P.I.
BE, Vanderbilt University (Biomedical Engineering)
MS, Vanderbilt University (Biomedical Engineering)
MSCI, Vanderbilt Medical School (Clinical Investigation)
Thesis: Molecular MRI of multiple sclerosis patients using 7 Tesla scanner
PhD, Vanderbilt University (Biomedical Engineering)
Advanced imaging of spinal cord white matter
Postdoctoral Fellowship, Vanderbilt Medical Center (Radiology & Radiological Sciences)
I am a biomedical engineer and neuroimaging scientist with formal training in clinical trial research (Masters of Clinical Investigation). My research program focuses on development and clinical translation of in vivo neuroimaging techniques with the ability to relay specific information on tissue anatomy, function, microstructure or biochemistry. This encompasses evaluation of standard of care clinical image data to protocol development for advanced image acquisition and analysis to development of computational prognostic models.
My primary research initiative involves directly relating hemodynamic and anatomical imaging factors to observed sex differences in stroke lesion progression and clinical outcome. We are identifying those factors that differentiate males and females using retrospective and prospective analyses addressing the question “Are optimal imaging-selection paradigms for ischemic stroke treatment eligibility influenced by biological sex?”
My career thus far has focused on the collaborative development and optimization of imaging methods for clinical translation with focus on applications in patients with various neuropathologies. I enjoy projects that require clinical teaming to solve biomedical problems. I appreciate collaborations that help establish the knowledge breadth necessary to drive curiosity in the field of stroke research as well as those that allow me to apply my imaging expertise to help solve broader clinical questions.
Lab Members
Research Scientists
Karinne is a speech-language pathologist by training, having completed her Master’s degree at UT Austin. During her time in graduate school and with the Aphasia Research and Treatment Lab at UT Austin, she engaged in research surrounding the characterization and treatment of primary progressive aphasia. Her current research interests include developing a deeper understanding of neurodegenerative disease, stroke and healthy aging as well as methods for providing clinically relevant interventions for these populations
Residents
Undergraduate Research Volunteers
Isabella is currently a second-year undergraduate student at The University of Texas at Austin majoring in biology and minoring in art history. Outside the lab she works in the Undergraduate Office of Admission as a Texas Tour Guide. At the moment she is working on a project to outline stroke lesions using MIPAV software.
Edwin is an undergraduate student pursuing a major in Biology and a minor in Business Administration. He is interested in professional clinical research and patient care, specifically in the field of radiology. He is currently working on the analysis of stroke lesions in FLAIR imaging.
Kerryn is an undergraduate student at the University of Texas at Austin majoring in Computer Science and Plan II Honors. She is interested in leveraging statistics and data analysis to improve patient care. Currently, she is working on a project investigating sex-differences in stroke imaging and recovery using the ENIGMA Stroke Recovery Dataset.
Rohit is an undergraduate student at the University of Texas at Austin, majoring in Biology and minoring in Health Communications. He is interested in the applications of medical imaging, data merging, and statistical analyses. He is currently working on anonymizing and merging patient data and completing the statistical analyses for the correlation between acute ischemic lesions in multiple vascular territories and atrial fibrillation.
Rivaaj is an undergraduate student studying Computer Science with a Pre-Health Professions certificate. He is currently in the pre-med track, aspiring to become a doctor of neurology. His main interests include machine learning for medical and biochemical applications as well as computational neuroscience. He is currently helping develop a smartphone-based image bank for CT scans of traumatic intracranial hemorrhage.
Srivi is an undergraduate student majoring in Computer Science and minoring in Entrepreneurship. She is interested in AI in medicine, statistical modeling, and medical imaging. Currently, she is working on a research project involving perfusion imaging and image processing with lesions, applying computational techniques to analyze brain imaging data.
Pranjal is an undergraduate student at the University of Texas at Austin majoring in Computer Science. She is interested in artificial intelligence, radiology, and sports medicine. Currently, she is working on a research project analyzing physical activity and fitness in relation to brain health and age using computational techniques on the CARDIA dataset.
Nikshita is an undergraduate student at the University of Texas at Austin majoring in Computer Science. She is interested in technological applications in medicine, data science, and image analysis. Currently, she is researching how to analyze CT scans to calculate hypoperfusion intensity ratios.
Ashi is an undergraduate student at the University of Texas at Austin majoring in Computer Science. She is interested in real-world applications of machine learning and data science in medicine, such as medical imaging. Currently, she is working on a research project validating a biomarker of collateral circulation in acute stroke patients.
