Program Overview

Introduction to the High School Summer Research Program

The High School Summer Research (HSSR) Program is an outreach initiative by the LSU College of Engineering, aimed at engaging high-achieving high school students in real research in the fields of engineering, computer science, and construction management. The program's goal is to develop students into the next generation of transformative problem solvers for the local region, the state, and beyond. HSSR interns have the opportunity to learn from faculty research groups, understand how they work, and gain insights into what inspires them and how to continue in " " " " " " " " " " " " " " " " " " " " " "ields related to engineering in college and beyond.

Program Goals

The program has several key goals:

• To give high-achieving, highly motivated, and hard-working local high school students meaningful experiences in engineering, computer science, and construction management research during summer.
• To develop students' curiosity, research methods, and intellectual abilities before they have completed high school or made decisions about which college to attend and what bachelor's degree to pursue.
• To develop students' abilities to communicate technical content using both written and oral modes of communication.
• To teach students about the engineering design process and how it can be applied to both fundamental and applied research.
• To introduce these students to the opportunities available at the LSU College of Engineering and showcase the impressive faculty and research available to them at the state flagship university.
• To support faculty in their research projects and outreach efforts.

Information Sessions

Three virtual sessions will be held, as well as one in-person session, each from 5:30 p.m. - 6:30 p.m.:

• October 22, 2025 (virtual)
• November 18, 2025 (virtual)
• December 9, 2025 (virtual)
• January 13, 2026 (in-person) Registration is required to attend an information session, and meeting details will be provided via email after registration.

Program Details

Students selected as HSSR interns are matched with a College of Engineering faculty member's research team. They will receive guidance from the professor, as well as graduate-student and undergraduate-student mentors, as they work on a project related to the research team's ongoing research. Key aspects of the program include:

• HSSR Interns will not be paid for their work.
• HSSR Interns will be held accountable for their work responsibilities by the College of Engineering and will be expected to compete in regional science fair competitions.
• The program will provide information and training regarding science fair participation.
• HSSR Interns will have to complete detailed safety paperwork and training through the course of the spring 2026 semester in order to begin work on a project in summer 2026 and beyond.
• HSSR Interns will be required to work about 15-20 hours per week during summer 2026 for a total of about 120-140 hours. Weekly schedules can be flexible depending on summer travel/activity schedules, however students should not miss more than 4 working days.

Eligibility and Application

To be eligible for this program, applicants must:

• Be at least 15 years of age.
• Be currently enrolled as a 9th, 10th, or 11th grader.
• Have a 3.5 (or equivalent) high school GPA (as listed on a current high school transcript).
• Complete and submit the application by February 6, 2026. The application process includes:
• Completing the LSU College of Engineering 2026 High School Summer Research Intern Application.
• Including/uploading a 500-word personal statement focused on how the opportunity will impact their future as they pursue an education/career in engineering and what skills and experience they expect to gain.
• Including/uploading a current unofficial high school transcript.
• Including/uploading a signed Parent/Guardian Statement of Support.
• Including/uploading a current resume of academic, volunteer, community service, leadership, and extracurricular activities.
• A letter of support from a current science teacher must be emailed to the program administrator.

Current Projects

The program features a variety of research projects across different fields, including:

• AI Text Completion
• Using Metal-Based Zeolite Catalysts to Recycle Plastics
• Optimizing Ultra High-Performance Concrete using Python
• Traffic Light Detection and Recognition on Autonomous Driving Systems
• Efficiency of Photovoltaic Panels Under Baton Rouge Weather Conditions
• Soft, Liquid Metal Embedded Fluoroelastomers for Space Equipment and Seals
• Developing the Usage of Hydrophones in Underwater Robots
• Machine Learning for Polymer Topologies
• Lane Detection Through Use of Mobile Robots
• Hurricane Performance on Storage Tanks
• Algorithm Design for Autonomous Vehicles: from Cyber System to Physical System
• Analyzing Influence of Lighting Parameters on Biological Surface Imaging
• Using Machine Learning to Predict Cross-Site Scripting Vulnerabilities in JavaScript
• Fabrication of Non-biofouling Nanochannel UV-Curable Devices
• Renewable Bio-Oil from the Pyrolysis of Sugar Cane Bagasse
• Sustainable Energy from Photovoltaic Panels
• Enhancing User Experience for d/Deaf Community Using Machine Learning
• Multi-Agent Reinforcement Learning for Gaming
• Ion Surface and Bulk Diffusion Coefficient Measurements in Microchannels of Microfluidic Devices Utilizing Current-Time Monitoring

