Faculty
Nicolas Honnorat, Ph.D.
Assistant Professor
Nicolas Honnorat received his Engineering Degree, his M.Sc., and his Ph.D. from the Ecole Centrale Paris in 2008 and 2013. After a five-year postdoctoral fellowship at the University of Pennsylvania and a three-year mission as a research scientist at SRI International, Nicolas joined the University of Texas Health Science Center at San Antonio in 2021 as a research instructor. His primary research interests are in image processing, optimization, and machine learning, with a specific interest in the analysis of MRI images and extensive expertise in studying functional MRI data. His current research projects aim at modeling the impact of neurogenerative diseases on the brain by analyzing large multimodal neuroimaging datasets and combining in-vivo and postmortem neuroimaging
Staff
Tanweer Rashid, Ph.D.
Research Scientist
Tanweer Rashid received his BSc in Computer Engineering from North South University, Dhaka, Bangladesh. He completed his MSc and PhD in Modeling and Simulation from Old Dominion University in Norfolk, VA, USA. He has previously worked on the development of algorithms for 2-manifold surface mesh generation and multi-material deformable surface meshes. Tanweer has also done research work in functional MRI analysis for Parkinson’s disease subjects treated with deep brain stimulation. Tanweer’s primary research interests are in machine learning/deep learning and their applications in brain aging, small vessels disease, postmortem brains and neurological disorders such as Parkinson’s and Alzheimer’s disease. He is currently working on developing deep learning algorithms for the detection of cerebral microbleeds, enlarged perivascular spaces, infarcts and other types of small vessels diseases, and for the identification of potential biomarkers related to Alzheimer’s Disease.
Crystal Franklin, M.Sc.
Statistician-Intermediate
I received my BS in Biology from Texas State University, San Marcos, TX in 2000. Following graduation, I began working at the Research Imaging Institute at UT Health San Antonio. I play a major role in the processing and analysis of functional and structural magnetic resonance imaging, positron emission tomography and clinical data using highly sophisticated computer systems, statistical software tools, and algorithms for multiple funded imaging projects. In addition, I train faculty, post docs, students and incoming staff procedures and software used for analysis. I enjoy learning new techniques and software for processing and interpreting neuroimaging data.
David Michael Martinez, Ph.D.
Project Manager
David Martinez received his BA in Psychology from Baylor University in Waco TX. His MSc is in Applied Cognition and Neuroscience, and his Ph.D. is in Psychological Sciences, both from The University of Texas at Dallas. David has worked in the fields of psychology, cognition, and neuroimaging, with a particular focus on clinical populations. David has managed imaging trials at both the University of Texas at Dallas and the University of Texas Southwestern Medical Center. David also has experience in managing pharmaceutical clinical trials as a manager for North Texas operations. Before entering graduate school in Dallas, David worked in the Research Imaging Institute at UT Health San Antonio and has returned to his current role as Project Manager for the Neuroimaging Core with the Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases.
Sachintha Ransara Brandigampala B.S.
Imaging Data Analyst
I'm an electrical and computer engineering graduate from University of California, San Diego with a research background in medical imaging. I have experience conducting research in medical imaging and have published articles on data augmentation methods for object detection and segmentation in ultrasound scans. My expertise includes statistical analysis and machine learning/deep learning techniques. I'm dedicated to advancing medical imaging technology to improve diagnosis, treatment, and patient outcomes.
Marco Boisselier, B.S.
(co-supervised with Tiffany Kautz)
received his BS in Neuroscience with a minor in Chemistry from Trinity University, San Antonio, TX in 2023. He previously worked in Dr. Kimberley Phillips' lab for four years developing a protocol to analyze and interpret PET-CT scans of Common Marmoset monkeys (Callithrix jacchus) using PMOD software. The project sought to determine the extent to which loneliness or social isolation contributed to cognitive decline. His current research interests include neurodegenerative diseases, neuroimaging analysis, biomarker identification, and cerebrovascular contributions to aging. He currently splits his time between the Biobank lab and the Neuroimaging Analytics lab where he helps with postmortem MRI-guided histopathology analyses.
