School of Medicine
Showing 41-60 of 103 Results
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Manoj Kumar
Postdoctoral Scholar, Radiology
Current Research and Scholarly InterestsI work on imaging-guided therapy using PET and MR imaging approaches. My academic training and background is in molecular imaging. During my doctoral training, I developed and validated a PET imaging approach for evaluating endocrine therapy responses in advanced breast cancer. My current research focuses on imaging tumor immune markers and responses to cancer immunotherapy. The goal is to develop new imaging toolboxes to monitor and guide treatment. Specifically, I employ antibodies, nanoparticles, and reporter genes for imaging and combinations of therapies to modulate and restore the body's suppressed immune functions against cancer cells. This is being done in collaboration with teams of researchers in early clinical development and teams in clinical practice.
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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. Dr. Liu is a recipient of the prestigious K99/R00 award for his work on integrating large language models and imaging-based deep learning for stroke outcome prediction.
Prior to joining Stanford, Dr. Liu earned his Ph.D. in Physics and Biology in Medicine from UCLA under the mentorship of Prof. Kyung Sung. This rigorous training equipped him with a strong 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 developing cutting-edge deep learning and machine learning techniques for MRI-based clinical applications. During his master’s studies, he conducted research on CT Virtual Colonoscopy under the guidance of Prof. Jerome Liang, an IEEE Fellow.
Dr. Liu has also made significant contributions to the academic community as a peer reviewer for leading journals, including The Lancet Digital Health, NPJ Digital Medicine, Medical Image Analysis, 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 research, and artificial intelligence, earning widespread recognition for his work. His accolades include the K99/R00 Award, the AJNR Lucien Levy Award, the David M. Yousem Research Fellow Award, and being named a semi-finalist for the 2024 Cornelius G. Dyke Award, all of which underscore his potential to make significant contributions in the future (https://med.stanford.edu/rsl/news/yongkai-liu-receives-research-fellow-award.html). -
Panpan MA
Postdoctoral Scholar, Radiology
BioTargeted drug delivery, Therapeutic Ultrasound, 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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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.
