About

Christopher Allred

PhD Candidate, AI Robotics Researcher, Software Engineer, Mechanical EIT

Welcome to my website! If your curiosity has brought you here, you’re in the right place. I love all things robotics and I’m passionate about developing innovative solutions to complex problems.

I am a robotics researcher focused on improving terrain cost estimation and dynamic motion learning for real-world robotic systems. My work emphasizes data-centric approaches to boost the performance and adaptability of legged robots. Explore my projects and research, and hopefully, you’ll learn something new about the field of robotics!

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Contact Information	https://www.linkedin.com/in/christopher-allred/

Summary	Ph.D. candidate specializing in reinforcement learning for robotics, with expertise in multi-agent systems and AI-driven autonomy. Research fellow at U.S. DEVCOM Army Research Lab, advancing robotic coordination, digital twin simulation, and intelligent decision-making.

Education	Doctor of Philosophy - PhD, Computer Science August 2021 - 2026 Utah State University Logan, UT, USA Advised by Prof. Dr. Mario Harper
	Bachelor’s Degree, Mechanical Engineering August 2016 - May 2021 Utah State University Logan, UT, USA

Experience	Research Fellow June 2021 - Present U.S. DEVCOM Army Research Laboratory (ARL) Logan, UT, USA Developed and researched a range of technology surrounding ground robotic platforms from reinforcement learning algorithms for legged robots and multi-agent coordination. Optimized and converted large-scale digital twins for ARL efforts on neural symbolic AI for the DARPA project: Transfer from Imprecise and Abstract Models to Autonomous Technologies (TIAMAT). Supported unifying simulation and learning efforts across Department of Defense and industry partners: NVIDIA: Omniverse/IsaacLab, ARL: Unreal, DSIAC: AFSIM, ERDC: Terramechanics. Invited to present multi-robot learning and simulations efforts at the 2025 NVIDIA GTC. Presented simulations at the AI Summit and collaborated with DSIAC. Developed a multi-agent system simulation that coordinated and collaborated among multiple robots for search operations. The simulation integrated with reinforcement learning (RL) and a centralized Multi-Agent Transformer (MAT). Created advanced dynamic reinforcement learning legged robot systems within the context of interpretable machine learning. Led the development of a terrain classification system that achieved a 97.5% accuracy using proprioceptive. Designed power terrain estimation system using both perception proprioceptive data for legged robots. Developed and deployed reinforcement learning algorithms for legged robot locomotion. *Legged Robots, Reinforcement Learning, Machine Learning, AI, Multi-Agent Systems*
	Graduate Research Assistant August 2022 - August 2023 Utah State University Logan, UT, USA Developed and tested learning-based locomotion strategies for quadrupedal robots in dynamic locomotion task. Created a simulation env and 12 benchmark algorithms for testing Multi-Agent Systems simulations for indoor environments, city-scale search, and team-based planning approaches. *Pytorch, Gymnasium, Reinforcement Learning, Legged Robots, Multi-Agent Systems*
	Graduate Teaching Assistant August 2021 - May 2024 Utah State University Logan, UT, USA Assisted and taught undergraduate and graduate courses in computer science: Compiler Construction, Intelligent Systems, Robot Intelligence, Multi-Agent Systems, Modern C++. *C++, Python, Java, AI, NLP, Machine Learning, Robotics*
	Lead Software Engineer March 2018 - May 2021 BRENKMAN & Company Logan, UT, USA Lead a team in a manufacturing technology startup, architect and developed automation software on the cloud for manufacturing with real-time image processing. Designed an automation system that increased production by 30% in six months. Orchestrated rapid design iterations, refining project scopes and deliverables in collaboration with corporate clients. Created high-performance multidisciplinary team in a fast-paced startup focused on manufacturing technology development and deployment. Transformed concepts into on-site implementations, overseeing refinement, testing, and deployment. Developed computer vision-based automation software to optimize manufacturing processes. Integrated CRM Database DynamoDB with the manufacturing process, enabling real-time photo processing and same-day manufacturing. *C++, Python, TensorFlow, Computer Vision, Javascript, DynamoDB, AWS*
	Mechanical Engineer Intern March 2018 - April 2018 BRENKMAN & Company Logan, UT, USA Worked on design and analysis of mechanical systems for manufacturing automation. HVAC and oil & gas industry. Developed drawings and designs of mechanical systems for oil & gas. Assisted Professional Engineer(PE) with fluid flow calculations. *Mechanical Engineering, CAD, Automation, Manufacturing, Analyses*
	Undergraduate Teaching Fellow January 2017 - March 2018 Utah State University Logan, UT, USA Taught Engineering Graphics and SolidWorks to undergraduate students. *SolidWorks, Mechanical Engineering, Teaching*
	Technical Support Specialist 2016 - 2018 Comcast, Stables, TiVo, CO & UT, USA Provided technical support, customer support, computer repair and sales. Proficient in networking, Internet, cable systems, consumer electronics, and entertainment streaming services. Provided Tier 2 (Advanced Support). *Technical Support, Customer Service, Networking, AV, Electronics, Computer Repair*

