HSRA Research Experiences

Researchers isolate an RNA molecule, called an aptamer, through the in vitro aptamer selection process. In essence, students will sieve a haystack for the few pieces of hay, aka aptamers, that bind a specific protein target. Through this sieving or selection process, researchers will learn technical skills like: micropipetting, amplification of DNA through the PCR reaction, generation of RNA through a transcription reaction, purification of DNA/RNA using a variety of techniques, visualization of DNA/RNA using gel electrophoresis, and more! Participants can expect to collaborate with a small team, receive mentorship from undergraduates and faculty, analyze real data, develop strategies for overcoming obstacles found when conducting real research, and communicate the results of their research findings.

Build with biological LEGOs of genetic information.

Participants will be introduced to laboratory skills including PCR, DNA mini prep, transformation, recombinant protein expression, recombinant protein purification, and western blot analysis, and how these techniques are applied to molecular and biochemical research. Students will have the opportunity to participate in a current research project with undergraduates, learn scientific communication and how to prepare a research poster. 

Identify mutations found in tumors. 

Participants will investigate the relationship between alterations in gene expression and the development of cancer, specifically looking at genes with suspected but unconfirmed roles in carcinogenesis.  Projects involve using a variety of molecular biology techniques to construct DNA molecules to facilitate the study of specific mutations found in tumors.  Expressing mutated proteins can allow for detection of changes in gene expression and cell growth and behavior.

Create DNA circuits to genetically engineer bacteria.

Students will work on one of our various projects, which include working with Cyanobacteria, bacteria found in bees, or E. coli.  We will design DNA sequences in silico and then conduct benchwork, including molecular biology techniques (such as PCR and genetically modifying bacteria) and microbiology techniques (such as culturing bacteria).  Students will also read scientific literature with guidance and present their work to undergraduate researchers and faculty. 

Discover new chemical compounds involved in infectious diseases. 

Participants will be involved with computational and wet-laboratory infectious disease drug discovery projects, such as tuberculosis, malaria, and SARS-CoV-2.  First, a molecular docking program is used to sift through libraries of chemical structures and predict which ones may bind to a protein that is a potential drug target. Results are visually analyzed with a molecular graphics program and ranked according to predicted binding affinity scores. Then, DNA cloning and protein expression protocols are implemented in the lab to test the top potential drugs in enzyme assays. HSRA students will primarily focus on developing wet lab skills to produce the target proteins in a lab strain of E. coli bacteria.  We will also focus on obtaining skills in molecular visualization software.

Probe the neurogenetic basis of alcohol addiction. 

Participants will be introduced to the Drosophila melanogaster system and research in fly behavior. They will be trained in various behaviors (e.g: courtship behavior, male aggression, learning and memory, alcohol sensitivity) as well as experimental procedures, data collection, analysis and interpretation, with the purpose of exploring gene function in behavior. Students will learn to read and interpret the literature connected to the behaviors and gene they are investigating in the laboratory, collaborate with undergraduates, and get exposure to data analysis using R statistical analysis software. 

Explore how cells communicate with each other in plants. 

The central question to our research will focus on is how extracellular ATP functions like a hormone-like signal in animal and plant cells. The experimental system used in their research is the model plant Arabidopsis. Specifically, students will learn the techniques needed to work independently in the lab and will then perform their own novel experiments aimed at discovering early signaling steps by which extracellular ATP regulates the opening and closing of stomatal pores in Arabidopsis leaves. In the process of doing research, students will practice methods of experimental design, data gathering, statistical analysis, data interpretation, and data presentation.

Genetic engineering of plants as biosensors and reporters of environmental toxins.

Our lab works on a mix of basic and applied research projects in plant biology. One example of an applied project students can work on we call the “diagnostic plants” project. This project seeks to couple a plant’s natural ability to produce colorful pigments with the plant’s ability to detect heavy metal toxins in the soil or water. Students will learn about and apply a variety of molecular cloning and plant genetic techniques towards the engineering of a plant that can “report” the presence of environmental toxins via the expression of pigments in the plant body. Besides molecular biology lab skills, students will also learn to document and analyze data, read scientific literature and communicate their work.

Use light to create the next generation soft materials.

Soft materials, such as plastics and other polymers, are ubiquitous in our everyday lives, however their production requires large amounts of energy, often in the form of heat. Light represents an abundant and renewable alternative energy source for soft materials fabrication, yet contemporary light-driven industrial chemistry relies on the use of high energy, intense ultraviolet (UV) rays. To overcome these hurdles, our research explores the use of organic dyes as efficient visible light-activated catalysts to generate next generation soft materials. As part of this research group, participants will learn how to characterize the optical properties and reactivity profiles of colorful molecules (dyes) to determine governing principles that improve the efficiency of soft material production using visible light.

Explore a new approach to selective molecular recognition.

