Radiology
Showing 51-87 of 87 Results
-
Magdalini Paschali
Postdoctoral Scholar, Radiology
Current Research and Scholarly InterestsMy research focuses on utilizing machine learning models to enhance the understanding, diagnosis, and treatment of clinical disorders. I am interested in multi-modal learning, combining imaging data like MRI and CT scans with non-imaging data such as electronic health records, creating more holistic and accurate diagnostic models. I am also interested in the robustness of deep neural networks under domain shifts, investigating how models perform when faced with changes in input data distributions.
Finally, I am interested in early biomarker identification using AI model interpretability, to enable the early detection and targeted treatment of chronic disorders. -
Suraj Pavagada
Postdoctoral Scholar, Radiology
BioSuraj Pavagada is a postdoctoral scholar at the Department of Radiology at Stanford University. His research focuses on exploiting magnetic levitation and optoelectronic techniques for applications in medical diagnostics.
Suraj received his PhD in Oncology from the University of Cambridge (24’), where he developed a new bioelectronic cell enrichment platform utilizing altered glycosylation patterns for the early detection of esophageal cancer. With a background in electrochemistry, surface functionalization, liquid biopsy, and molecular diagnostics, he is passionate about developing portable sensor technologies that can be translated into the clinic to facilitate timely diagnosis and monitoring. -
Edward Pimentel
Postdoctoral Scholar, Radiology
BioEdward Pimentel is a postdoctoral scholar in the lab of Prof. Tom Soh. After receiving his BS in Chemistry at BYU and pursuing the total synthesis of a natural product with anticancer activity in the lab of Dr. Merritt Andrus, Edward was the first graduate student in the lab of Dr. Jeffrey Martell, where his PhD work centered on using DNA nanostructures to accelerate catalytic reactions and building an ultrahigh-throughput DNA-encoded reaction screening platform. Now as a postdoctoral scholar, his research focuses on applying functional nucleic acids to solve problems in diagnostic and sensing for human health. In addition to his research, Edward is a passionate mentor and has been involved in mentoring programs at every stage of his career. He is now a coordinator for the SURPAS Someone Like Me Peer Mentoring program.
-
Giovanni Marco Saladino
Postdoctoral Scholar, Radiology
BioI am a Postdoctoral Scholar in the Department of Radiology at Stanford University. I graduated in Engineering Physics with a BSc at Politecnico di Milano (Italy) and an MSc at KTH Royal Institute of Technology (Sweden). In 2024, I obtained my PhD in Biological and Biomedical Physics from the Department of Applied Physics at KTH Royal Institute of Technology.
My research interests lie at the intersection of molecular imaging, nanomedicine, and nanomaterials. Specifically, I focus on developing novel contrast agents and exploring advanced imaging techniques. During my PhD studies, I designed hybrid multimodal contrast agents for complementary imaging using X-ray fluorescence computed tomography, magnetic resonance imaging, and optical fluorescence imaging. I am currently involved in investigating theranostic applications of nanomaterials, which hold great promise for personalized medicine and targeted therapies. -
Shailja
Postdoctoral Scholar, Radiological Sciences Laboratory
BioShailja is an engineer and computational scientist interested in the modeling of the human brain to study neurological diseases and guide neurosurgeries. As a Wu Tsai Neuroscience Institute’s postdoctoral fellow with Prof. Jennifer A. McNab and Prof. Josef Parvizi, she investigates tractography-based neurosurgical targeting. She is interested in mapping the whole brain structural connectivity network from diffusion MRI to functional connectivity in the human brain. Shailja received her PhD in Electrical and Computer Engineering from the University of California, Santa Barbara and BS from Electrical Engineering Department, Indian Institute of Technology, Kharagpur. Her doctoral research is on Reeb graphs for modeling white matter fibers in the human brain, which was awarded the Winifred and Louis Lancaster Best PhD Dissertation at UC Santa Barbara.
-
Liyan Sun
Postdoctoral Scholar, Radiological Sciences Laboratory
Current Research and Scholarly InterestsPhysics-driven deep learning algorithms for MRI/CT reconstruction and analysis:
(1) MRI acceleration with partial measurements.
(2) Medical image segmentation under limited data resources.
(3) Unsupervised/supervised medical image synthesis for MRI or CT.
(4) Longitudinal medical data analysis with deep learning models.
(5) PET image reconstruction and analysis. -
Simon Thalén
Postdoctoral Scholar, Radiological Sciences Laboratory
BioI am a clinical physiology resident at Karolinska University Hospital and completed my thesis on cardiovascular magnetic resonance imaging (MRI). With a background in mathematics, I am trying to live at the intersection of mathematics, technology, and medicine. My thesis focused on MRI evaluation of constrictive heart diseases, such as pericardial effusion and constrictive pericarditis. I used phase contrast MRI to measure respiratory variation in mitral and tricuspid peak early blood flow velocities and T1 mapping to characterize pericardial effusion fluid.
-
Matheus Tonholo Ikedo
Postdoctoral Scholar, Radiology
BioMatheus Tonholo Ikedo is a Postdoctoral Research Fellow at Stanford University’s Department of Radiology, where he conducts research under the guidance of Dr. Bruno P. Soares. His academic interests lie at the intersection of pediatric neuroradiology and artificial intelligence, specifically focusing on how AI-driven tools can optimize magnetic resonance imaging (MRI) diagnostics and improve healthcare delivery for neuropediatric patients.
