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The Center for Systems Science and Engineering (CSSE) at JHU

about us
who we are

The Center for Systems Science and Engineering (CSSE) is a research collective housed within the Department of Civil and Systems Engineering (CaSE) at Johns Hopkins University (JHU).  Our faculty, researchers, and students work on a range of complex and interdisciplinary problems, united by the goal to better understand and improve societal, health, and technological systems for everyone.

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Areas of focus

Explore Our Research

Energy

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public health

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healthcare

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transportation

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space

Tracking COVID-19

We are tracking the COVID-19 spread in real-time on our interactive dashboard with data available for download. We are also modeling the spread of the virus. Preliminary study results are discussed on our blog.

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Tracking Measles Cases in the U.S.

The project is a collaborative, interdisciplinary effort conducted by a group of researchers at Johns Hopkins University who are tracking and modeling the risk of measles in the U.S. It reflects contributions from the Center for Systems Science and Engineering (CSSE) at the Whiting School of Engineering, the International Vaccine Access Center (IVAC) at the Bloomberg School of Public Health, and the Bloomberg Center for Government Excellence. The team is led by Lauren Gardner, Shaun Truelove, and William Moss.

Link to Tracker

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.