A preliminary diffusion-based generative model experiment with cat and dog images

Optimal Trajectories via Generative Diffusion with Formal Guarantees for Drone Kinetic Intercept

This project establishes a control-theoretic generative capability for trajectory generation in drone kinetic interception scenarios.

Sandia 2026-LDRD-SUPN (ongoing)

Details and publications
A photograph of a custom-built knee brace

Neuromuscular retraining to relieve joint contact forces

Alteration of gait to minimize joint contact forces, thereby delaying the onset and slow down the progression of knee osteoarthritis.

Unfunded (ongoing)

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A block diagram of the proposed NDIMS framework

Network DISCORD Interface and Mitigation Systems (NDIMS)

The unifying conceptual thread of NDIMS is the use of spectral analysis of operators to distill complex, high-dimensional swarm behavior into low-rank, actionable approximations. By identifying the dominant eigenvalues and eigenvectors of the operators governing adversary dynamics, communication, and intent, we can isolate the critical vulnerabilities of a swarm.

DARPA DARPA-PS-26-27 (ongoing)

Details and publications
A schematic of satellite relative navigation reference frames

An adaptive optimal control approach for multi-agent autonomy in aerospace applications

The primary objective of this project is to develop novel solutions to multi-agent learning and control problems in the aerospace domain by formulating them as output-feedback adaptive optimal control problems.

AFRL FA8651-24-1-0019 (ongoing)

Details and publications
A schematic of load-based testing and predictive control

Optimal Control of Switched Systems for MCM

Online (i.e., real-time) adaptive optimal controllers for maritime systems that operate in complex environments where intermittent sensing and actuation render modern online optimal control methods unsuitable.

ONR N00014-21-1-2481 (completed)

Details and publications
A plot of value function estimation error being close to zero

Mine Countermeasures and Optimal Control

This project developed computational methods for reinforcement learning in continuous-time dynamic systems.

ONR N00014-16-1-2091 (completed)

Details and publications
A schematic of load-based testing and predictive control

Development of Reduced-order System Models for Next Generation Comfort Cooling Equipment

This project will focus on reduced-order modeling of HVAC units using both experimental research and first-principle model-based analysis.

OCAST AR41-042 (completed)

Details and publications
A collage of dynamic mode decomposition flow predictions

Operator Theory for Identification and Verification

We seek the development of new operator theoretic kernel methods that can harness data obtained from black and gray box dynamical systems.

NSF 2027999 (completed)

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A schematic of wind-aware UAV navigation

Wind-Aware UAV Navigation

Development of theoretical and computational tools that enable prediction and exploitation of low-altitude gust information for autonomous aircraft operations.

NSF 1925147 (completed)

Details and publications
A schematic of assume-guarantee contracts and wind-field decomposition

Scale Separation for Wind-aware Guidance and Control

In this project we developed a hierarchical control architecture that exploited the spatiotemporal scale separation in the atmospheric boundary layer wind flow dynamics.

NASA - EPSCoR - RIG 2019-33 (completed)

Details and publications
A block diagram of an actor-critic-identifier controller

An output feedback approach to adaptive optimal control of unmanned multi-agent teams

The objective of this project is to develop novel solutions to the multi-agent optimal decision making problem by formulating it as an output-feedback adaptive optimal control problem.

AFRL FA8651-23-1-0006 (completed)

Details and publications
A block diagram of an actor-critic-identifier controller

Model-Aware Reinforcement Learning

Methods for online real-time learning that are robust to modeling errors and abrupt changes in the dynamic models using a model-aware reinforcement learning framework.

AFRL FA8651-19-2-0009 (completed)

Details and publications
An image of an occupation kernel

Operator Theory for Control Synthesis

We are developing novel operator theoretic techniques for data and model-driven synthesis of control via control Lyapunov functions and solution of optimal control problems.

AFOSR FA9550-20-1-0127 (completed)

Details and publications