The College of Engineering is pleased to announce that the College will fund three Catalyst proposals as winners of the Catalyst 2020 competition. The Catalyst program is aimed at early-stage, innovative ideas and can also enhance existing programs to help further scientific and research pursuits by engineering faculty.
A review committee, comprised of College of Engineering faculty, assessed the projects and made recommendations to the dean, who then selected the winning proposals. The reviewers noted that the proposed research will catalyze new areas of research, foster new collaborations that explore breakthrough ideas, and advance current pursuits in engineering research, potentially leading to a future moonshot initiative or serving as seed efforts directed toward large-scale, external funding.
The winning teams will work closely with the Engineering Research Accelerator to advance their research idea and identify external partners or sponsors.
2020 Catalyst winners
Catalyzing an interdisciplinary approach to engineering bacterial communities
Led by Shelley Anna, professor of chemical engineering, and N. Luisa Hiller, associate professor of biological sciences, this interdisciplinary partnership will use Catalyst funding to combine expertise in microfluidics and molecular and cellular biology, effectively enabling the high throughput exploration of various cells.
The influence of bacterial relationships extends from observable behavior, such as the dynamic spatial organization of a complex bacterial community, to molecular scale expression of specific metabolic compounds, and to genetic mutations that promote bacterial competition or cooperation. Although the connections across scales are known to exist, the generalizable rules and mechanisms that connect them have not yet been elucidated, so researchers are currently unable to exploit these rules to engineer bacterial communities for desired functionality.
The reason these mechanisms are still unclear is that significant challenges exist in systematically isolating, culturing, and combining individual bacteria from a given community and then examining corresponding genetic and molecular changes. While methods exist at each of these scales, they are difficult to connect across the history of a single species or community, and they are challenging to scale up to encompass the extremely diverse possibilities for bacterial species, communities, and systems. Anna and Hiller’s objective is to uncover the common rules by which effectors of bacterial relationships are integrated into genetic networks.
An integrated platform for high-throughput and real-time study of immune responses at single cell resolution
Led by Siyang Zheng, associate professor of biomedical engineering and electrical and computing engineering, Zheng’s team will use Catalyst funding to harness the immune system’s power to combat disease. This requires a novel technical approach that features high-throughput and real-time monitoring of immune responses at the single cell resolution.
To address the challenges in studying immune response and to provide a potential technology platform to advance personalized cancer immunotherapy, the team plans to develop a high-throughput microfluidic platform that traps cell pairs of different cell types, which then integrates sensors and in situ signal processing circuity to monitor cellular interactions in real-time. The resulting platform will hopefully create innovative and efficacious cancer immunotherapy treatments to fruition that can quantitatively assess immune responses and cancer cell behavior at the single cell resolution.
Other team members include Marc Dandin, assistant professor of electrical and computer engineering, Pulkit Grover, associate professor of electrical and computer engineering, and Elizabeth Wayne, assistant professor of biomedical engineering and chemical engineering.
Temperature field informed deep learning for fault detection and classification in additive manufacturing
Jonathan Malen, professor of mechanical engineering, and Amir Barati Farimani, assistant professor of mechanical engineering, will lead this effort. Process monitoring is key to additive manufacturing (AM) process qualification, and monitoring tools that can be applied across a wide range of metals AM processes are essential. Temperature is key to the melt processes, and thermal images provide quantitative insight beyond simple video.
Malen and Barati Farimani will use Catalyst funding to improve fault detection in AM processes by enhancing physical monitoring with unique, two-color thermal imaging systems that acquire accurate real-time temperature fields.
Additionally, they’ll be interpreting these fields with a deep convolutional neural network to anticipate and classify faults in the build. The Catalyst 2020 award will enable the acquisition of cameras and computers that will solidify this collaborative approach, teaming Malen (expertise in heat transfer and thermal imaging) and Barati Farimani (expertise in machine learning (ML) methods).