Students
                    The Pack Research Experience Program (PREP) is a research award for students with an academic standing of first-year or sophomore to join an existing research project under the guidance of a faculty mentor. Students unsure of their academic standing are encouraged to check with their academic advisors. Preference may be given to historically underrepresented or first-generation students.
Benefits of participating:
                    
                    Applications for these projects are due on Friday, Oct. 31, 2025 at 11:59 p.m. Visit the PREP student information page for details. Stay tuned for fall 2026 project announcements!
                    Elisa Baldrighi
Deep-sea life after oil spill
                    Laura Blume
Violence against public figures in Central America
                    Lei Cao
Behavior and evolution of alloys
                    Edward Ester
Eye movement correlation to decision making
                    Xingang Fu
Smart power electronics converters
                    Andrew Gorzalski
Hamilton liquid handler training
                    Sarah Haigh
Visual symmetry and discomfort
                    Alexis Hanna
Studying couples’ career strategies
                    Andrew Hess
Animal health, adaptation and grazing environment
                    Melody Huslage
Improving support for human trafficking survivors
                    Paul Kwon
Art intervention for transgender and gender diverse individuals
                    Jennifer Lanterman
Legal system deflection and diversion programs
                    Dingsheng Li
Life cycle impact of computing e-waste
                    Theresa McKim
Coding while analyzing neuroscience datasets
                    Mahdi Mehrtash
Renewable energy and the clean energy transition
                    Nicholas Murray
Diagnostics of sport-related concussions
                    Sujata Pandit
Monoclonal antibody generation
                    Shanon Taylor
Teacher requirements in behavior management
                    Yan Wang
Deep-neural-network molecular dynamics