I am working as a postdoctoral researcher at Houston Methodist Research Institute on developing novel deep learning models adapted to diffusion MRI

I am presently a PhD student in Electrical and Computer Engineering at the University of Arizona. My research focus involves applying artificial intelligence and deep learning models and adapting them to create novel, advanced, and adaptive medical imaging protocols for image reconstruction. I have a Master's in Optical Sciences at the University of Arizona and a Bachelor's in Physics from the University of West Georgia.

Imaging modalities such as Magnetic Resonance Imaging (MRI) are utilized to image various biological and anatomical structures as well as physiological functions. Acquiring these data lead to the detection, diagnosis, and treatment of disease(s). However, the ability to perform these functions at a high efficacy rate requires high quality and resolution images. The process of acquiring such images is a challenging task through conventional image processing techniques. In the case of MRI, this… Show more Imaging modalities such as Magnetic Resonance Imaging (MRI) are utilized to image various biological and anatomical structures as well as physiological functions. Acquiring these data lead to the detection, diagnosis, and treatment of disease(s). However, the ability to perform these functions at a high efficacy rate requires high quality and resolution images. The process of acquiring such images is a challenging task through conventional image processing techniques. In the case of MRI, this imaging modality is highly sensitive to subject motion, which leads to motional-induced artifacts. This is primarily due to the large amount of time it takes to acquire sufficiently large data to output a high-quality image. Thus, the problem that needs to be addressed is how to achieve high quality and resolution images without exposing subjects to prolonged scan times or having to compromise image quality. This is where artificial intelligence and deep learning come into play. In this position I am devising deep convolutional neural networks and developing novel and vendor-agnostic imaging protocols that can greatly decrease scan times and improve image quality and resolution. Show less

Research at the University of Arizona Department of Medical Imaging involved the investigation of the feasibility of using a fluorescence optical imaging technique for the application of in vivo flow cytometry. Comparison and evaluation of three system configuration were used to image fluorescence labeling of cancer cells using a folate receptor targeted contrast agent, OTL38, which fluoresces in the NIR band ~780 nm and has an emission spectrum of ~810 nm. Quantitative analysis was performed… Show more Research at the University of Arizona Department of Medical Imaging involved the investigation of the feasibility of using a fluorescence optical imaging technique for the application of in vivo flow cytometry. Comparison and evaluation of three system configuration were used to image fluorescence labeling of cancer cells using a folate receptor targeted contrast agent, OTL38, which fluoresces in the NIR band ~780 nm and has an emission spectrum of ~810 nm. Quantitative analysis was performed to compare relative optical system throughput and SNR of all three systems. Qualitative analysis was performed to establish a minimum SNR required to effectively image and detect cells. Show less

Research Assistant, Department of Physics, University of West Georgia. Responsibility: Researching high temperature iron-based superconductors, conducting neutron diffraction experiments at Oakridge National Laboratory and analyzing miller indices of the lattice structures and their magnetic structures.

Research Assistant, Wallace H. Coulter Department of Biomedical Engineering at Emory University and Georgia Institute of Technology. Supervisor: Xiaoping Hu, PhD, Puneet Sharma, PhD, and Diego Martin MD PhD. Responsibility: Researched Nuclear Accoustic Resonance. Assisted in background theory and preliminary theoretical assessment deriving quantum mechanical modeling of MR energy deposition in tissue.

Research Assistant, Department of Radiology, MRI Research Program, Emory University. Supervisors: Diego Martin, MD PhD and Bobby Kalb, MD. Responsibility: Completing data analysis concerning enhanced gadolinium-contrast MRI protocols to reduce risk of Nephrogenic Systemic Fibrosis (NSF).