Research Publications	Cultivating Quadrupedal Robotic Agility: Unveiling Reinforcement Learning Dynamics with the Boosted Tree Motif Classifier March 2025 International Journal of Semantic Computing Explores the Boosted Tree Motif Classifier (BTMC) for precise motion pattern classification in quadrupedal robots, achieving 96% training precision. This builds on previous work by incorporating multivariate motif analysis and additional machine learning models, paving the way for whole-body reward development. https://doi.org/10.1142/S1793351X25410016 *Quadrupedal Robots, Reinforcement Learning, Boosted Tree Motif Classifier, Dynamic Motions*
	Coordinating Search with Foundation Models and Multi-Agent Reinforcement Learning in Complex Environments December 2024 International Conference on Robotic Computing Tokyo, Japan Authors: Christopher Allred, Jacob Haight, Chandler Justice, Isaac Peterson, Rosario Scalise, Theodore Hromadka, Jason L. Pusey, Mario Harper This presents a multi-agent system simulation designed for efficient coordination and collaboration for a team of robots, designed for search operations, that integrates well with reinforcement learning (RL) and a centralized Multi-Agent Transformer (MAT) https://doi.org/10.1109/IRC63610.2024.00046 *Multi-Agent System Simulation, Reinforcement Learning, Multi-Agent Transformer, Coverage*
	Efficient and Resilient Multi-Robot Exploration in Complex and Unknown Indoor Environments December 2024 International Conference on Robotic Computing Tokyo, Japan Authors: Huzeyfe Kocabas, Christopher Allred, Mario Harper Assessed the performance of twelve exploration strategies, considering factors like initial robot distribution, environmental segmentation, and robot failure conditions, when they are specifically supported with a task allocation strategy https://doi.org/10.1109/IRC63610.2024.00045 *Multi-Robot Exploration, Task Allocation Strategy, Robot Failure Conditions, Environmental Segmentation*
	Detecting Ballistic Motions in Quadruped Robots: A Boosted Tree Motif Classifier for Understanding Reinforcement Learning December 2023 International Conference on Robotic Computing Laguna Hills, CA, USA Authors: Christopher Allred, Jason L. Pusey, Mario Harper Introduced the Boosted Tree Motif Classifier (BTMC), a approach designed to accurately detect intricate learned motion patterns linked to high reward signals, thereby facilitating the learning of dynamic actions in quadrupedal robots. Demonstrating efficiency with a 96% precision rate. https://doi.org/10.1109/IRC59093.2023.00032 *Quadrupedal Robots, Reinforcement Learning, Boosted Tree Motif Classifier, Dynamic Motions*
	Unknown Building Exploration Simulator (UBES) October 2023 Software Impacts Authors: Christopher Allred, Huzeyfe Kocabas, Mario Harper Developed an open-source Unknown Building Exploration Simulator that employs twelve different algorithmic search strategies. It’s designed to stress test exploration scenarios in hazardous environments. The simulator allocates individual tasks to agents and partitions buildings. It also provides highly configurable environments for benchmarking and numerous intricate auto-generated building structures for strategy evaluation. https://doi.org/10.1016/j.simpa.2023.100576 *Simulator, Exploration, Robotics*
	Divide and Survey: Observability Through Multi-Drone City Roadway Coverage September 2022 2022 IEEE International Smart Cities Conference (ISC2) Pafos, Cyprus Authors: Huzeyfe Kocabas, Christopher Allred, Mario Harper Presented an algorithmic technique, Postman Moving Voronoi Coverage (PMVC), which effectively distributes and plans coverage routes for each drone agent, which divides city roadways into similarly sized subregions based on system limitations for many types of unmanned aerial vehicles (UAV). https://doi.org/10.1109/ISC255366.2022.9922207 *Drone Systems, City Roadway Coverage, Unmanned Aerial Vehicles*
	Terrain Dependent Power Estimation for Legged Robots in Unstructured Environments December 2022 International Conference on Robotic Computing Italy Authors: Christopher Allred, Huzeyfe Kocabas, Mario Harper, J. Pusey Developed a hybrid method for power estimation, utilizing proprioceptive and vision capabilities of a legged robot. This study examines strategies for forecasting terrain-dependent energy costs on five unique surfaces (asphalt, concrete, grass, brush, and snow). https://doi.org/10.1109/IRC55401.2022.00064 *Legged Robots, Terrain Dependent Power Estimation, Unstructured Environments*
	Improving Methods for Multi-Terrain Classification Beyond Visual Perception November 2021 International Conference on Robotic Computing Taichung, Taiwan Authors: Christopher Allred, M. Russell, Mario Harper, J. Pusey This research demonstrated terrain classifier using a long short-term memory (LSTM) model trained on actuator time series data, Utilizing the difference in center-of-pressure (COP) and leg forces. https://doi.org/10.1109/IRC52146.2021.00022 *Terrain Classification, Long Short-Term Memory, Actuator Time Series Data*

