Lab Members

Kristy K. Brock, Ph.D., D.A.B.R., F.A.A.P.M., F.A.S.T.R.O, F.A.I.M.B.E
Principal Investigator, Morfeus Lab
Professor, Imaging Physics and Radiation Physics
Founding Director, Image Guided Cancer Therapy Research Program

Tien T. Tang, Ph.D.
Research Assistant Professor

Tien joined the Morfeus Lab in 2023 as a Research Assistant Professor. She received her Ph.D. in bioengineering from Rice University. Her doctoral work focused on identifying functional imaging marker of radiation-induced damage in the brain and predicting radiation therapy response.

Tien’s current research is on using machine learning and diagnostic imaging to predict treatment outcome.

Jun Hong, Ph.D.
Imaging Physics Resident

Jun is an Imaging Physics Fellow in Imaging Physics. She received her Ph.D. in nuclear physics from Michigan State University. She became very interested in applying physics into medicine and had postdoctoral training on modeling cancer metastasis at Yale University, as well as on AI assistance for adaptive radiotherapy and toxicity analysis at Memorial Sloan Kettering Cancer Center. In her free time, she enjoys playing games with her family, oil painting and cheering for her favorite college football team.

Her current research project involves image guided liver ablation using imaging technologies to achieve more accurate and personalized treatment for the patients. The project aims to help establish the artificial Intelligence workflow with biomechanical modeling, assess the automatic segmentation of critical regions of interest and image registration performance, and analyze the clinical outcome. 

Amirreza Heshmat, Ph.D.
Postdoctoral Fellow

Amirreza is a postdoctoral fellow in the Morfeus Lab who joined the lab in October 2022. He received his Ph.D. in engineering science from the Vienna University of Technology (Austria). His doctoral work focused on computational modeling and simulation using the finite element method.

Amirreza's current research in the Morfeus Lab involves percutaneous liver tumor ablation by employing finite element modeling and simulation from image data of patients treated with the ablation approach to gain more precise and patient-specific treatment.

Bilel Daoud, Ph.D.
Postdoctoral Fellow

Dr. Bilel Daoud received his Ph.D. in advanced information technology from Kyushu University in Japan. His doctoral work focused on developing deep learning models for segmenting tumor and organs at risk, predicting dose distribution and tumor response to radiation therapy. Following his Ph.D., he served in a special appointment as assistant professor at Okayama University in Japan, where he developed deep learning models for cervical cell detection and classification and online adaptation of proton therapy in head and neck cancer. Outside of the lab, Bilel enjoys playing tennis, is learning violin and harmonica, loves to travel and to watch sports.

His ongoing research in the Morfeus Lab is focused on developing and validating AI models of intra-cervix response to therapeutic interventions and auto-segmentation of the pancreas and relevant structures.

Xinyue Zhang, M.A.
Ph.D. Student, Rice University

Xinyue is a Ph.D. student in the Computer Science program at Rice University. She received her M.A. and B.A. in quantitative economics with a minor in computer science from San Diego State University. In her free time, she enjoys traveling to different cities and visiting zoos.

Xinyue's research interest is in surgical AI. Her current research focuses on CT image registration and deformation vector field prediction with a 3D deep learning model (3D UNet). The goal of the project is to use limited image data to predict the deformation vector field accurately and efficiently in real time during surgery. 

Aashish Gupta, M.S.
Ph.D. Student

Prior to joining the lab, Aashish obtained his B.S. and M.S. from Texas Tech University, and the MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, respectively. In his free time, he likes to play tennis, Gaelic football and do weightlifting.

After 3-6 months of radiotherapy, there is an increase and decrease in the volume of liver in the region of low and high radiation dose, respectively. Aashish’s Ph.D. project focuses on developing AI based anatomical models to describe the response of liver to radiation. He plans to accomplish three major milestones in his project. Firstly, he is developing AI based contouring infrastructure to auto-contour liver segments on CT and MRI scans to quantify the volumetric change. Secondly, he plans to develop both machine and deep learning models to predict the longitudinal volumetric response of liver segments after radiotherapy. Thirdly, he plans to investigate how functional imaging modalities such as SPECT and DCE-MRI could help describe physiological and volumetric change in liver when radiation is administered. Once the segmental response of liver is clearly known, clinicians will be able to better spare the sensitive parts of liver which would decrease the risk of hepatic failure and increase the survival rate post-therapy.  

Erin Snoddy, B.A.
Ph.D. Student

Erin is a medical physics Ph.D. student at the MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences. She received her B.A. in astrophysics with a minor in English literature from Swarthmore College. In her free time, she enjoys practicing yoga, reading, watching movies, and going to concerts with friends.

Erin’s research interests are centered on correlative medical and diagnostic imaging (especially non-ionizing imaging modalities). Her current research focuses on the correlation of MR imaging with histology to determine anatomical characteristics of the breast. The goal is to use this information to improve breast reconstructive techniques for breast cancer patients who have had mastectomy procedures. 

Rebecca Lim, B.A.
Ph.D. Student

Rebecca is a medical physics Ph.D. student in the graduate program at MD Anderson. She obtained a B.A. in physics with double minors in computer science and mathematics at Washington University in St. Louis. In her free time, she enjoys skiing, doing puzzles, reading books and exploring new coffee shops.

Rebecca's research is focused on calculating lung ventilation from 4DCTs across photon and proton patients. The goal is to investigate local lung function and correlate it with dose and pneumonitis on a voxel-level basis. She will also be working on RBE modeling and investigating lung ventilation as an endpoint for RBE.

