PhD candidate · Electrical Engineering · University of Notre Dame
I research robotic locomotion in environments that punish rigid machines — soil, sand, confined channels, anywhere a wheel is the wrong idea. The work sits in the MiniRo Lab (Minimalist Naturally-Inspired Robotics) at the University of Notre Dame, advised by Prof. Yasemin Ozkan-Aydin.
Three threads run through it: soft and limbless bodies that get their capability from compliance rather than from more actuators; granular media, where the ground is neither solid nor fluid and standard models stop applying; and mathematics that makes either tractable — geometric mechanics, variational integrators, and feedback control derived from partial differential equations rather than from a lumped approximation.
Publications
5
All first-author
IEEE venues
3
ICRA · IROS · ISER
Degrees
3
ME major · EE + aero minors · EE doctorate
Undergrad GPA
3.9
Tau Beta Pi · Johnson Scholar
(01)
Five peer-reviewed and preprint papers, first author on all of them. Listed newest first; PDFs and demonstration videos linked where they are public.
2025
ISER 2025 · International Symposium on Experimental Robotics
What happens when several small robots have to excavate together rather than one large one doing it alone — which tools work, where the coordination breaks down, and what the experiments say that the simulations did not.
2024
arXiv:2409.10827 [cs.RO] · Preprint
Limbless locomotion modeled through geometric mechanics with a variational integrator that requires only the dissipation metric. Despite substantial simplification from the variational principle, simulation tracks experiment on real undulating robots — which is the whole claim worth making.
2024
IEEE ICRA 2024 · International Conference on Robotics and Automation
Burrowing is expensive to model analytically and expensive to search by hand. This paper puts machine learning in the loop to find gaits that get a snake-like robot into granular media efficiently — the intersection of the applied-ML practice and the locomotion research.
2023
IEEE IROS 2023 · International Conference on Intelligent Robots and Systems
A soft body is a continuum, so control it as one. Feedback derived from the governing PDEs rather than from a lumped-parameter stand-in, and closed in real time on real pneumatic hardware.
2023
IEEE IROS 2023 · International Conference on Intelligent Robots and Systems
Peristaltic locomotion and obstacle negotiation in a worm-like soft body — getting useful navigation out of a robot with very few degrees of freedom and no rigid skeleton to plan against.
(02)
Four recurring problems, and why each one resists the obvious approach.
A soft robot has effectively infinite degrees of freedom and no rigid frame to plan against, so most of classical robotics does not transfer. The payoff is that compliance does work for free — squeezing through a gap, surviving a collision, conforming to a surface — that a rigid machine buys with more actuators and more failure modes.
Sand and soil are neither solid nor fluid, and they change state under the robot that is moving through them. Locomotion there cannot be designed from a free-body diagram; it has to be measured, learned, or derived from a model that admits the ground is participating.
Lumping a continuum into a handful of rigid links is convenient and quietly wrong. Deriving feedback from the governing partial differential equations keeps the model honest — and the papers above show it closing in real time on actual pneumatic hardware, not only in simulation.
Geometric mechanics and variational integrators turn a hard dynamics problem into a structured one, and preserve the physical invariants that naïve numerical integration destroys over long horizons. Fewer parameters to identify, and a simulation that still agrees with the experiment after a thousand cycles.
(03)
Mechanical first, electrical second, computing throughout — in that order, on purpose.
2022 – present
University of Notre Dame · MiniRo Lab · Advisor: Prof. Yasemin Ozkan-Aydin
Doctoral research in minimalist, naturally-inspired robotics: soft and limbless locomotion, burrowing in granular media, collective excavation, PDE-based real-time control, and geometric-mechanics modeling. Five first-author papers to date across IEEE ICRA, IROS and ISER. Graduate coursework spans control theory, machine learning, computer vision, and deep generative models.
2017 – 2021
Santa Clara University · Minors: Electrical Engineering, Aerospace Engineering
A full mechanical engineering degree — machine design, thermodynamics I and II, fluid mechanics, dynamics, statics, strength of materials, materials science, and manufacturing processes — with an electrical minor covering circuits, logic design and electromagnetics, and applied mathematics through differential equations and numerical methods. Dean's List; Tau Beta Pi (top 8% of the engineering class); Johnson Scholar, one of ten full-tuition academic scholarships awarded to the incoming class.
Fall 2019
LTH School of Engineering, Lund University · Sweden
A term at Sweden's leading technical university, in the aerospace engineering exchange track.
Summer 2019
Shamrock Foods Company · Phoenix, Arizona
Reported to the Head of Engineering at one of the southwest's largest food distributors. Overhauled the record-keeping system for the company's transition to automated storage, and worked with the project manager on the installation logistics of a Dematic Multishuttle system — construction, commissioning, and automation at industrial scale.
(04)
Selected awards and distinctions.
Open to collaboration, review, speaking, and consulting work where the problem is genuinely a research problem — locomotion, soft actuation, control, or applied machine learning.