award/5679/opportunity/7791

Eligibility

Students who apply to GraLNA must be

  • US citizen or permanent resident
  • In good academic standing at their college or university
  • Have completed data structures and computer programming courses
  • Available full-time during the program
  • Prior research experience, demonstrated strong programming capability, or mathematical capability is a plus

Students from underrepresented minorities groups in STEM, including those from Minority Serving Institutions (MSIs) or Primarily Undergraduate Institutions (PUIs), are strongly encouraged to apply.

Acceptance

The applications will be reviewed on a rolling basis, so apply earlier! After the acceptance process is complete, the remaining applicants will be notified by email.

Once the program offer is accepted, a student participant is obligated to complete the entire (all 8 weeks) program and meet the program requirements.

This program is made possible by the National Science Foundation (NSF).