Postdocs
Karl Li, MD/PhD
(co-supervised with Sudha Seshadri)
Karl received his MD/PhD from the University of Texas Health at San Antonio. For his PhD training, he worked in Dr. Peter Fox's lab, where he did his dissertation on assessing functional connectivity changes in the default mode network with normal aging as well as other common comorbidities to better understand normal aging without neurodegenerative disease.
My work sought to establish a functional connectivity biomarker of the default mode network to search for potential early indicators of neurodegenerative conditions.
Di Wang, PhD
I started my medical imaging research in 2016 at the Center for Advanced Imaging Innovation and Research of New York University. In the subsequent year, I obtained master's degree in biomedical engineering from New York University. In 2018, I started my PhD in biomedical engineering at the Research Imaging Institute of the University of Texas Health Science Center at San Antonio. I have acquired extensive knowledge regarding medical imaging processing, statistical analysis, and machine learning/deep learning. Currently, my work and interest are focused on understanding and analyzing medical imaging using innovative machine learning and deep learning methods.
Ngoc-Huynh (Henry) Ho, PhD
a postdoctoral research fellow at UT Health Science Center at San Antonio, specializing in developing machine learning algorithms for diagnosing neurodegenerative diseases. Holding a PhD in AI Convergence from Chonnam National University, South Korea, he has extensive experience developing deep learning models for disease progression prediction and emotion recognition using multimodality. His work is recently dedicated to advancing healthcare through innovative AI solutions."
Mengjin Dong, PhD
Finished her Ph.D. study in August 2023 at the University of Pennsylvania, supervised by Professors Paul Yushkevich and David Wolk. Her research primarily focuses on developing robust deep learning methods for longitudinal analysis of Alzheimer’s disease progression. She is interested in using modern learning-based techniques to understand the mechanism and interaction of different biomarkers in Alzheimer’s disease and related disease. In addition to her dissertation work, she has also interned as a machine learning engineer at Siemens and Amazon Inc.
Niyas Shamsudeen Kutty, PhD
received his B. Tech in Electronics and Communication Engineering and M. Tech in Signal processing from CUSAT University, India, in 2011 and 2014, respectively. He earned his Ph.D. in 2024 from the Department of Computer Science and Engineering at the National Institute of Technology Karnataka (NITK), India. His research focuses on image processing and deep learning for detecting and quantifying abnormalities in medical imaging, particularly CT and MRI. Niyas has gained significant experience working in reputed research institutions and startups, where he has contributed to brain data analysis and related fields. He is currently developing deep learning algorithms for the detection of cerebral microbleeds, iron deposits, and other small vessel diseases, as well as identifying potential biomarkers associated with Alzheimer’s disease.
Residents
Sokratis M Charisis, MD
I am currently a resident in the Department of Neurology at UT Health San Antonio. Following the completion of my medical degree, I undertook a 2.5-year epidemiology and clinical research fellowship at the University of Athens, Greece, during which I received training in Epidemiology and Population Health from the Department of Epidemiology at the University of Athens, Greece, and extensive training in applied statistics at the Hellenic Mathematical Society (HMS). My research is focused on the investigation of imaging, metabolic, and genetic biomarkers in neurodegenerative diseases and healthy aging, by utilizing data from large epidemiological studies such as the Framingham Heart Study and the Multi-Ethnic Study of Atherosclerosis. In particular, I am interested in identifying certain genetic signatures, and subtle alterations in brain structural and functional measures as well as in metabolic homeostasis that are associated with early neurodegenerative changes and vascular brain injury. I feel proud and privileged to be part of NAL, where we leverage state-of-the-art AI tools to make groundbreaking discoveries in neuroimaging research.
