Larson Group People
Personnel
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Peder Larson, PhD Dr. Peder Larson got his PhD under Dwight Nishimura from the Department of Electrical Engineering at Stanford University on "MRI of Semi-solid Tissues" in 2007. His research interests are in RF pulse design, pulse sequence development, novel imaging strategies, and optimized reconstruction methods for MRI, with an emphasis on applications in Hyperpolarized carbon-13 agents and semi-solid tissue imaging with ultrashort echo time (UTE) methods. |
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Charlie Wang, MD, PhD Dr. Charlie Wang is a Radiology Resident who completed his PhD at Case Western Reserve University on MR fingerprinting methods. He is working on applying MR fingerprinting to hyperpolarized carbon-13 MRI studies. |
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Abhejit Rajagopal Dr. Rajagopal received his PhD in 2019 from UC Santa Barbara under the mentorship of Shivkumar Chandrasekaran and Hua Lee. His thesis focused on the role of approximation theory in imaging and recognition algorithms. Since joining UCSF, Dr. Rajagopal has been working on machine learning techniques for enhanced PET/MRI reconstruction, prostate cancer grading, and techniques for quantifying generalization in deep learning. |
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Xiaoxi Liu Dr. Xiaoxi Liu received her PhD in Diagnostic Radiology from the University of Hong Kong with Dr. Hing Chiu Chang. She has extensive experience in sequence design with Philips pulse programming environment and imaging reconstruction in the diffusion imaging field. She is currently working on pulse sequences and imaging reconstruction for liver tumor imaging with hyperpolarized carbon-13 MRI. |
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Xin Shen Dr. Shen is focusing on sequence development, especially using rosette k-space trajectories for UTE MRI and MRSI, which has been demonstrated in myelin imaging, brain iron mapping, and other nuclei imaging including phosphorous and sodium. |
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Anil Kemisetti Anil Kemisetti received his master’s in Biomedical Imaging from UCSF in 2021. He also has a master’s in Health Informatics from the University of San Francisco and two decades of industry experience in software development. His work is focused on Federated Learning. |
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Nikhil Deveshwar Nikhil Deveshwar is a PhD candidate in the UC Berkeley-UCSF graduate program in bioengineering. His work is focused on deep generative models for synthetic phase/raw MRI data and designing hardware accelerators for deep learning MRI reconstruction. |
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Erin Argentieri Erin is a PhD student in the joint UC Berkeley - UCSF program in Biomedical engineering. Her work focuses on the utility of quantitative MRI (T2, T1ρ, ZTE, UTE-T2*, UTE-MT) for musculoskeletal applications with a particular interest in establishing sex-specific, imaging-based biomarkers to inform the etiology and prognosis of various MSK pathologies. |
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Sule Sahin Sule Sahin is a graduate student in the UC Berkeley - UCSF Graduate Group in Bioengineering. She is currently working on quantification and modelling of hyperpolarized carbon-13 imaging studies. |
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Avantika Sinha Avantika Sinha is in the UCSF Master's of Biomedical Imaging program and working as a research assistant. She is currently working on her thesis "Software Developments for Processing Hyperpolarized MRI Data" and assisting with myelin imaging using UTE and diffusion MRI. |
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Anna Bennett Anna Bennett is a student in the UCSF Master's of Biomedical Imaging program. She is currently working on her thesis "Improving SNR and Spatial Coverage of Hyperpolarized Carbon-13 MR Imaging Using Real-Time Calibrations". |
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Ernesto Diaz Mr. Diaz is working on data processing and analysis methods for hyperpolarized 13C MRI studies. |
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Alumni
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Ningjing (Nora) Zhang Ningjing (Nora) Zhang is a graduate student of the UCSF Master's of Biomedical Imaging program. She is currently working on her thesis "Improving Quantification of Prostate-Specific Membrane Antigen (PSMA) - Positron Emission Tomography (PET) Clinical Data via Deep Learning for Clinical Decision Making". |
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Phil Yuan Tai Xie Phil Yuan Tai Xie is a UC Berkeley undergraduate student studying Electrical Engineering, Computer Science, and Bioengineering. Under the mentorship of Dr. Abhejit Rajagopal, Phil has been researching deep learning methods to improve multi-class cancer segmentation on MRI images. He studies the applications of latent space representations of brain and prostate cancer MRI images for improving the generalization performance of machine learning models. |
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Fei Tan, PhD Dr. Fei Tan completed her PhD in Bioengineering from UC Berkeley - UCSF Bioengineering program. Her work focused on pulmonary ventilation analysis with ultrashort echo (UTE) proton MR. She is currently a Fellow at USFDA. |
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Jingwen Yao, PhD Dr. Jingwen Yao completed her PhD in Bioengineering from the University of California Los Angeles under the mentorship of Dr. Benjamin Ellingson. Her dissertation involved developing and validating pH-sensitive chemical exchange saturation transfer (CEST) MRI in adult glioma patients. She worked on myelin imaging using ultrashort echo (UTE) relaxometry MRI with Dr. Peder Larson and multi-modal characterization of Huntington's disease (HD) at 7T with Dr. Janine Lupo. She is currently an Assistant Professor at UCLA. |
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Peng Cao, PhD Dr. Peng Cao was a postdoctoral scholar in the Larson Group at UCSF from 2014-2018, where he worked on a broad range of advanced imaging projects including advanced hyperpolarized carbon-13 MRS and MRI methods. He became an Assistant Professor at The University of Hong Kong in 2018. |