A Brazilian-trained physician, Matheus earned his medical degree from the Federal University of São Paulo (UNIFESP) and completed his Radiology residency at the University of São Paulo (USP), where he was recognized with the Guerbet-InRad Best Resident Award in his final year. -
Henk van Voorst
Postdoctoral Scholar, Radiology
BioDr. van Voorst is a postdoctoral scholar in Radiology studying the interfaces of artificial intelligence and neuroradiological imaging in stroke. Originally educated as an MD, Dr. van Voorst gained additional degrees in Finance and Data Science. As a PhD student, Dr. van Voorst focused on cost-effectiveness modeling and developed machine learning and deep learning algorithms with applications in acute ischemic stroke imaging. In his current research, Dr. van Voorst develops artificial intelligence algorithms to automatically extract information from arteries and veins in radiological stroke imaging.
-
Chong Wang
Postdoctoral Scholar, Radiology
BioI am currently a Postdoctoral Scholar in the Department of Radiology at Stanford University School of Medicine, affiliated with the Center for Artificial Intelligence in Medicine and Imaging (AIMI). My research mainly focuses on AI and foundation models in healthcare, with an emphasis on developing trustworthy, robust, and efficient AI solutions for medical imaging. I earned my Ph.D degree, honored with the Doctoral Research Medal, in Computer Science from the Australian Institute for Machine Learning (AIML), The University of Adelaide.
-
Jie Wang
Postdoctoral Scholar, Radiology
BioDr. Jie Wang is deeply passionate about magnetic nanotechnology, including magnetic resonance imaging (MRI), magnetic particle imaging (MPI), magnetic nanoparticles (MNPs), magnetic nanofluid hyperthermia (MNFH), magnetic biosensors, etc., for biomedical applications. His dissertation focuses on MRI-guided magnetic hyperthermia for cancer theranostics. Currently, his research interests include developing enzyme-activable nanoparticles for brain cancer theranostics and employing multi-modal imaging modalities to investigate the interaction between nanoparticles and biosystems (nano-bio interaction) within tumor microenvironment.
-
Philipp Wesp
Postdoctoral Scholar, Radiology
BioI am a postdoctoral researcher investigating interpretable machine learning (ML) and large language model (LLM) applications in clinical radiology. My current research focuses on two complementary areas: understanding what human-interpretable concepts self-supervised vision foundation models learn through mechanistic interpretability techniques like sparse autoencoders, and developing LLM-based systems, including agentic workflows and retrieval augmented generation (RAG) architectures, that leverage unstructured hospital data to improve radiological workflows. I earned my PhD from LMU Munich, where I focused on clinically motivated machine learning applications in medical imaging in the Department of Radiology.
My work is partially funded by a Walter Benjamin Fellowship from the DFG (German Research Foundation). -
McKenzie White
Postdoctoral Scholar, Radiology
BioI work at the intersection of machine learning, medical imaging, and biomechanics. I'm committed to developing tools that bridge gaps between computational methods, musculoskeletal research, and clinical care - enabling more precise analyses, efficient workflows, and improved surgical decision-making.
-
Wesley Williams
Postdoctoral Scholar, Radiology
Current Research and Scholarly InterestsFirstly, a goal of mine is to fashion a novel scatter-based parameter for PET reconstruction algorithms to improve image resolution via determining a more detailed scatter/true ratio estimate via binning the photons that have scattered once, twice, and perhaps, many more times.
Secondly, AI drug discovery application towards radiotracers may quicken experimentation by determining the formulations worth trying. Moreover, it may be able to characterize efficacy (biodistribution) (self-update). -
Zhen Xiao
Postdoctoral Scholar, Molecular Imaging Program at Stanford
Current Research and Scholarly InterestsApplying magnetic nanomaterials for bioimaging and cancer treatment
-
Zijian Yang
Postdoctoral Scholar, Radiology
BioI have long term interest in combining advanced science and technology to provide next generation healthcare system.
To reach that goal, I have developed machine learning based diagnosis model on the software end, which is combined with my hardware end work including wearable/flexible electronics and microelectronic/microfludic platforms. -
Judith Zimmermann
Postdoctoral Scholar, Radiological Sciences Laboratory
BioI am a postdoctoral scholar focusing on advancing breast magnetic resonance imaging, advised by Dr. Brian Hargreaves at the Radiological Sciences Laboratory (RSL), Body Magnetic Resonance (BMR) Group. My research objectives are driven by the need for faster, more accessible breast cancer screening using MRI. Specifically, I want to advance methods for contrast-free imaging, as well as enabling MRI exams with the patient positioned supine, that is laying on their back. I work in close collaboration with clinicians at Stanford Clinics, and contribute to translating new techniques to clinical practice.
I received my PhD from the Department of Computer Science, Technical University of Munich in 2021, jointly with the CMR Lab at Stanford, advised by Dr. Daniel Ennis. My PhD work focused on four-dimensional flow magnetic resonance imaging. After completion of my PhD studies, and prior to joining Dr. Hargreaves' lab, I was with the Breast Imaging Research Group (Dr. Nola Hylton) at UCSF.
