Matthew Gopaulchan 
Assistant Clinical Research Coordinator

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Matthew is an Assistant Clinical Research Coordinator supporting Dr. Lei Xing and Dr. Ruijiang Li in the Division of Medical Physics. Originally from the islands of Trinidad and Tobago, he obtained his Bachelor of Science in Physics from Hofstra University, New York. He has completed projects in the fields of Biophysics, Optical Science, and Medical Physics.

Tauhidul Islam, Ph.D, 
Researcher

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Tauhidul Islam was a postdoc that joined Lei Xing’s lab in 2019. He transitioned on to Physical Science Research Scientist in 2021. Tauhidul received his PhD in Electrical and Computer Engineering from Texas A&M University.  His research interests include ultrasound elastography, ultrasound poroelastrography, analytical and finite element modeling of tumors, reconstruction of mechanical parameters, mechanopathological parameters, and drug delivery.

Matthew Jinsoon Kim
Assistant Clinical Research Coordinator

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Matthew Kim is an Assistant Clinical Research Coordinator for Medical Physics. He obtained his Bachelors degree in Biomedical Engineering at the University of California, Davis. His undergraduate research focused on biomedical imaging, quantitative imaging, and vascular health. His current research is focused on clinical application of automated radiation therapy planning and AI.

Emma Wu, Ph.D,
Basic Life Research Scientist

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Emma Wu has been a research scientist in the Xing Lab since 2023. She joined Heike Daldrup-Link's lab as a postdoc and received her Ph.D. degree from the Technical University of Munich in 2019. Her research interests include immunotherapy, particularly CAR-T/macrophage therapy, and targeted therapy using the CRISPR system in brain tumor models. Her current research focuses on analyzing high-dimensional biological datasets, such as scRNA-Seq, using deep learning to elucidate biological phenomena and contribute to drug development and targeted therapy.

Yizheng Chen, Ph.D, 
Post Doctoral Scholar

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Yizheng is a postdoctoral researcher in the Xing Lab. He received his bachelor’s and Ph.D. degrees in Engineering from Tsinghua University. Yizheng's research primarily focuses on deep learning-based medical image processing and clinical translation studies. His current work involves advancing techniques for medical image auto-segmentation and auto-registration, with the aim of leveraging the power of deep learning to contribute to improved radiation therapy.

Mingjie Li, Ph.D, 
Post Doctoral Scholar

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Mingjie is a postdoctoral researcher in the Xing Lab. He received his Ph.D. degree in Computer Science from the University of Technology Sydney (UTS) and a master's degree in engineering from Shanghai Jiaotong University. Before joining Stanford, Mingjie was a researcher fellow at UTS. His research mainly focuses on medical multi-modal representations and medical image analysis, such as medical report generation, medical large multi-modal models, and lesion detection. Currently, he is working on utilizing large language models to analyze gene sequences.

Junyan Liu, Ph.D, 
Post Doctoral Scholar

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Junyan is a postdoctoral researcher at the Xing lab. He earned his Bachelor's degree in Biomedical Engineering from Zhejiang University in China and completed his PhD at the University of Texas at Austin. His doctoral research centered around the utilization of differential equations to predict patient-specific responses to radiation treatment. Currently, his research involves the application of computational models to genes, including gene mutation data and single-cell RNA expression data.

Sheng Liu, Ph.D, 
Post Doctoral Scholar

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Sheng Liu is a Postdoctoral researcher at the Department of Radiation Oncology and Biomedical Data Science, Stanford University. Before joining Stanford, he obtained his Ph.D. degree in Data Science and Machine Learning from New York University in 2023. His research interests include robust deep learning with imperfect datasets, multi-modality, vision-language models, and medical image analysis.

Liang Qiu, Ph.D, 
Post Doctoral Scholar

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Liang is a postdoctoral researcher in the Xing Lab. Before embarking on his journey at Stanford, he honed his expertise as a research scientist at the Agency for Science, Technology and Research (A*STAR) in Singapore. He obtained his Ph.D. degree in Biomedical Engineering from the National University of Singapore. Liang’s primary focus lies in the fields of medical AI and surgical robotics, and he is currently working on longitudinal image analysis via implicit neural representation for personalized treatment and patient-adaptive therapy.

