Space

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Resilient Space Infrastructure

Space habitation is coming sooner than we think. Someone needs to make sure that the civil infrastructure we have developed on Earth can stand up to the hazards of Space when we take steps to build it out. It is difficult to ensure the resilience of critical infrastructure on Earth, but will be equally if not more complicated to do for Space. We aim to identify the risks associated with our critical infrastructure on Earth and understand how they will be exacerbated in Space. Additionally, we are designing resilient technology architecture for critical Space infrastructure that can be used as the basis for future Space-faring generations. 

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Hazard and Collision Avoidance

Space is becoming crowded. There is ‘Space junk’, cubesats, and expensive military satellites that orbit our planet. As it gets more crowded in Low Earth Orbit (LEO) we will need better mechanisms to make sure everything (including astronauts in the ISS) remain safe. Partnering with Space Force, AFRL and the Applied Physics Lab, we are working on solutions to conduct traffic in orbit. 

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Space System Cybersecurity

Space assets are highly susceptible to cyberattack. Sometimes the ground stations are targeted, other times it’s the communication channels; it’s even possible to compromise a satellite in orbit. Given the calibrated, sensitive nature of space assets, in conjunction with the challenges servicing and updating these systems, special attention should be paid to their resilience.  We work on theorizing attacks against such systems as well as resilience mechanisms to support their continued operations. We are also interested in studying the burgeoning ‘new space’ industry and how they are addressing security issues. 

In radiation therapy with continuous dose delivery for Gamma Knife® Perfexion™, the dose is delivered while the radiation machine is in movement, as oppose to the conventional step-and-shoot approach which requires the unit to stop before any radiation is delivered. Continuous delivery can increase dose homogeneity and decrease treatment time. To design inverse plans, we first find a path inside the tumor volume, along which the radiation is delivered, and then find the beam durations and shapes using a mixed-integer programming optimization (MIP) model. The MIP model considers various machine-constraints as well as clinical guidelines and constraints.

Radiation therapy is frequently used in diagnosing patients with cancer. Currently, the planning of such treatments is typically done manually which is time-consuming and prone to human error. The new advancements in computational powers and treating units now allow for designing treatment plans automatically.

To design a high-quality treatment, we select the beams sizes, positions, and shapes using optimization models and approximation algorithms. The optimization models are designed to deliver an appropriate amount of dose to the tumor volume while simultaneously avoiding sensitive healthy tissues. In this project, we work on finding the best beam positions for the radiation focal points for Gamma Knife® Perfexion™, using quadratic programming and algorithms such as grassfire and sphere-packing.