In April 2020, the Science Alliance released a call for the JDRD Rapid Response COVID-19 Focus program. The program provided an expanded focus, offering support for projects related to the investigation of COVID-19 in any relevant discipline. Existing JDRD awardees were given the opportunity to apply for second year funding for their existing work based on the original parameters of the 2019 JDRD program.
COVID-19 JDRD First Year Projects
Dustin Gilbert – Department of Materials Science and Engineering
Developing Metallic Alloys for Self-Sanitizing Surfaces with Synergistic Mechanisms
The recent COVID-19 pandemic has exposed significant flaws in the global and national strategic preparedness for a biological outbreak. Metallic surfaces, specifically copper, has been demonstrated to have strong bioactivity against a variety of pathogens, including COVID-19, inactivating the virus in less than 4 hours and potentially as quickly as 150 seconds. His research proposes to develop high entropy alloys based on bioactive constituents to combat the indirect spread of pathogens.
Heidi Goodrich-Blair – Department of Microbiology
Diversity of Phage-like Tail Fiber Adhesins and Their Association with Contractile Structures
Bacterial viruses, or phases, can inject their genomes into hosts and have, over evolutionary time, co-opted phage remnant DNA to encode structures that can kill competitor cells. Researchers are engineering new types of phages and structures that can kill specific bacteria while leaving others intact. Her work seeks to better understand the relationship between phage/phage-like structures and target host cells.
Artificial Intelligence Aided 3D Metagenomic Mapping of Built Environments and Humans to Model Pathogen Transmission
Diseases caused by microbial pathogens have long plagued humanity. The staggering infection and death toll imposed by the ongoing COVID-19 pandemic further adds to the urgency for developing effective strategies to mitigate the spread of infectious pathogens, particularly within built environments. His research seeks to quantify the human-built environment | microbial exchange, such as the distribution of pathogens between hands and surfaces.
Second Year Projects
Anahita Khojandi – Department of Industrial & Systems Engineering
Dynamic Deep Reinforcement Learning-Bayesian Framework
The modern economy has been described as sensor-based. Sensors can collect data at high-frequency, which could potentially allow decision making in real time. Many frameworks exist that allow for such decision making, but they are typically either really good at fusing many data streams or adapting to changes in a dynamic environment. Khojandi’s work proposes to integrate the strengths of these frameworks and develop new methods that can accommodate various human-in-the-loop considerations and resource limitations.
Michela Taufer – Min H. Kao Department of Electrical Engineering and Computer Science
Empowering Training and Validation Stages in AI-Orchestrated Workflows
Adversarial attacks on AI-orchestrated systems occur when small perturbations of an input cause a dramatic change in the prediction of a neural network.There is recent research around training neural networks to be resilient to attacks, but none of these methods can prevent adversarial attacks. Taufer proposes to research methods to detect adversarial attacks so that the attack can be mitigated.