Stanford University
Showing 51-100 of 102 Results
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Sanaz Nazari Farsani
Postdoctoral Scholar, Molecular Imaging Program at Stanford
BioDr. Nazari Farsani works on developing and implementing machine learning techniques for automated tissue segmentation from brain PET/MR images. She is also developing machine learning algorithms for PET data correction and de-noising.
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Sophie Ostmeier
Postdoctoral Scholar, Radiology
BioMy current research is in deep neural networks that learn from multimodal clinical data including images and clinical information. I would like to combine these primary computer vision algorithms with large language models/EHR encoding models in order to integrate them into the clinical workflow, potentially as a virtual assistant.
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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-based techniques for applications in point-of-care 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. -
Shirin Pourashraf
Postdoctoral Scholar, Molecular Imaging Program at Stanford
Current Research and Scholarly InterestsMy working is focused on building a 100 ps CTR pre-clinical partial ring TOF-PET scanner; specifically, by exploring, and designing high speed low noise/jitter instrumentation, and data acquisition.
I am also designing an scalable side-readout electronic to detect Cherenkov radiation and improve TOF resolution in PET detectors using BGO crystals. -
Shobha Regmi
Postdoctoral Scholar, Radiology
BioResearch interest: Mesenchymal stem cell transplantation, Stem cell biology, Islet transplantation, Biomaterials, Drug delivery
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Eduardo Pontes Reis
Postdoctoral Scholar, Radiology
BioI'm a visiting scholar at Stanford AIMI Center, working in the intersection of Artificial Intelligence and Medicine. My purpose is to contribute to our understanding of intelligence. And our best chance to achieve this is through AI.
Research highlights:
- Published BRAX, the Brazilian Chest X-ray Dataset - https://www.nature.com/articles/s41597-022-01608-8
- Open-sourced the PyTorch implementation of ConVIRT (Y Zhang et al), a contrastive learning method for radiologic images and text (before CLIP) - https://github.com/edreisMD/ConVIRT-pytorch
- Released Brain Hemorrhage Annotations - Brain Hemorrhage Extended - BHX (https://physionet.org/content/bhx-brain-bounding-box)
At Hospital Israelita Albert Einstein:
- Started the Health Story project, a medical history timeline to support research and a more personalized clinical practice
- Ran the development of AI algorithms for diseases of national importance: Tuberculosis, COVID, Melanoma and Head CT -
Shengtian Sang
Postdoctoral Scholar, Radiology
BioShengtian Sang is currently a post-doctoral scholar at the Laboratory of Artificial Intelligence in Medicine and Biomedical Physics in the department of Radiation Oncology at Stanford University. He received his Ph.D. degree from the College of Computer Science and Technology, Dalian University of Technology, Dalian, China. His current research interests are high-dimensional data mining, medical image computing, and machine learning. In his Ph.D. study, he worked on the biomedical literature-based discovery and data mining.
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Shailja
Postdoctoral Scholar, Radiological Sciences Laboratory
BioDr. Shailja is a Postdoctoral researcher in the Radiological Science Laboratory at Stanford. She recently completed her PhD in Electrical and Computer Engineering at the University of California, Santa Barbara. Her research vision is to model healthcare data for precise diagnostics using AI and to integrate domain knowledge to "close the loop" between surgeons, physicians, and scientists. Her Ph.D. dissertation focused on developing a principled approach to model the white matter pathways in the human brain to analyze the topology of brain connections. At the Radiological Science Laboratory, she will primarily focus on mapping MRI structural and functional connectivity imaging data with electrophysiological measurements in the same patients.