Talks & Presentations	Coordinating via Foundation Models for Heterogeneous Multi-Robot Search and Rescue [S71244] March 2025 NVIDIA GTC 2025 San Jose, CA, USA Multi-agent systems can be deployed using foundation models along with NVIDIA Omniverse to facilitate search-and-rescue operations with a team of heterogeneous robots, each possessing unique capabilities. Learn how multi-agent foundation models enhance coordination, data sharing, and decision-making in complex environments. Showcase real-time simulations of diverse robot morphologies (including wheeled, legged, and airborne systems) working together in dynamic, unstructured environments to complete rescue missions efficiently. Click Here to View
	Multi-Agent Reinforcement Learning in NVIDIA Complex Environments October 2024 AI Summit 2024 Washington, DC, USA Demonstrated simulations of large-scale outdoor environments where robots can learn and test capabilities. Presented to NVIDIA Rev, Vice President of Simulation and Omniverse, to facilitate collaboration between NVIDIA, ARL, and the USD alliance. Click Here to View

Certifications	Fundamentals Engineering Certificate EIT January 2021 National Council of Examiners for Engineering and Surveying (NCEES). Mechanical Engineering Fundamentals Certificate ID: 21-258-63 certifies a strong foundation in mechanical engineering and understanding of engineering principles. https://account.ncees.org/rn/2125863-1375797-77febd9
	Certified SolidWorks Associate October 2016 SolidWorks SOLIDWORKS CAD Design Associate (CSWA):C-XZTB6FJ3UW, certification validates fundamental proficiency in SolidWorks, demonstrating skills in 3D modeling, design principles, and engineering best practices, making it valuable for entry-level engineering and design roles. https://cv.virtualtester.com/qr/?b=SLDWRKS&i=C-XZTB6FJ3UW