Angelica is an undergraduate student at The University of Texas at Austin studying Computer Science and Medicine. She aspires to become a surgeon. Currently, she is researching how cerebrovascular health and cardiovascular disease risk differs between women and men, and what role menopause may play in shaping these effects in women.
Valeria is a rising senior at the University of Texas at Austin, pursuing a B.S. in Neuroscience along with a teaching certificate in Life Sciences. This summer, they are working as an intern where they will begin developing their senior thesis. Valeria’s scientific interests include lesion tracing, neuroimaging techniques, and exploring differences in aphasia presentation between monolingual and bilingual stroke survivors.
Anabella is a rising senior at Lake Travis High School. She will be applying to college in the fall as she plans to pursue medicine, specifically oncology. This summer, she will work with Dr. Dula to explore neuroimaging techniques and further analyze stroke survivors.
Ryan is a third-year student at the University of Texas at Austin, pursuing a B.S. in Computer Science and Computational Biology. Ryan's research interests include AI in medical imaging and clinical outcome predictions.
Adriana Rodríguez-Aponte is a rising second year medical student at Universidad Central del Caribe - School of Medicine in Puerto Rico. This summer, Adriana will be contributing in the project focused on neuroimaging and stroke lesion tracing. Her medical interest include women’s health, neuroscience and imaging techniques.
Alumni
Dhriti graduated from the University of Texas at Austin, majoring in Computer Science and pursuing a certificate in Core Texts and Ideas in Fall 2023. Her interests include machine learning and its applications, especially in the medical sphere. She worked on a project that will allow people to upload brain scan images from their smartphones and automate the detection of stroke lesions.
She is currently interviewing for a position in software engineering.
Aditya was an undergraduate researcher studying Computer Science and Mathematics at the University of Texas at Austin. His interests include computer vision algorithms in medical image segmentation. His project focused developing deep learning models for segmentation of MRI images of stroke patients to determine the final infarct volume on the FLAIR image.
Aditya has graduated from UT Austin and is a co-founder of a startup in the Technology, Information, and Media space.
Breanna “Rylie” McQueen, a recent graduate from The University of Texas at Austin, holds a degree in psychology and a certificate in pre-health professions. Her journey with the Dula Stroke Lab began in the Spring of 2022, and she remained an integral part of the lab as a research affiliate during her gap year in Austin. Rylie's unique research interests are deeply rooted in her personal experience as a stroke survivor. Her work spans a wide spectrum, from investigating sex differences in stroke symptoms to delving into the intricacies of Circle of Willis variations. With a strong desire to contribute to the medical field, Rylie is joining the Cognitive Neuroscience and Human Neuroimaging master's program at The University of Sheffield. This will support her goal to further her quest to advance patient care and make a meaningful impact on the world of healthcare.
Geoffrey was an undergraduate studying Computer Science and Computational Biology at the University of Texas at Austin. He is specifically interested in applications of computation in neuroscience and medicine. He worked on processing and analyzing fMRI imaging to better understand factors impacting stroke risk and severity.
He has graduated with a degree in Computer Science and Computational Biology and is starting medical school at Baylor College of Medicine in Fall 2024.
Abhinav is an undergraduate studying Computer Science and Mathematics at the University of Texas at Austin. His interests include algorithm design, NLP, and data science, especially in regards to their applications to other fields of research such as medicine and classics. He currently performs data engineering and analysis to process CT images and evaluate sex differences in stroke.
Gargi is an undergraduate student majoring in Computer Science with a Pre-Health Professions certificate. Her interests include machine learning and medical imaging. She is currently working on developing a machine learning based brain age model to predict a patient’s brain age index from fMRIs.
Rohan is an undergraduate Computer Science and Mathematics double major at the University of Texas at Austin. His research interests involve deep learning and computer vision algorithms, as well as their interdisciplinary applications. His work included developing deep learning models to study collateral blood flow in ischemic stroke patients and evaluate cerebral blood flow in Long COVID patients.
Anish is an undergraduate studying Computer Science, Mathematics, and Neuroscience at the University of Texas at Austin. His interests involve clinical applications of computer vision, NLP, and the broader artificial intelligence field. He is currently conducting research on the applications of deep learning models for localization and infarct volume estimation for stroke lesions in FLAIR MRI images.
Neha is an undergraduate majoring in Health and Society at the University of Texas at Austin. Her interests include understanding sex differences in stroke.