The DIY Diagnostics Stream is part of the Freshman Research Initiative, a program that teaches students science through independent research experiences, in the College of Natural Sciences at the University of Texas at Austin. We are part of the do-it-yourself (DIY) health diagnostics revolution, developing diagnostic tests and building visual interfaces to improve patient health.
February 13, 2015COURSE CREDIT Spring Semester: (BIO 206L with BIO 102C) or (CH 204 with CH 108) Syllabus from Spring 2014 Fall Semester: BIO 377, CH 369K, CS 378 Who is this stream for? This is a young stream ...
DIY Stream Video
February 12, 2015
February 6, 2015If you have any questions about what the stream is about or how to join, don’t hesitate to contact: Dr. Tim Riedel firstname.lastname@example.org Research Educator Office in Painter Hall PAI 3.04N (512) 232...
Dr. Tim Riedel
Research Educator, DIY Diganostics
I have a diverse background in developing detection platforms. This includes working with classical optical detectors, two-component signal transduction pathways, fluorescent protein expression, respirometers, and most recently quantitative PCR. I’m excited to join the FRI and look forward to seeing what the students develop.
Dr. Andy Ellington
Biochemistry and Molecular Biology Professor
The Ellington Lab is a biotechnology lab that engineers nucleic acids and proteins for biomedical and other applications. Nucleic acid biosensors (aptamers, ribozymes) and nucleic acid circuits (DNA computers) are being harnessed to diagnostic applications, especially for point-of-care diagnostics in resource-poor settings and for facile tumor detection.
Dr. Pradeep Ravikumar
Computer Science Assistant Professor
I lead the Statistical Machine Learning Group at the Department of Computer Science at the University of Texas, Austin.
DIY research featured by KVUE!
March 25, 2016DIY was featured last night by Austin’s Channel 24, KVUE! Read about it here. If you want to help DIY further their research initiatives, feel free to donate any amount here.
Help fund DIY Fellowships and Zika research
March 24, 2016Researchers within DIY Diagnostics are working diligently to create diagnostics for some of the world’s most notorious illnesses. Within the scientific community, funding is instrumental to any ...
DIY in the Daily Texan!
February 1, 2016Check out our article in the Daily Texan! http://www.dailytexanonline.com/2016/01/26/ut-researchers-working-to-create-diagnostic-tool-to-assess-viruses-such-as-zika
In the Spring 2014 semester, 34 freshmen along with 7 upper-division mentors completed a series of skill development exercises that produced authentic data on a wide range of topics including the diversity of the student’s oral microbiome, the public health of the creek on UT campus, and the diagnostic potential of molecular techniques on saliva.
The DIY Diagnostics FRI stream is made possible thanks to the continuous financial support of Bob and Cathy O'Rear. Additionally, DIY has a strong history of collaboration with labs, companies, agencies, foundations, and other stakeholders who have generously donated money, expertise, or reagents to the students of DIY.
Texas Memorial Museum
We are grateful to the Texas Memorial Museum for sponsoring 2 summer fellowships under the Joseph Jones Life on Waller Creek endowment. Additionally, TMM has sponsored numerous undergraduate research awards at the Undergraduate Research Forum.
The success of the DIY Diagnostics stream research is in no small part due to the continuous support of the Ellington Lab.
Bob and Cathy O’Rear
The DIY Diagnostics FRI stream is made possible thanks to the continuous financial support of Bob and Cathy O’Rear.
The DIY Diagnostics Stream is made possible thanks to a generous donation from Bob and Cathy O’rear.
DIY is supported by the Freshman Research Initiative and the University of Texas at Austin.
Students researchers learn basic coding principles and create web-based mobile apps. Smart phones possess powerful diagnostic potential with their computational power, communication capabilities, sensors, and image processing power. We aim to leverage these powers into useful products. Below are a few of our more developed products. These apps should work on a computer or mobile device and do not require any installation. These are beta level apps that may have flaws and, of course, should not be used for any real medical diagnoses.