Stanford University
Showing 41-60 of 102 Results
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Jeong Hoon Lee
Postdoctoral Scholar, Radiology
BioLeveraging a strong foundation in data science and engineering, my objective is to address challenges within the biomedical sector. My experience encompasses a broad spectrum of data, including radiology, genomics, histopathology, and clinical data. I am committed to integrating these diverse datasets to conduct research aimed at benefiting patients.
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Yongkai Liu
Postdoctoral Scholar, Radiology
BioDr. Yongkai Liu is a postdoctoral scholar at Stanford's Center for Advanced Functional Neuroimaging, led by Drs. Greg Zaharchuk and Michael Moseley. His interests lie in developing and evaluating advanced techniques for improving treatment decision-making and prognostics in brain diseases, especially stroke, using imaging and deep learning.
Before joining Stanford, he earned a Ph.D. from UCLA, majoring in Physics and Biology in Medicine, under the supervision of Prof. Kyung Sung. This gave him a solid foundation in medicine, deep learning, and physics. His Ph.D. thesis, titled "Advancing Segmentation and Classification Methods in Magnetic Resonance Imaging via Artificial Intelligence," focused on the development of advanced deep learning and machine learning techniques specifically for MRI-based clinical applications. During his master's degree, he studied CT Virtual Colonoscopy under the supervision of Prof. Jerome Liang. In addition, he served as a reviewing editor for Frontiers in Oncology and as a peer reviewer for several critical journals in medical imaging, such as Medical Physics, Scientific Reports, British Journal of Radiology, BJR|Artificial Intelligence, Annals of Clinical and Translational Neurology, IEEE Transactions on Medical Imaging, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Radiation and Plasma Medical Sciences, IEEE Transactions on Biomedical Engineering, and IEEE Transactions on Neural Networks and Learning Systems.
Dr. Liu is an emerging leader in neuroimaging, stroke, and AI, earning widespread recognition for his work. Being named the recipient of the 2024 AJNR Lucien Levy Award, the David M. Yousem Research Fellow Award, and a semi-finalist for the 2024 Cornelius G. Dyke Award underscores his potential to make significant future contributions. (https://med.stanford.edu/rsl/news/yongkai-liu-receives-research-fellow-award.html) -
Ning Lu
Postdoctoral Scholar, Molecular Imaging Program at Stanford
BioNing Lu received a joint Ph.D. degree in Biomedical Engineering and Scientific Computing from the University of Michigan, Ann Arbor, USA, in 2023. Previously, she earned a B.S.E. degree (highest honors) in Biomedical Engineering from Southeast University, Nanjing, China, in 2018. From May 2022 to September 2022, she worked at Meta (formerly Facebook) Reality Labs as a research scientist intern on ultrasonic eye tracking for AR/VR wearable devices, in Redmond, Washington, USA. Her research interests include ultrasound instrumentation, ultrasound therapy, ultrasound imaging algorithms, and AI in healthcare.
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Panpan MA
Postdoctoral Scholar, Radiology
BioTargeted drug delivery, Therapeutic Ultrasound, Tumor Biology, Cancer Research, Pharmaceutical, Nanomedicine, Clinical Research
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Rim Malek
Postdoctoral Scholar, Molecular Imaging Program at Stanford
Current Research and Scholarly InterestsMy work is focused on the development of small molecules radiotracers for cancer imaging, and small molecules and peptides theranostics for cancer detection, targeted radionuclide therapy, and monitoring of tumor response to therapy.
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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.