Research Projects

With the increasing demand for new, cleaner chemical processes, the use of living systems (like microorganisms) has become of increased interest. One approach is towards engineering microorganisms, such as bacteria and yeast, as cellular factories to produce chemicals of interest. Natural, internal regulators of these microorganisms called small RNAs (sRNAs) are promising tools for the control of these organisms for engineering purposes. However, it is largely unknown where these sRNAs are encoded in the cellular genome and which of these sRNAs are actually useful for the given engineering goal. The Chemical Engineering group is developing a bioinformatics pipeline including RNA-sequencing analysis to identify sRNAs and rank them according to their probability of impact as regulators for engineering goals. The REU student will help automate this process, adapt it across different organisms, combining multiple existing tools (R, Python, web) and manual processes into a more user-friendly package.

The REU student will investigate utilizing publicly available datasets with immersive and/or interactive visualization techniques to create an interface between the technology and the scientific or societal problem at hand. An emphasis is placed on the selection and creation of the appropriate visualization modality (e.g. 2D or interactive vs. VR immersive) for effective exploration of the research question. This project allows the opportunity for motivated students to select a research problem based on a compelling environmental or societal problem that is of interest to them, and work through the process of evaluating the available datasets, performing statistical analysis, and designing, implementing, and evaluating a visualization. There are also several projects underway that the student can select from that use environmental, crime, or poverty/homelessness data sets. One example of an established project is an interactive virtual reality environment “A Walk along Waller Creek” done in collaboration with Dr. Mary Poteet (UT Jackson School of Geosciences) that shows correlations between water quality and fish biodiversity using a local Austin watershed Waller Creek. The REU student will access geolocated datasets concerning collected water quality sensor data and biospecimens as cataloged by the iNaturalist database. The student will investigate correlations between physical properties of water quality and aquatic life/biodiversity (using GIS, R, and python tools) and represent this correlation using immersive or interactive technologies.

Women’s health represents one of the most pressing health policy issues nationally. In no medical specialty are the deficiencies of medical evidence more pronounced than in women’s health, especially in obstetrics. Over the course of the human lifespan, birth is one of the most dangerous health episodes for both mother and baby. Worldwide, between 2.6 and 4 million pregnancies result in stillbirth annually. If stillbirths were included among the causes of human mortality, they would rank as the third leading cause of death following ischemic heart disease and stroke. Additionally, the U.S. is experiencing a health crisis resulting from decades of increasing health care expenses associated with ever-smaller improvements in health outcomes, and the development of an efficient, modern healthcare system has become an increasingly critical concern. The U.S. spends five times more per capita on health care than countries with similar life expectancies, and it has become increasingly clear that the rising number of tests and interventions do not improve health unilaterally - 5% of the population accounts for 51% of total healthcare expenditures. This project will support research in computational health, primarily researching and developing methods to support individualized medicine and risk visualization.