Residents, Fellows & Alumni

Hussein Akafzade, Ph.D. 
Ph.D., 2020, UT Arlington
M.S., 2011, Isfahan University of Technology
B.S., 2008, Tabriz University

Research Mentor:  Tinsu Pan, Ph.D.

Research Interests:  The accuracy of PET/CT registration is affected by respiratory motion. Dr. Pan’s lab is focused on using data-driven gating (DDG) method to provide more reliable quantitative thoracic imaging. This is important in precise localization and severity assessment of the lesions.

Yan Dai, Ph.D.
Ph.D., 2026, UT Southwestern Medical Center
B.S., 2020, Nanjing University

Research Mentor: Research Mentor: Ho-Ling Anthony Liu, Ph.D.

Research Interests: Dr. Dai joins the Liu lab and works on developing and validating advanced MRI techniques for measuring the physiological and functional status of the brain in cancer patients, with clinical applications in tumor characterization, presurgical planning and post-treatment outcome prediction. Specific techniques of interest include functional MRI and DTI connectomes for predicting neurocognitive and functional outcomes, and non-contrast MRI methods for quantitative assessment of glymphatic function.

Rachel Glenn, Ph.D.
M.S., 2024, UT Health/MD Anderson
Ph.D., 2012, University of Utah
B.S., 2008, Weber State University

Research Mentor: David T. Fuentes, Ph.D.

Research Interests: Dr. Glenn's research centers on diffusion MRI and biopsy-anchored radiomics for in-vivo characterization of gliomas. By integrating ADC mapping with multiparametric MRI (T1, T1-post, T2, FLAIR, DWI/DTI) and neuronavigation-registered stereotactic biopsies, the lab develops quantitative, voxel-level models of tumor cellularity and proliferation (e.g., Ki-67) with calibrated uncertainty. Methodological interests include feature harmonization, uncertainty-aware machine learning (from random forests to quantum-constrained matrix learning), and translation of these tools for image-guided biopsy targeting, grading, treatment planning, and longitudinal response assessment.

Hamidreza Hemmati, Ph.D.
Ph.D., 2018, Beheshti University
M.Sc., 2012, Beheshti University
B.Sc., 2009, Qazvin University

Research Mentor: Tinsu Pan, Ph.D.

Research Interests: Research is centered on advanced hybrid imaging technologies, including PET/CT, MR-based systems, and molecular imaging with emphasis on techniques that combine anatomical and functional information. Areas of focus include signal and data processing, image recovery and correction, system modeling. Applications involve motion-compensated imaging, data-driven gating, time-of-flight PET, and the integration of AI to enhance diagnostic precision and support image-guided therapy. Efforts are directed toward translating innovative imaging solutions into clinically impactful tools that improve both diagnostic precision and therapeutic outcomes, ultimately advancing patient care and accessibility.

Humberto Monsivais, Ph.D.
Ph.D., 2024, Purdue University
M.S., 2021, Purdue University
B.S., 2015, Stephen F. Austin State University

Research Mentor: Brian A. Taylor, Ph.D.

Research Interests: Advanced neuroimaging tools can be used to gain a better understanding of the neurocircuitry and physiology of substance use disorders (SUDs), aiding in the development of targeted treatments for affected patients. In collaboration with the Department of Behavioral Science, our work employs a multi-parametric approach to explore the modeling of attentional bias and craving in nicotine users via structural, functional, and neurochemical measurements from MRI. My work will focus on assessing structural changes, like cortical thickness and grey matter volume, and understanding how neurotransmitters such as GABA and glutamate influence neuronal connectivity in SUDs. This research aims to shed light on the underlying neurobiology and support the development of more effective treatments.

Augustino Scorzo, Ph.D. 
Ph.D., 2025, Dartmouth College
B.S., 2021, Rowan University

Research Mentor: Kristy K. Brock, Ph.D. 

Research Interests:The Morfeus Lab focuses on developing and applying image guidance technologies to improve cancer therapy across radiation oncology and surgery. Augie’s research in the lab centers on leveraging co-registered diagnostic imaging modalities to 1) visualize vasculature for applications in image-guided surgical interventions and 2) evaluate osteoradionecrosis through the integration of cryo-fluorescence tomography and correlative pathology. This research aims to enhance anatomical visualization and improve our understanding of treatment-induced tissue changes.

Mahsa Servati, Ph.D.
2026-2027 Chief Resident
Ph.D., 2024, Purdue University
M.Sc., 2020, Purdue University
M.Sc., 2018, Texas Tech University
B.Sc., 2015, Sharif University of Technology

Research Mentor:  C. Chad Quarles, Ph.D.

Research Interests:  The Quarles Lab focuses on a broad spectrum of imaging science, including biomarker discovery, image-based preclinical mechanistic studies, clinical therapy response assessment, multi-scale systems analysis, image-guided surgery and radiotherapy, advanced image analysis (e.g., radiogenomics, deep learning solutions), multi-modality prognostication (e.g., imaging and liquid biomarkers), PET/MRI, radiotracer development, and the development of acquisition and analysis tools for clinical integration.

Linying Zhan, Ph.D.
Ph.D., 2026, University of Wisconsin - Madison
M.S., 2024, University of Wisconsin - Madison
B.Sc., 2022, The University of Hong Kong

Research Mentor: Ke Li, Ph.D.

Research Interests: Photon-counting detector CT and cone-beam CT have the potential to improve cancer diagnosis and treatment by enabling more accurate lesion localization, characterization, and treatment planning. Our research aims to further improve image quality and quantitative accuracy while expanding the clinical applications of photon-counting imaging to better address the needs of diagnostic imaging, surgery, and radiation therapy.