Androniki Mitrou, M.S.
Ph.D. Student

Androniki is a Ph.D. student in the medical physics program at MD Anderson. Prior to joining the Morfeus Lab as a Ph.D. student, she served as a physics assistant in the lab for two years. She completed her undergraduate degree in physics at Grinnell College in Iowa and then received an M.S. in medical physics from University of Massachusetts Lowell, where she conducted biophotonics research for breast cancer detection. She is interested in clinical medical physics, image guided therapy research, and science education. Androniki loves swimming, hosting at her home and Grinnell College alumni activities.

Mais Al Taie, M.D., Ph.D.
Research Investigator

Mais is a Research Investigator in the Morfeus Lab who joined the lab in April 2022. She received her Ph.D. in radiology and oncology from Tokyo Medical and Dental University and is a skilled and compassionate radiologist with broad clinical and research experience. Her doctoral work focused on analyzing the long-term complications of brachytherapy in patients with mobile tongue cancers. Her research found that brachytherapy is an acceptable treatment option, with low rates of long-term toxicity. In her free time, Mais enjoys spending time with family and friends, exercising, shopping, and cooking a diverse array of foods.

Her current research in the Morfeus Lab involves manual contouring of liver images and vessels annotation detection on CT images towards developing robust AI segmentation algorithms.

Caleb O'Connor, M.S.
Data Scientist

Before joining  the Morfeus Lab in July 2021, Caleb worked as an Image Scientist for L3Harris for five years. He completed his undergraduate degree in physics at University of Louisiana at Lafayette and then received an M.S. in physics, with a focus in signal processing. In his free time, he likes to watch basketball, play videos games and participate in local sporting leagues. 

His current research projects focus on deformable image registration techniques, AI implementation, and RayStation automation. He is actively involved with the COVER-ALL and STEROLAB clinical trials.

Mark Hickey, Ph.D.
Data Scientist

Mark joined the Morfeus Lab in 2023 as a data scientist. He received his Ph.D. in geophysics from Texas A&M University, where his doctoral research included finite element modeling, inverse theory, and subsurface fluid monitoring. In his free time, he enjoys tinkering with maker projects, playing video games and exploring the outdoors.

His research in the Morfeus Lab focuses on biomechanical modeling of brain shift during neurosurgery using finite element analysis.

McKell Woodland, Ph.D.
Data Scientist

McKell joined the lab as a Data Scientist in August 2024 after earning her Ph.D. in the Computer Science Program at Rice University. Her thesis work was also completed the Morfeus Laboratory. She received her B.S. in applied and computational mathematics with a minor in computer science from Brigham Young University. She has interned in data science roles at Microsoft, Lawrence Livermore National Laboratory, 3M Health Information Systems and the National Security Agency. In her free time, she enjoys outdoor adventures and time with family.  

Deep learning models typically fail on inputs that are far from the model’s training distribution. McKell’s research focuses on utilizing model features and generative adversarial networks (GANs) to detect these out-of-distribution inputs. Her research has applications in warning clinicians when a deep learning-based segmentation model likely failed, flagging which images should be reviewed when large amounts of data are automatically segmented, determining which images in large cohorts of data would have the most utility to label, and improving datasets and model capabilities over time by diversifying data. 

Austin Castelo, B.S.
Associate Data Scientist

Austin is an Associate Data Scientist in the Morfeus Lab. Before joining in March 2022, he received his undergraduate degree in financial mathematics and statistics from University of California, Santa Barbara and worked in web-based computer vision and machine learning engineering. In his free time, he enjoys reading, playing video game with friends and playing poker.

His current research project involves automated liver segmentation during liver ablation for use in image guided liver ablation. He also works within the lab to provide computational and machine learning support to other projects.

Stephanie Robles, B.S.
Research Assistant II

Stephanie graduated at the top of her class with a bachelor's degree in physics with a pre-medical concentration from Texas Southern University and transitioned into a research assistant position in Morfeus Lab in 2023. As an undergraduate, Stephanie was a full-time student-athlete and worked in the Morfeus Lab as an undergraduate research student. Before joining the lab in May 2022, Stephanie was a summer intern for the Perelman School of Medicine at the University of Pennsylvania (UPenn). At UPenn, her research focus was working with dual-energy computed tomography scans. Her current research focus in the Morfeus Lab involves manual contouring of pelvic floor images towards developing an artificial intelligence model.

She is interested in both clinical and translational research in medical physics. During her free time, Stephanie enjoys playing soccer, exploring the outdoors and volunteering with her Society of Physics club.

Kari Brewer Savannah, Ph.D.
Director, Image Guided Cancer Therapy Research Program 

Kari Brewer Savannah, Ph.D., joined the IGCT in Fall 2020 and serves as the Program Director. Dr. Savannah holds a B.S. in chemistry from Hillsdale College and a Ph.D. in biochemistry and biomedical sciences from the MD Anderson  Cancer Center UTHealth Houston Graduate School of Biomedical Sciences. She previously served as Assistant Professor at the University of Texas at Brownsville (Biomedicine Department) and Houston Baptist University (Biology Department). Dr. Savannah has significant experience in the design, management, and assessment of research training programs, educational programming, and in initiatives to expand diversity, equity, and inclusion for underrepresented minorities in STEM fields. Dr. Savannah brings a strong background in research administration, scientific project management and program management to her role in the IGCT and Morfeus Lab. She manages large, multidisciplinary scientific projects, assists in multi-investigator grant preparation and management, and manages IGCT/Morfeus Lab classified staff.