Ph.D. Students
Mariam Mojtabai
I received my BS (2020) and MS (2022) in Physics with a focus in astrophysics from New Mexico Institute of Mining and Technology. My interest in imaging led me to pursue a PhD in Radiological Sciences, specializing in Medical Physics with a concentration in imaging at the University of Texas Health Science Center in San Antonio. My current interests are in medical image processing and analysis along with machine learning/deep learning.
Yuheng Zeng
I earned a BS in Physical Therapy from Sichuan University, China (2022), and an MRes in Advanced Neuroimaging from University College London, UK (2024). My clinical and research experiences motivated me to pursue a PhD in Biomedical Engineering at UT Health San Antonio, focusing on translational neuroimaging. I am particularly interested in utilizing machine learning techniques to identify neuroimaging biomarkers, aiming to advance clinical treatments and facilitate drug discovery.
Faiza Azhar
I received my Bachelor’s degree in Software Engineering in 2015 and my Master’s degree in Computer Science in 2020, both from Sukkur IBA University, Sukkur, Pakistan. During my master’s thesis, I worked extensively on image processing, with a focus on machine learning and deep learning techniques. My current research interests lie in biomedical imaging, specifically in the application of machine learning and deep learning to process and analyze MRI images as part of my PhD studies.
Constance Alexia Zanze
Constance earned a Bachelor of Science in Physics with a specialization in Biophysics and a minor in Chemistry from the University of California, San Diego. Her undergraduate work involved coding MATLAB simulations to analyze the effect of ER tubule radius on network transport and she engaged in neural network research. Building on this technical foundation, she gained clinical experience by shadowing at UC Health on the TrueBeam machine and at the proton center, assisting with quality assurance and reviewing patient safety measures. These experiences have led her to pursue a Ph.D. in Radiological Sciences on the Medical Physics track at UT Health San Antonio, where she is focusing on Medical Imaging and conducting research related to Alzheimer’s disease. She is currently learning about using MRI images to create and train a model.
M.D. Students
David Haoyuan Wang
I received my BS in Biomedical Engineering from the University of Texas at Austin, and I am a MS1 at the Long School of Medicine at UT Health San Antonio. My work with neurology patients at Ascension Seton motivated me to enter the field of medicine and is where I decided to dedicate my career to the field of neurology. I am interested in the development of prognostic tools for the progression of Alzheimer’s.
Morgan Fox Torres
Morgan Fox Torres obtained his Bachelor’s degree at Texas A&M International University. Upon graduation, he became a medical student at the Long School of Medicine at the University of Texas Health Science Center at San Antonio. He enjoys helping underserved communities, such as in Laredo, Texas, where he volunteers his time helping host health screenings, and researching barriers to healthcare access in such communities. He has a goal of becoming a radiologist with a sub-specialization in neuroradiology. Driven by a fascination with the brain's complexities, Morgan is currently dedicated to research focused on identifying cerebral microbleeds. This work aims to assist with machine learning and contribute to the diagnosis and treatment of neurological conditions. Morgan aspires to contribute significantly to the field of neuroradiology, enhancing patient care through innovation and research.
M.D./Ph.D. Students
Je Ryong Im
I received my BS in Chemical Engineering at Yale University (2023), and now am a first year medical student at the Long School of Medicine at UT Health San Antonio in the Medical Scientist Training Program. My post-baccalaureate work in ultrasound research got me interested in medical imaging, and now I hope to pursue a PhD in Radiological Sciences. My current research interests are in medical image processing and machine learning. During my free time, you can find me volunteering at the San Antonio Refugee Health Clinic.
Alumni
-
Yuhan Cui, M.Sc. Data Analyst. New position: bioinformatician at CBICA.
-
Haykel Snoussi, Ph.D. Image and Data Analyst. New position: postdoctoral fellow at Baylor.
-
Hangfan Liu, Ph.D. Postdoc. New position: assistant professor at University of Maryland.
-
Elyas Fadaee, M.D. Postdoc. New position: resident at Texas Institute for GME and research.
-
Anoop Benet Nirmala, Ph.D. New position: assistant professor at Manipal University.