Past Projects

Previous years' projects include:

• The Use of Glass Sand to Prevent Erosion in Coastal Louisiana
• Quantifying the Benefits of Freeboard Policy on Louisiana Parishes' Class in the Community Rating System
• Studying the Effects of Distortion on the Hydrodynamics in the Lower Mississippi River Physical Model
• Coordination of Fully Automated Vehicle Platoons for Crossing Non-stop Intersections
• Optimal Path Planning with Applications to Automatic Parking
• Utilizing Machine Learning Classification Algorithms to Detect Pancreatic Cancer with Fluorescence Spectrum Data
• Weighted Gene Co-expression Network Analysis (WGCNA) Analysis of the Genotype-Tissue Expression (GTEx) data from the left ventricle
• Pancreatic Cancer Detection by Artificial-Intelligence-Assisted Raman Spectroscopy
• Development of Earthen Building Materials Inspired by the Nest Construction Techniques of Mud Dauber Wasps
• Machine Learning-Based Colloidal Self-Assembly Phase Identification
• Unraveling the potential of ChatGPT and AI in optimizing the Average High Schooler's Daily schedule
• Examining Drivers' Behaviors to Connected and Autonomous Vehicles
• Comparison of Bone's Natural Microstructure to Applied Speckle Patterns
• A Machine Learning Approach to Analyze Energy Burden in U.S. Low-Income Households
• Toluene Production Capacity of a Microbial Community Derived from Colorado River Sediment
• The Photobleaching Effect of Fluorescent Proteins for Cell-Free Biosensor Development
• 3D Printed Co-culture Platform to Study Bacteria Induced Endocrine Resistance in Breast Cancer
• Tracking Augmented Reality/Virtual Reality (AR/VR) Users' App Usage Duration through Push Notifications
• Improving Low Temperature DRM by Deposition of CeO2 Overlayers on Ni/Al2O3 Catalysts
• Microfluidic 3D Co-culture of Estrogen Receptor Positive (ER+) Breast Cancer and Stromal cells Study Endocrine Resistance
• Backdooring AI Models with Data Poisoning
• Improving Superwood by Optimizing the Delignification Process
• Optimization of Cell-Free Protein Synthesis
• Evaluation of Staining Method for Analysis of Cortical Bone Geometry
• 3D-Printed Co-Culture Platform to Study Bacteria-Induced Chemotherapeutic Resistance in Breast Cancer
• Solute Movement in Surface Water With Different Stream and River Geometries
• Keystroke Privacy Leakage From Zoom Meetings
• Artificial-Intelligence-Aided Laryngeal Cancer Identification
• 3D-Printed Soil Bricks Inspired By Mud Dauber Nest
• Single Cell Analysis of Deubiquitinating Enzyme (DUB) Activity Using a Droplet Microfluidic Trapping Array
• Accelerating Reinforcement Learning
• The Role of the Genus Azospira in Transforming Arsenic-Containing Compounds
• Designing RNA Gene Circuits With Coherent Feedforward Loops
• Demonstrating UAV Propulsion Using an Aircraft and Flight Model With Hardware in Loop Approach
• An Investigation into the Role of Fluid Shear Stress on Enhanced Cancer Extravasation during Metastasis
• Nanoengineering Balsa Wood for Resilient Superwood
• Reinforcement Learning in Flappy Bird
• Steel Fiber Reinforcement in 3D Construction Printed Concrete
• Detecting Hidden Security Threats With a Thermal Camera
• The Impact of an Integrated Local Fan in a Central Cooling System on Occupant Thermal Comfort in Working Environments
• Designing RNA Gene Circuits With Incoherent Type-1 Feedforward Loop
• Multimodal Label-Free Monitoring of Stem Cell Differentiation: Confocal Microscopy
• Geotechnical Analysis and Comparison of Recycled Glass Sediment for Coastal Restoration