Many students of the Texas A&M Vehicle Systems & Control Laboratory have been selected for internships for the Summer of 2026. These internships show VSCL student representation at a variety of companies and institutions across the United States. Students which have been selected for internships in the Summer of 2026 include:
Jillian Bennett will be interning with the Naval Air Warfare Center Aircraft Division in Patuxent River, Maryland with the STEM Student Employment Program (SSEP) implementing an adaptive multiple time-scale controller (KAMS) on a VTOL vehicle.
Raul Santos accepted an internship with the Force Projection Sector of John Hopkins University APL in Laurel, Maryland where he will be a Missiles GNC Engineering Intern.
Sadie Binz is joining the Naval Research Office (NRO) in Washington DC as a NREIP Intern working on single and multi agent reinforcement learning.
Seth Johnson accepted an internship with VectorNav Technologies in Dallas,Texas as a Navigational Engineering Intern where he will be working on software for sensor data fusion.
Aidan Timofte is joining General Atomics ASI in San Diego, California as a Flight Controls Engineering intern.
Lily Mikulas accepted an internship with the Air Force Research Lab (AFRL) Autonomous Capabilities Team (ACT3), facilitated through the University of Dayton Research Institute (UDRI).
Allision Barnes will be an Aviation Programs Engineering Intern with Garmin in Olathe, Kansas facilitating avionics integration with OEMs.
Bella Grayson will be joining NASA at Johnson Space Center in Houston, Texas as a systems engineering intern supporting Artemis III and IV.
Paige Warren is joining Gulfstream in Savannah, Georgia as a Flight Sciences Engineering Intern – Control Laws working on control law theory and simulation.
Laura Escamilla accepted an internship with AeroVironment in Moorpark, California as an Autonomy Engineering Intern.
Izzy Peressim was selected for the S-REU at Texas A&M University with Dr. Valasek. She will be researching the use of human eye gaze for improving the real-time training and mission performance of intelligent agents
Ishaan Bansal will be a software engineering intern for United Launch Alliance (ULA) in Denver, Colorado working on their control systems and state machines.
Erin Swansen: Guidance, Navigation, and Control TC
Cassie-Kay McQuinn: Intelligent Systems TC
Evelyn Madewell joins VSCL as a Ph.D student in the Aerospace Engineering department. She graduated in the Spring of 2024 from the 
Zach Curtis is graduated from 
Approaches for teaching learning agents via human demonstrations have been widely studied and successfully applied to multiple domains. However, the majority of imitation learning work utilizes only behavioral information from the demonstrator, i.e. which actions were taken, and ignores other useful information. In particular, eye gaze information can give valuable insight towards where the demonstrator is allocating visual attention, and holds the potential to improve agent performance and generalization. In this work, we propose Gaze Regularized Imitation Learning (GRIL), a novel context-aware, imitation learning architecture that learns concurrently from both human demonstrations and eye gaze to solve tasks where visual attention provides important context. We apply GRIL to a visual navigation task, in which an unmanned quadrotor is trained to search for and navigate to a target vehicle in a photo-realistic simulated environment. We show that GRIL outperforms several state-of-the-art gaze-based imitation learning algorithms, simultaneously learns to predict human visual attention, and generalizes to scenarios not present in the training data.
Payton Clem is a Master of Science Student in the Aerospace Engineering department. She is graduating from Texas A&M with her Bachelor of Science in Aerospace Engineering with Minors in Mathematics and Astrophysics in Fall 2023. During her undergrad, she was involved in campus activities like working at the Memorial Student Center to provide support to her fellow Aggies, and was a member of 
Jillian Bennett is a Masters of Science student in the Aerospace Engineering department. She graduated with her Bachelors of Science in Aerospace Engineering and Minor in Mathematics in Fall 2023. As an undergraduate she interned with Los Alamos National Laboratory and TAMU Material Science and Engineering, working on characterizing impacted materials. Additionally she was the lead ambassador for the Aerospace Ambassador program and a Fish Camp chair. Her work with VSCL will be primarily focused on 
2nd Lieutenant Noah Luna is a Masters of Science student in the Aerospace Engineering Department. He graduated from the United States Air Force Academy with a Bachelors of Science in Aeronautical Engineering and Computer Science. During his undergraduate studies, he performed research on a neural network based flight control system for an ongoing fixed-wing project through the Air Force Research Lab (AFRL). Additionally, he completed an internship and further research with Lockheed Martin Skunk Works as a Software and Flight Test engineer developing nonlinear adaptive flight controls for aerial systems. At VSCL, Noah will be working on 
) successfully defended his Ph.D. dissertation titled “Multiple-Timescale Adaptive Control for Uncertain Nonlinear Dynamical Systems”. Kameron’s dissertation investigated combining nonlinear multiple time-scale controllers that VSCL has been researching for the last 15 years, with adaptive controllers which VSCL has been researching for more than 20 years. Multiple-timescale control has been shown to have difficulty with uncertain systems and adaptive control has been shown to have difficulty with multiple-timescale systems. His dissertation describes a novel control methodology called [K]Control of Adaptive Multiple-timescale Systems (KAMS). KAMS seeks to address systems that simultaneously exhibit uncertain and multiple-timescale behaviors. Unlike traditional multiple-timescale control literature, KAMS uses adaptive control to stabilize the subsystems. The reference models and adapting parameters used in adaptive control significantly complicate the stability analysis. KAMS is a flexible theory and framework and the stability proofs apply to a wide array of adaptive algorithms and multiple-timescale fusion techniques. Additionally, formal and numerical validation of how KAMS can relax the minimum phase assumption for a multitude of common adaptive control methods. KAMS is demonstrated and evaluated on examples consisting of stabilization and attitude control of a quadrotor Unmanned Air System; fuel-efficient orbital transfer maneuvers; and preventing inlet unstart on hypersonic aircraft.