Projects	Go1 Quadruped Robot June 2022 - Present DIRECT LAB Logan, UT, USA Researched reinforcement learning-based locomotion methods for robotic quadrupeds. Created a water resistant fabric snow protection system for the Go1 robot. Develop reinforcement learning jumping simulation . https://www.youtube.com/watch?v=QKlAStYxywY *Pytorch, Reinforcement Learning, Legged Robots*
	Boston Dynamics Spot Robot June 2021 - Present DIRECT LAB Logan, UT, USA Developed on autonomy and perception research with Spot quadruped robot.. Utilized a Spot robot to evaluate MEP-VP, a hybrid proprioception and vision-based approach for forecasting terrain-dependent energy costs across five surfaces, requiring only two seconds of motion data to generate actionable power estimates. Field experiments validated the effectiveness of this method, demonstrating its potential to enhance the deployment of legged robots. https://www.youtube.com/watch?v=5Sx1_3p9bOE
	DOFbot Robot Arm January 2022 - March 2022 DIRECT LAB Logan, UT, USA Developed a teleoperation robotic arm for a long-distance control system using Unity. https://www.youtube.com/watch?v=oqhFLoBzofw *Unity, C#, Robotics, Teleoperation*
	LLAMA Robot June 2021 - August 2021 Army Research Laboratory Aberdeen, MD, USA Within a short time frame, revived a dormant LLAMA prototype from storage, collected data on ARL’s first large-legged robot, and authored a published paper within three months.. Developed a terrain classification system using legged robot data, detailed in . https://www.youtube.com/embed/Hm9OMts41TM *Legged Robots, Terrain Classification, MATLAB*
	USU Mars Rover August 2020 - May 2021 USU Mars Rover Team Logan, UT, USA Developed robotic systems for planetary exploration. Designed ROS-based software for autonomous navigation and long range radio communication. Performed systems integration and testing. https://www.youtube.com/embed/deJiZued-sc *ROS, Radio Communication, Robotics*
	Angle Bender Automation April 2019 - June 2021 BRENKMAN & Company Logan, UT, USA A TensorFlow model is utilized to outline the curvature of a window well. After managing the data in our custom CRM using DynamoDB the photo is made immediately available for manufacturing either from a projected image or on an automatic angle bender. I managed the mechanical retrofit and development of the computer vision system on the angle bender. https://www.youtube.com/watch?v=DbwdfHJX2yQ *TensorFlow, Pytorch, Computer Vision, Manufacturing Automation*
	Perspective Correction of Images and Image Measurements April 2019 - June 2021 BRENKMAN & Company Logan, UT, USA A computer vision system software automatically identifies patterns used as references to correct perspective image distortion. A companion software package is subsequently employed to position measurement markers and reference lines. https://www.youtube.com/watch?v=oeR4ByDl1cE *Computer Vision, Manufacturing Automation*
	Soap Box Derby Car 2019 - 2021 Utah State University Logan, UT, USA Designed, built, and raced a gravity-powered Car for the annual Soap Box Derby. *Racing, Power Tools, Hand Tools*
	F.I.R.S.T. Robotics August 2008 - May 2012 USU Mars Rover Team Fort Collins, CO, USA Contributed to the development of a basketball-playing robot. Within six weeks, prototyped, developed, and assembled a functional drive train and manipulator. Designed and implemented an autonomous play system and a remote console. This comprehensive system earned a second-place finish in the regional championship. *SolidWorks, Robotics, Milling, Lathe, Mechanical Engineering*

Honors & Awards	GTC 2025: NVIDIA Top Developer Award 2025 Recognized for contributions and active engagement in NVIDIA’s developer ecosystem.
	1st Place, USU Hackathon: Hardware Category 2022 Utah State University Logan, UT, USA Robot Arm teleoperation using an Oculus VR Head set, with a Heroku server to transmit the data live to and from the robot arm. https://www.youtube.com/watch?v=Rrh76Q8C39Y *Unity, Digital twin, Simulation, WebSockets, Robotics*
	1st Place, USU Hackathon: General Category 2019 Utah State University Logan, UT, USA Designed an Augmented Reality program. Employed a Machine learning system for hand pose detection from the openCV DNN library. Used an Object file, in this case a 3D dragon, and rendered it on the palm of the hand of the user. 1st place in the General category and 2nd Place Overall. Click Here to View
	Mechanical Engineering Dean’s List 2017 Utah State University Logan, UT, USA Awarded for maintaining a 3.5 GPA or higher.