Oscar Pastor Serrano, Ph.D, 
Post Doctoral Scholar

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Oscar is a postdoctoral researcher in Xing’s lab. Before joining Stanford, Oscar received his PhD from the TU Delft in the Netherlands, where he developed AI algorithms to predict dose distributions and the anatomical variations that happen in radiotherapy treatments. Before that, he obtained a master’s in physics from the KTH Royal Institute of Technology in Sweden. His research interests concern AI applications to treatment planning, including dose calculation and image registration, with the goal of online adaptation of treatment plans.

Siqi Wang, Ph.D, 
Post Doctoral Scholar

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Siqi Wang is a postdoctoral scholar at the Department of Radiation Oncology at Stanford University. Prior to joining Stanford, he earned his Ph.D. degree in Biomedical Engineering from the University of California, Irvine, in 2023. Siqi's research interests are centered around biomedical imaging instrumentation and the development of radiation dosimetry technology. His current project focuses on the development of luminescence-based tools for quality assurance in radiotherapy, with a special emphasis on the application of machine learning algorithms to enhance treatment accuracy and efficacy.

Xiaohan Xing, Ph.D, 
Post Doctoral Scholar

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Xiaohan is a postdoctoral researcher in the Xing lab. She obtained her Ph.D degree in Electronic Engineering from the Chinese University of Hong Kong and her Bachelor degree in Biomedical Engineering from Shandong University. Her research mainly focuses on Biomedical AI, which lies in the interdisciplinary areas of machine learning, computer vision, biomedical imaging, medical image analysis, and omics analysis. She is currently developing methods for multi-contrast low-field MRI enhancement and multi-modal data fusion.

Siqi Ye, Ph.D, 
Post Doctoral Scholar

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Siqi Ye is a postdoctoral researcher in the Xing lab. She obtained her Ph.D. in Electronic Science and Technology from Shanghai Jiao Tong University (SJTU), China, in 2021. Her research at SJTU was developing image reconstruction algorithms for X-ray computed tomography (CT). She is currently focusing on designing physics-involved AI methods for biomedical imaging, which encompass super-resolution imaging, image reconstruction, and image registration. These methods are intended for various biomedical applications, such as microscopy, CT, MRI, and PET.

Zixia Zhou, Ph.D, 
Post Doctoral Scholar

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Zixia received her PhD degree in Biomedical Engineering from Fudan University. Her interests include improving medical imaging quality in cost-effective manners with artificial intelligence.  Her research also focuses on high spatio-temporal ultrasound image reconstruction and high-dimensional data reduction and visualization.

Mark Laurie
Graduate Student

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Mark Laurie is a graduate student at Stanford studying Computational and Mathematical Engineering (CME) under the co-mentorship of Professor Liao and Professor Lei Xing from radiation oncology. He received his B.S. in Biomedical Computation at Stanford. Mark’s current work encompasses the use of state-of-art video processing models to detect bladder cancer, the creation of a benchmark cystoscopy dataset to streamline predictive model assessment, and the development of new multimodal algorithms to guide decision support system for bladder cancer screening and surveillance. 

Quigyue Wei
Graduate Student

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I am a first year Master student in Electrical Engineering at Stanford. I graduated from Fudan University with a bachelor's degree in Electrical Engineering in 2020. My research interest in medical image processing has been inspired since I became a junior at Fudan University. I have been involved in several projects related with medical image processing (e.g., noisy/semi-supervised segmentation, liver ultrasound video segmentation/classification, MRI reconstruction and so on). And currently I am working on gene imputation.

Rui (Rachel) Yan
Graduate Student

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Rachel is a Ph.D. candidate in Computational and Mathematical Engineering at Stanford University. Her research interests lie in the intersection of machine learning and healthcare. Her current project focuses on developing advanced computational tools to extract meaningful representations from complex biomedical data.

Ridvan Yesiloglu
Graduate Student

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Nathan Nguyen
Undergraduate Student

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