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Elizabeth Smith, PhD Dr. Elizabeth Smith is a biophysicist and data scientist who is passionate about applying artificial intelligence and machine learning (AI / ML) to improve healthcare. Her current projects are focused on scaling the impact of PSMA PET in clinical decision making. Dr. Smith spent the past five years at a geospatial analytics startup where she applied AI / ML to build software products from terabytes of satellite imagery. Her postdoctoral fellowship at UCSF and the Advanced Light Source focused on developing novel methods to image, reconstruct, co-align, and analyze features within three-dimensional tomographic reconstructions. She has a PhD in biophysics from the University of Wisconsin, Madison, and a bachelor's in physics from Pomona College. |
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Kirti Magudia, MD Dr. Magudia received her graduate training in the Weill Cornell/ Rockefeller/ Sloan-Kettering Tri-Institutional MD-PhD Program, where her PhD thesis focused on developing a 3D cell culture model of colon epithelial tumorigenesis. She completed her Radiology residency at Brigham and Women's Hospital, where she worked at the MGH & BWH Center for Clinical Data Science applying machine learning methods to define population-based normal values of body composition. She is currently an Assistant Professor at Duke University. |
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Nick Dwork, PhD Dr. Nicholas Dwork completed his PhD in Electrical Engineering from Stanford University with Prof. John Pauly working on acquisition and reconstruction of MRI and optical imaging data. He worked on novel methods for hyperpolarized C-13 MRI acquisition and reconstruction. Dr. Dwork is an Assistant Professor at the University of Colorado. |
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Jessica Scholey, PhD Jess received her master's degree in Medical Physics and clinical residency training in Radiation Oncology from the University of Pennsylvania. She is currently a Board-Certified Medical Physicist and Bioengineering PhD student, where she focuses on MRI-applications in Radiation Oncology, specifically implementing sequence-based and deep learning-based approaches used for Radiotherapy dose calculation and incorporating these approaches into the clinical workflow. Jess is an Assistant Professor at UCSF Radiation Oncology. |
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Andrew Leynes, PhD Andrew Leynes is a graduate of the UCSF Masters of Biomedical Imaging Program and completed his PET/MR Master’s Thesis on “Tissue Segmentation and Classification for PET/MR MR-based Attenuation Correction using Zero-Echo Time (ZTE) MRI” in 2015. He is working on advanced methods for quantitative PET/MRI, high-field (7T) MRI, and RF coil design projects. |
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Jeremy Gordon, PhD Dr. Jeremy Gordon came to UCSF from UW-Madison as a postdoctoral scholar in 2013 and he pioneered imaging methods and experimental protocols for human hyperpolarized carbon-13 metabolic MRI studies. He became an Assistant Professor at UCSF in 2020. |
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Manuska Vaidya, PhD Dr. Vaidya received her PhD at the NYU School of Medicine under the mentorship of Ricardo Lattanzi, Graham Wiggins, and Dan Sodickson. She has extensive experience in RF coil design and evaluation of MRI evaluations, and is currently working on improved RF hardware and pulse sequences for brain tumor imaging with hyperpolarized carbon-13 MRI. |
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Shuyu Tang Shuyu Tang was a graduate student in the UC Berkeley - UCSF Graduate Group in Bioengineering, and a graduate of the UCSF Master's of Biomedical Imaging program. He completed his thesis “Improved Acquisition Methods for Hyperpolarized Carbon-13 Magnetic Resonance Imaging” in 2019 and became an MRI research scientist in industry. |
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Xucheng Zhu Xucheng Zhu was a graduate student in the UC Berkeley - UCSF Graduate Group in Bioengineering. He worked on Motion Correction for lung imaging and dynamic hyperpolarized imaging strategies. He completed his thesis “Advanced 1H Lung MRI” in 2020 and became an MRI research scientist in industry. |
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Wenwen Jiang Wenwen Jiang got her PhD in 2017 in the UC Berkeley - UCSF Graduate Group in Bioengineering, working jointly with Prof. Larson at UCSF and Prof. Michael Lustig at UC Berkeley on "Rapid and Robust Non-Cartesian Magnetic Resonance Imaging Methods". Upon graduation, she became an imaging scientist in industry. |
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Tanguy Boucneau Tanguy Boucneau was a visiting graduate student in our group from the Ecole Normale Superior (ENS)-Cachan in France, working on ultrashort echo time (UTE) MRI methods for imaging myelin in the brain. He subsequently completed his PhD at the Unviersité Paris-Saclay. |
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Dharshan Chandramohan Dharshan Chandramohan worked on quantitative cancer imaging methods using PET/MRI and to improve radiation therapy planning. He continued on to medical school in 2020. |
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Sonam Machingal Sonam is a graduate of the UCSF Master’s of Biomedical Imaging Program. She completed her Master’s thesis on “Sampling Strategies for Hyperpolarized Carbon-13 Dynamic Imaging” in 2014 under Dr. Larson. |
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Naeim Bahrami Naeim is a graduate of the the UCSF Master's of Biomedical Imaging program. He completed a Master’s thesis on “Modeling Hyperpolarized 13C Pyruvate and Urea Concentration Kinetics With Multibanded RF Excitation MRI In Prostate Cancer” in 2013, and went on to receive his PhD at Virginia Tech. |
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Yan Ann Xing Ann was in the inaugural class of the UCSF Master's of Biomedical Imaging program. She completed her Master's thesis on "Optimal Variable Flip Angle Schemes For Dynamic Acquisition Of Exchanging Hyperpolarized Substrates" in 2012 under Dr. Larson. |
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Qing Dai Qing is a graduate of the the UCSF Master's of Biomedical Imaging program. He completed a Master’s thesis on “Clear Cell Renal Cell Carcinoma: Deep Learning-Based Prediction of Tumor Grade from Contrast-Enhanced CT” in 2019, and worked in the group for one year before returning to UCLA to pursue his PhD. |