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Sushruta Surappa
Postdoctoral Scholar, Radiology
BioSushruta Surappa is a postdoctoral researcher at the Canary Center for Early Cancer Detection at Stanford University. His current research focuses on developing various MEMS-based tools for the separation and capture of extracellular vesicles for medical diagnostics. Sushruta received his MS (‘15) and PhD (‘21) degrees in Mechanical Engineering from Georgia Institute of Technology, where he developed a new class of nonlinear MEMS transducers with applications in wireless power transfer, sensing and energy harvesting. He is passionate about developing low-cost, miniature technologies for medical diagnostics and is a keen proponent of science communication.
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Zahra Shokri Varniab
Postdoctoral Scholar, Radiology
BioZahra Shokri Varniab, MD, studied medicine at Tehran University of Medicine Sciences, Iran, and earned her medical degree in 2020. Her goal in novel cellular and molecular imaging is to develop novel in vivo imaging approaches to visualize, characterize and quantify molecular and cellular processes involved in developing brain tumors. She intends to utilize non-invasive imaging techniques to assess tumor microenvironment to understand their role in cancer, develop a method for determining tumor profiles, and also using brain MR Imaging to assess treatment response. She hopes cancer to be history.
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Shashi Singh
Postdoctoral Scholar, Radiology
BioAs a postdoctoral scholar at Stanford University's Department of Radiology (2023-Present), I am privileged to contribute to Dr. Heike E. Daldrup-Link's laboratory, focusing on clinical and translational molecular imaging research. My endeavors deal with the development and application of artificial intelligence algorithms aimed at automated detection and monitoring treatment response of pediatric cancers, such as lymphoma and sarcomas, using PET and MRI. This includes the application of AI in multimodal pediatric lymphoma detection, automating the Deauville score, and predicting the post-chemotherapy response in pediatric osteosarcomas using PET and MRI. I am also studying the effects of iron-oxide nanoparticles on tumor-associated macrophages in osteosarcoma using Ferumoxytol-enhanced-MRI.
I served as a physician in Nepal for two years (2019-2021), which deepened my understanding of complex diseases like cancers and infectious and inflammatory disorders. Later, I worked as a research scholar at the Hospital of the University of Pennsylvania (2021-2023) where I worked with PET/CT imaging across various studies using novel radiotracers such as FDG, NaF, PSMA, and DOTATATE. My research at UPenn primarily focused on PET/CT imaging of hematological malignancies. I assessed the potential of PET/CT in CAR-T cell therapy for lymphoma and multiple myeloma and analyzed the efficacy of hematopoietic stem cell transplantation in multiple myeloma. I also studied dual time point imaging for Hodgkin's and non-Hodgkin's lymphoma using total-body FDG PET/CT. Beyond oncology, my research broadened to include PET/CT applications in aging, musculoskeletal, neurological, psychiatric, and cardiovascular diseases.
Each phase of my career has deepened my resolve to harness the power of imaging and artificial intelligence to revolutionize clinical management, honoring my commitment to patient care and groundbreaking scientific research. The significant potential of the application of artificial intelligence with both - structural (CT and MRI) and molecular (PET) imaging modalities has spurred my interest in utilizing AI to refine disease diagnosis and monitoring processes. I envision being a physician-scientist at the intersection of advanced clinical imaging and AI-based innovation, developing cutting-edge tools for early and accurate disease diagnosis and management. I believe that my contributions signify my commitment to this vision. -
Muhammad Nasir Ullah
Postdoctoral Scholar, Molecular Imaging Program at Stanford
BioMuhammad Nasir Ullah has received a BS degree in Electronic Engineering from International Islamic University, Islamabad (IIUI) Pakistan in Jun 2012 and an integrated MS + Ph.D. degree in Bio-Convergence Engineering from Korea University, Seoul, South Korea under the supervision of Professor Jung-Yeol Yeom in Feb 2020. His Ph.D. thesis was focused on detector design for Nuclear Medicine (NM) system and NM-Ultrasound hybrid systems.
