Applied Scientist II Intern, Amazon Robotics
Developed proprioceptive nonprehensile manipulation behaviors for high-throughput bin stowing across tens of thousands of distinct item states in dense clutter and uncertain contact conditions.
Edward Morgan
PhD candidate at Louisiana State University building physics-based robotics systems for underwater and manipulation problems, with a focus on uncertainty-aware modeling, stochastic systems, robust and model-based control, motion planning, and deployment.
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I am a PhD candidate in Mechanical Engineering at Louisiana State University with a minor in Computer Science. My research centers on marine robotics, multibody dynamics, physics-based simulation, uncertainty-aware and stochastic modeling, robust and model-based control, motion planning, and controls.
Before and alongside academia, I have worked across robotics and production software. That includes manipulation work at Amazon Robotics and backend systems engineering at Stanbic Bank, where I built software used in large-scale financial workflows.
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Developed proprioceptive nonprehensile manipulation behaviors for high-throughput bin stowing across tens of thousands of distinct item states in dense clutter and uncertain contact conditions.
Built multibody models, feedback controllers, and trajectory planners for underwater vehicle-manipulator systems using CasADi, PyTorch, Python, and C++. Designed simulation workflows for validation and supported field deployments for uncrewed marine systems research.
I also lead undergraduate labs in robotics and instrumentation.
Engineered backend systems for loan processing and tracking, built self-service mobile money banking features, and developed APIs for MobyCash, a digital cash management platform integrated with core banking infrastructure.
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Differentiable multibody dynamics from URDF to symbolic kinematics, dynamics, identification regressors, and code generation using CasADi.
Differentiable underwater vehicle dynamics with analytic derivatives and JIT compilation for optimization and simulation.
Physics-driven underwater vehicle-manipulator simulation with hardware-in-the-loop workflows for validation and sim-to-real analysis.
GPU acceleration for CasADi symbolic functions for large-batch evaluation and fast simulation.
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Uncertainty-Aware Adaptive Dynamics for Underwater Vehicle Manipulator Systems ICRA 2026
Autonomous Underwater Manipulation: Current Trends in Dynamics, Control, Planning, Perception, and Future Directions Current Robotics Reports, 2022
A Probabilistic Framework for Hydrodynamic Parameter Estimation for Underwater Manipulators OCEANS 2023
Collision Free Path Planning for Underwater Vehicles in Rapidly Changing Environments AIM 2024
Model-Based Visual Control for Robotic Manipulators Using Udwadia Kalaba Formulation IMECE 2023
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PhD in Mechanical Engineering, minor in Computer Science.
BSc in Mechanical Engineering, minor in Computer Science.
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Reviewer for IEEE ICRA 2024, IEEE Transactions on Field Robotics 2025, and RSS 2026.
1st Runner-Up, MTN Ayoba Hackathon, 2021.
Excellent Student Award, College of Engineering, KNUST, 2015 - 2018.
Mentoring and outreach through LSU robotics programs, ENGage LSU, and earlier community-led initiatives.
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C++, Python, CUDA, MATLAB, Java
ROS2, OMPL, FCL, Gazebo, OpenCV
CasADi, IPOPT, PyTorch, CVXPY, MOSEK, NumPy, SciPy
Linux, Git, Docker