Lipscomb's College of Engineering offers 3 ABET-accredited degrees in mechanical, electrical & compu
With employment rates near 100% for our graduates with companies like SpaceX, Boeing, Rolls-Royce, Barge Waggoner Sumner & Cannon, TTL, Torch Technologies, Bonitron, TTL, Nissan, and more, we have a proven record. Offering degrees in civil and environmental, electrical and computer, and mechanical engineering, we provide students with a solid theoretical base coupled with real world application. I
06/17/2026
The Honor's College at Lipscomb University featured some of the research opportunities that exist at the College of Engineering, take a look!
https://youtu.be/3i1fjTJDKAI?si=I7dgSn5FrDEgAbRF
Lipscomb University | Honors College Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.
06/17/2026
The group at is working hard to finish this open-source open-hardware bi-manual humanoid by the end of the summer! We look forward to be working with our new robot!
https://youtu.be/QzJSBbF7zIE?si=vCoQ6qaCMczsUB-l
❤️
06/09/2026
Congratulations to Dr. Juan Rojas for winning an award from the Nvidia Academic Grant program for his work in "Accelerating Deep Reinforcement Learning via Fractal Symmetries".
Nvidia will be supporting the research by donating an RTX PRO 6000 Max-Q Workstation Edition GPU.
https://bit.ly/4e4d8Py
NVIDIA Academic Grant Program for Researchers Submit your research proposal.
06/09/2026
The undergraduate team had a chance to present their latest reasearch at ICRA, the premiere conference in robotics, which was celebrate in Vienna, Austria. Ryan Vanderstelt and Gabe Everett presented their work in Accelerating DRL via Fractal Symmetries at the RoboARCH: Robotics Acceleration with Computing Hardware and Systems Workshop.
06/09/2026
Congratulations to Dr. Juan Rojas and the Undergraduate research team for publishing their research in the Frontiers in AI Journal!
Their work is titled:
Exploring Deep Reinforcement Learning Acceleration by Superscaling Data Augmentation via Branched Fractal Symmetries
The work explores how to superscale data augmentation for learning deep reinforcement learning policies directly on physical robots via fractal branching, resulting in state-of-the-art learning speeds.
This work is critical in allowing robots in the wild to learn robust policies on the spot.
The full article will be available shortly:
https://myfrontiers.frontiersin.org/projects/submission/1791812
04/30/2026
The lippyRobotics undergraduate research lab participated in Stewarts Creek High School's battlebot competition "Kilobots" https://www.kilobots.stemwise.net/event-info. Associate Professor Juan Rojas served as one of the judges at the competition.
It was an action-packed competition where middle and high school students 3D-printed their battle bots. It was an honor and an amazing opportunity.
On our end, we got the students to directly control the robot, create demos, observe how the robot learned on its own, and ask questions!
It was an inspiring time.
04/30/2026
The lippyRobotics undergraduate lab (https://lipscomb-robotics.notion.site/), recently took their FR3 robot to an AI competition hosted at Vanderbilt University: https://www.vanderbilt.edu/valiant/programs-events/discoverai-2026/
The embodied AI the team presented, by running response deep reinforcement learning on manipulation tasks, caught a lot of attention at the event. For many people, it was the first time they had seen a robot learn live and respond to disturbances (see the video below)
We are very proud of their participation!
For more pictures, look at our photo album: https://bit.ly/4f2yO0C
04/30/2026
Associate Professor Juan Rojas (www.Juanrojas.net) was awarded a $15,000 grant by Open Research Community Accelerator (Open Scholarship Catalytic Awards Program).
This project is working to lower barriers to entry regarding the research and science necessary for undergraduate students and underserved populations to quickly get up to speed with the theory and skills in artificial intelligence, robotics, and systems.
Members of the lippyRobotics undergraduate research lab created and continue to update their www.lipscomb-robotics.notion.site portal to this end.
The group is also hosting workshops and round-table discussions to further bring community members as well, Follow the notion site for more details.
Finally, enjoy the following YouTube video as the team discusses their achievements.
https://youtu.be/mmtwe8K3oHQ?si=mIYflfLJ-t2RczPi
Juan Rojas 1 like. "ORCA Final Report: Minutes-to-Mastery: Accelerating Robotic Manipulation with Efficient Group DRL"
As part of the "EECE 4483 Fundamentals of Machine Learning" class, students learned to deploy DRL algorithms directly on a 7-degree-of-freedom robot manipulator.
The algorithms must operate in high-dimensional continuous spaces and produce safe, coherent manipulation trajectories.
Students work in Linux, learn about Mujoco simulations, use Gym to interface with the system, and leverage algorithms like DDPG/SAC to train. Results are visualized in TensorBoard or in Weights & Biases.
The video below depicts a policy that students programmed and learned on their own through
reward signals.
It's been an exciting semester in our "EECE 4483 Fundamentals of Machine Learning" class. Associate Professor Juan Rojas (www.JuanRojas.net) teaches machine learning (supervised and unsupervised), neural networks, Markov Decision Processes, Reinforcement Learning, and Deep Reinforcement Learning (DRL).
The final project then explores the intersection of Deep Neural Networks and Reinforcement Learning. Students studied the underlying mathematics of how these algorithms work and then deployed them.
The videos below show student assignments in which agents learned policies using DRL algorithms like Deep Deterministic Policy Gradient and Soft Actor-Critic.
For the bipedal runner, notice how an agent may develop different policies as it learns to walk and move forward.