Service & Volunteering	Robotics Outreach August 2021 - Present Utah State University Present robotics to local K-12 students. Demonstrate the capabilities of legged robots and the importance of robotics in the future.
	Direct Lab Robotics Mentor August 2021 - Present Direct Lab Mentor students in the Direct Lab on robotics projects, monitoring their progress, providing constructive feedback, and assisting students. Additionally, recruit students for the Direct Lab Robotics team, conducting interviews and selecting candidates for the lab.
	Reviewer, IROS Conference March 2025 IROS Conference Reviewed papers for IROS Conference
	Reviewer, I-ETC Conference March 2024 I-ETC Conference Reviewed papers for I-ETC Conference
	Session Chair, IRC Conference December 2023 IEEE IRC Conference Chaired a session at the IRC Conference
	Session Chair, IRC Conference December 2022 IEEE IRC Conference Chaired a session at the IRC Conference
	Session Chair, IRC Conference December 2021 IEEE IRC Conference Chaired a session at the IRC Conference
	USU Robosub 2018 Utah State University Advised computer vision algorithmic recommendations for the USU Robosub team.
	USU ASME BattleBots 2017 Utah State University Supported ablation armor research for the USU ASME BattleBots team.
	Full-Time Missionary Service August 2013 - August 2015 Church of Jesus Christ of Latter-day Saints Eugene, OR, USA Served a two-year mission for the Church of Jesus Christ of Latter-day Saints in the Oregon Eugene Mission. Lead and organized teams of missionaries in service and food distribution.

Teaching Assistance	Compiler Construction January 2024 - May 2024 Utah State University Logan, UT, USA Introduction to key design principles and techniques for constructing compilers. This course aims to understand compiler components, algorithms, and theories, including lexical, syntax, semantic, intermediate, and target code generation, as well as some optimization principles. *Java, Compiler, Programming*
	Intelligent Systems August 2023 - December 2023 Utah State University Logan, UT, USA Data-Driven Intelligence, Natural Language Processing(NLP), and Planning are computational models that extract patterns, models, and understand and generate natural language texts and solve problems, respectively. *Artificial Intelligence, NLP, machine learning, Lisp*
	Robot Intelligence August 2022 - December 2022 Utah State University Logan, UT, USA Explore robotics through decision-making algorithms. Examine autonomous systems from a machine learning and data science perspective, focusing on sensing, planning, and interaction. *Robotics, Artificial Intelligence*
	Multi-Agent Systems January 2022 - May 2022 Utah State University Logan, UT, USA Comprehensive understanding of how to analyze, model, classify, apply, and design complex Multi-Agent systems *Multi-Agent Systems, Artificial Intelligence*
	Modern C++ August 2021 - December 2021 Utah State University Logan, UT, USA Advanced C++ language, focusing on updates made to it over the past 10 years. *C++, Programming*
	Engineering Graphics January 2017 - August 2017 Utah State University Logan, UT, USA Instructed Engineering Graphics course, covered ASME Y14.5-2009 standards, 3D modeling, and SolidWorks workflows. *SolidWorks, mechanical engineering, fundamentals*

Technical Skills	Languages: Python, C++, C#, Java, MATLAB, Lisp, JavaScript Robotics: Reinforcement Learning, ROS, Gazebo, Omniverse, Unreal Engine, Robotics, Legged Robots, Wheeled Robots, UAVs, Multi-Agent Systems, Computer Vision, Machine Learning, Terrain Classification, Path Planning, Autonomy, Teleoperation, Radio Communication Language Model Frameworks: Ollama, Hugging Face, OpenAI, CrewAI, OpenHands, SuperAGI Mechanical Engineering: SolidWorks, Manufacturing Automation, 3D Modeling Data Science: Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, OpenCV, Seaborn, cuDF Frameworks: PyTorch, OpenCV, ROS, TensorFlow, Unity libraries: torch, tensorflow, matplotlib, numpy, pandas, scikit-learn, stumpy, seaborn, cuDF Cloud: AWS, DynamoDB, Ray, Dask, Docker, Proxmox Simulators: Omniverse, Unity, Unreal Engine, Gazebo, pyBullet Project Management: Git, Kanban boards, LaTeX

Mentoring	Ph.D. Students Utah State University Logan, UT, USA Mentor Ph.D. students in the Direct Lab on robotics projects, supporting their progress, providing constructive feedback, and assisting students. Huzeyfe Kocabas Isaac Peterson Kobra Bohlourihajar
	Master’s Students Utah State University Logan, UT, USA Mentor Master’s students in the Direct Lab on robotics projects, supporting their progress, providing constructive feedback, and assisting students. Carter Bailey Zarin Shamma Gabe Tonks Jacob Haight Braxton Geary Tayler Baker Chandler Justice Chad McIntire Ryan Anderson Taylor Anderson

Christopher A.

Christopher Allred