Our lab seeks ways to implement existing organic chemistry techniques in the creation of novel sensing protocols using modern analytical devices. These protocols are designed to be effective, rapid, and readily usable in any academic lab or industrial setting. HSRA participants will learn the basics of organic synthesis and modern analytical chemistry techniques to help develop fast and cheap sensors that are easy to implement can provide very helpful solutions to real everyday problems!

Develop better materials for fuel cells and batteries.

Participants will be introduced to computational material science, one of the most interdisciplinary fields! Research is specifically focused on developing better materials for fuel cells and batteries, and more importantly methodologies for material analysis and discovery, ideally automagically. Students will be exposed to all the required knowledge in physics, mathematics, chemistry, and computer science from a community of undergraduates and faculty. Specifically, students will learn how to: write python scripts for simple task automation, write python optimizers that produce relaxed molecular structures with Lennard-Jones potentials or perform non-linear fitting, use Density Functional Theory software (VASP) to simulate simple chemical reactions and surface catalytic reactions that take place in fuel-cells and model ion diffusions in Li-ion battery cathode materials, and much more.

RobIn Lab is directed by Roberto Martín-Martín, and is part of the University of Texas at Austin, Department of Computer Science, UTAI Lab and Texas Robotics.

The research in RobIn explores at the intersection of robotics, computer vision and machine learning, with an emphasis on creating robotic solutions that accomplish interaction-rich tasks in the real world. Our research revolves around the question: what are the mechanisms that enable physically intelligent behavior in embodied agents? Our hypothesis is that intelligence is not a purely computational process, but an interplay between perceiving, reasoning, learning and interacting physically with the world.

Investigate the structure and motion of star clusters, galaxies, and clusters of galaxies. 

Students will learn to use powerful Data Science tools in Python like Jupyter Notebooks, NumPy, SciPy, MatPlotLib, and Pandas, and will apply these tools to datasets that professional astronomers use like SDSS (Sloan Digital Sky Survey), NED (NASA Extragalactic Database), and GAIA. The concepts in astronomy that students will be dealing with are simple and deep - and students will spend time developing the necessary programming and data analysis skills in order to deepen our understanding of the universe and our place in it.

Develop the latest at-home diagnostics.

Researchers will be working on developing and applying state-of-the-art diagnostic technologies to water sources around Austin. Specifically, we will be attempting to perform "creek-side" diagnostic tests. These tests are well established but are normally performed in a full laboratory setting. By attempting them out of the lab, we will better understand the limitations/strengths of diagnostics in both environmental and low resource healthcare settings.

Participate in innovation that crosses STEM disciplines! 

Participants will learn to apply a variety of technical skills to design and create their own individual projects. The Makerspace is home to a variety of 3D printers, laser cutters, and electronic components, all of which students will learn how to operate with the help of experienced undergraduates. The focus of the lab is to encourage ingenuity and innovation across multiple disciplines. Previous projects have included robotics, an environmentally friendly wind-powered boat, prosthetic arms, water quality sensors, and much more. Students will develop valuable STEM skills such as problem-solving and creative thinking that will be represented in their individual projects.

Investigate human impact on the quality of Austin watersheds.

Participants will focus on research related to understanding urban nature. We study the microbiology, macrobiology, molecular biology, chemistry, and ecology of urban ecosystems. The Water Quality project collects samples along Austin's creeks to understand how human activity impacts the organisms that we share our city with. We focus on general measures of water quality and habitat quality as well as looking for contaminants. Experiments include measuring tree canopy; identifying aquatic insects; quantifying aquatic microbes; measuring basic water chemistry such as pH, conductivity, nitrates, and phosphates; and assessing riparian habitats. Students will be embedded with ongoing research projects working in both the field and the lab and will perform experiments alongside experienced undergraduate researchers and faculty. 

Environmental Chemistry 

Participants will focus on research related to understanding urban nature. The Environmental Chemistry project collects samples along Austin's creeks to understand how human activity impacts the organisms that we share our city with. We use analytical chemistry to detect and quantify the amounts of various pollutants in various environmental samples, including creek water, sediment, and biofilms. Students will be embedded with ongoing research projects and will perform experiments alongside experienced undergraduate researchers and faculty collecting samples from Waller Creek, which runs through the UT campus.

Exploratory Data Analysis

Our Exploratory Data Analysis project will introduce you to the field of data mining. Our collaboration with the US Geological Survey studies the enormous RSQA database of measurements of environmental chemical and biological metrics, using samples collected from almost 500 streams across the country over a five-year period. We will teach you to program in R, a statistics and visualization language, to create visualizations, and perform statistical and multivariable analysis to answer an environmental research question of your own. No experience in statistics required, though we recommend that you have either had some computer programming experience or have the interest to work hard on learning the basics quickly.