His area of research interest is radiation detection and measurement for medical applications. He has been working on detector design for Positron Emission Tomography (PET) system, intraoperative gamma probe detector, beta/gamma discrimination, and hybrid Ultrasound-gamma probe. He has also been working on frontend discrete circuit designs for various types of radiation and Ultrasound (US) detectors. He has published 6 peer-reviewed articles as the first author while 2 as co-author. He also has 4-patents under his name in S. Korea. -
Jeya Maria Jose Valanarasu
Postdoctoral Scholar, Radiology
BioDr. Jeya Maria Jose Valanarasu is a postdoctoral scholar working with the Stanford Machine Learning Group and the Center for Artificial Intelligence in Medicine and Imaging (AIMI Center). He leads the AI for Healthcare bootcamp with Dr. Andrew Ng, Dr. Curt Langlotz, and Dr. Nigam Shah which provides Stanford students an opportunity to engage in advanced research at the intersection of AI and healthcare.
He obtained his Ph.D. and M.S from Johns Hopkins University where he worked on various problems in Computer Vision, Machine Learning, and Healthcare. His research aims to overcome the challenges that arise when translating machine learning models to practical applications for healthcare and engineering sectors. His works have spanned over topics like designing effective deep architectures, model adaptability to changing environments, role of data and annotations, multi-modal learning and taming large models for computer vision and healthcare tasks. He has published over 25 peer-reviewed journal/conference articles at top venues and filed 3 U.S. patents. He has been awarded Amazon Research Fellowship 2022, Best Student Paper Awards at ICRA 2022, CVIP 2019, MICCAI Young Scientist Impact Award Finalist 2022, and the NIH MICCAI Award 2022. He has also served as a reviewer for multiple journals and conferences. -
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.
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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.
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Zhen Xiao
Postdoctoral Scholar, Molecular Imaging Program at Stanford
Current Research and Scholarly InterestsApplying magnetic nanomaterials for bioimaging and cancer treatment
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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. -
Alaa Talaat Youssef
Postdoctoral Scholar, Radiology
BioDr. Youssef is a postdoctoral fellow in the Department of Radiology at Stanford University School of Medicine. She received her Doctor of Philosophy degree in Data Science and Population Health from the Institute of Medical Science, University of Toronto, Canada in 2021. Her research addresses ethical considerations in AI development, aiming to promote responsible use of AI in healthcare. Using mixed-methods methodologies, she investigates the end-user experience with AI systems, identifying ethical and safety concerns related to integrating AI into clinical workflows. Dr. Youssef leads several AI educational programs and policy initiatives. She co-directs the Stanford AIMI High School Programs, preparing the next generation for careers that intersect AI and medicine. She also serves on several AI policy and education committees across the Stanford School of Medicine.
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Aroosa Zamarud, MD
Postdoctoral Scholar, Radiology
BioDr. Aroosa Zamarud is a medical doctor who completed her undergraduate education at Bannu Medical College, Khyber Medical University, Pakistan. Following her graduation and a one-year medical internship, she served as a Medical Officer at Zubaida Khaliq Memorial Hospital, Gilgit Baltistan, Pakistan, a charitable institution. During her tenure, she organized medical camps in remote villages in Northern Pakistan, providing healthcare services to underprivileged populations.
In March 2022, Dr. Zamarud joined the Stanford Neurosurgery department as a Visiting Instructor. Her research primarily focused on Clinical Neurooncology, with a special emphasis on the use of Cyberknife stereotactic radiosurgery as a treatment modality for various benign and malignant brain pathologies, including Vestibular Schwannoma, Sarcoma, Spinal metastases, Meningioma, Pineal and Pituitary metastases, and Arteriovenous malformations.
Currently, Dr. Zamarud is serving as a postdoctoral fellow in neurointerventional Radiology. Her ongoing research centers on investigating the role of venous outflow in patients with acute ischemic stroke, among other stroke-related studies. -
Lichun Zhang
Postdoctoral Scholar, Radiology
BioPostdoctoral Scholar at Stanford University | AI in Medical Imaging | GoHawks
