Founder Dr. Harrison Bai is Associate Professor of Radiology and Radiological Science, Department of Radiology at the Johns Hopkins University School of Medicine. Having graduated from Yale College in 2008 and Yale Medical School in 2013, he completed the IR Direct Pathway (2 years of general surgery + 3 years of Diagnostic Radiology + 1 year of Interventional Radiology) from 2013 to 2019 at the Hospital of the University of Pennsylvania before joining Brown as faculty. With his primary research interest in AI/Machine learning/Deep learning with its application to Radiology and the healthcare system, Dr. Bai has a Master’s Degree in Bioinformatics from Johns Hopkins and published more than 100 peer-reviewed papers. His research is widely funded by NIH, NSF, RSNA, and SIR. firstname.lastname@example.org
Director Dr. Zhicheng Jiao is the Principal Investigator and co-director. Having got his Ph.D. degree and bachelor’s degree from Xidian University in 2018 and 2013, he worked as a postdoc at the University of North Carolina at Chapel Hill and University of Pennsylvania before joining Brown as an assistant professor. His research interests are AI methods for medical image analysis and computer vision, and his study has been widely published in top AI conferences and prestigious journals and funded by NIH, NSF, Bank of America Private Bank, and Brown University. email@example.com
Collins, Scott A
Broad and deep experience with all aspects of cross-sectional CT imaging: from protocol design to radiation dose reduction, to advanced post-processing and image analysis. Particularly interested in advanced visualization for 3D medical image rendering; which has led to expertise in modeling, surface representations, anatomic shape analysis, and AR/VR display technologies. He has worked extensively in creating real-time tumor ablation validation workflows; as well as designing image presentations for VR systems including the Brown YURT Ultimate Reality Theater and the Microsoft Hololens. He has participated in dozens of translational research projects; and has been recognized as co-author for visualization work in numerous abstracts and publications across multiple clinical services.
Wu Jing is a Radiologist from China. She has completed her IR training and started to work on body DR in 2019. She has worked under Dr. Harrison Bai since 2016 and participated in projects focusing on AI/Machine learning/Deep learning for evaluation of tumors on imaging.
Daniel received his B.A. in computer science at Brown University in 2020. He is currently a 2nd medical student at Warren Alpert. His current research interests are automatic tumor segmentation and response assessment following treatment.
John (Jack) Sollee obtained his B.S. in Molecular Neurobiology from Haverford College in 2018. He is now an MD candidate at the Warren Alpert Medical School of Brown University, class of 2024. He is part of the scholarly concentration in translational research in medicine, and is working to develop AI tools for the characterization of lung and kidney abnormalities.
Braden obtained his B.S. in Biology from Oregon State University in 2018 and is currently pursuing an MD from the Warren Alpert Medical School of Brown University. He is involved in projects using AI models applied to medical imaging techniques to predict lung and renal cancer outcomes.
Ashwin is a first-year medical student at the Warren Alpert Medical School of Brown University. Ashwin obtained his B.S. in computational neuroscience from Carnegie Mellon University in 2019. His previous research involvement includes computational radiology research at the Canary Center at Stanford for Cancer Early Detection developing a novel quantification method for molecular ultrasound imaging for which he obtained a provisional patent. Ashwin has also presented several abstracts and posters at national clinical pathology meetings and imaging conferences. His current research interests include artificial intelligence in medical imaging and clinical decision support. A trivia fanatic, Ashwin hopes to be a Jeopardy! contestant in the near future.
Mihir Khunte is an MD candidate at Warren Alpert Medical School of Brown University, class of 2025. He obtained his B.S. in Biomedical Engineering from Yale University in 2021. His research interests center around building clinical AI tools based on medical imaging and clinical outcomes data.
Chris graduated from Brown University in 2020 with a Bachelor of Arts in Computer Science. He is currently deferring medical school to acquire experience in management consulting but plans to matriculate into the Warren Alpert School of Medicine in 2022. His current projects in the lab are focused on developing deep learning models to diagnose COVID-19 from chest X-ray images and to estimate brain tumor sizes from MRI scans. Chris is also interested in healthcare automation, such as telemedicine and AI-assisted diagnostics, as well as its implementation in modern clinical systems through healthcare entrepreneurship.
Soryan Kumar is an MD candidate at Warren Alpert Medical School of Brown University, class of 2025. He obtained his Sc.B in Applied Math-Economics at Brown University in 2021. His current research projects include applying deep reinforcement learning for brain tumor segmentation and developing deep learning models for pediatric COVID-19 diagnosis. He is part of the Medical Technology, Innovation, and Entrepreneurship scholarly concentration and ultimately aims to develop AI tools for clinical implementation.
Gabrielle Windsor is an MD candidate at the Warren Alpert Medical School of Brown University, class of 2025. She obtained her B.S. in Cell and Molecular Biology and Anthropology from Tulane University in 2021. Her previous research experience includes investigating triple negative breast cancer through novel patient-derived xenograft models, and her current project involves applying AI models to imaging techniques in monitoring breast cancer.
Helen Zhang is a first-year medical student at the Warren Alpert Medical School of Brown University. She obtained an Sc.B. in Biology and Computer Science from Brown University in 2022. Her current research projects involve Parkinson’s disease and transarterial chemoembolization.
Hossam Zaki is an MD candidate at the Warren Alpert Medical School of Brown University. He earned a B.S in Computer Science and a B.A in Biology from Brown University in 2022. His current research projects involve 3D tumor segmentation and analysis for treatment planning. He is currently in the Biomedical Informatics Scholarly Concentration and plans to continue building AI based models for radiologic clinical support.
Shreyas Kulkarni is an MD Candidate at Warren Alpert Medical School Class of 2026. He graduated with a B.S in Computer Science from Duke University in 2021 and spent his gap year as a software engineer at Capital One. His interests are in advancing radiology through AI/ML and expanding medical informatics education. He is currently working on models related to pulmonary embolism and plans to expand his experience by spending more time in developing AI models. He is also a part of the Biomedical Informatics Scholarly Concentration.
Robin Wang received his B.A. in Computer Science from Dartmouth College in 2014. He worked at Goldman Sachs for three years before leaving to pursue a career in medicine. He is now studying at the Perelman School of Medicine. Robin is interested in applying artificial intelligence to assist physicians. His current research involves distinguishing malignant from benign tumors in various cancers (ovarian, renal, etc).
Sope received his B.S. in Mechanical Engineering from MIT in 2019. He is pursuing an MD at the Perelman School of Medicine at the University of Pennsylvania. His career interests are in the translation and commercialization of technological innovations in healthcare, especially as it relates to medical device development. He is currently working on developing a deep learning model for the classification of bone carcinomas.
Zhusi (Jules) Zhong received the B.S. degree from Xidian University, Xi’an, China, in 2018. He is currently pursuing the Ph.D. degree in School of Electronic and Engineering at Xidian University, Xi’an, China. His research interests mainly focus on the application of deep learning technology in medical image analysis and the process flow of medical data, his research results have been widely presented on top-level medical AI conferences and published journals.
Brown PLME students
Lulu is a sophomore completing her B.A. in Biology at Brown University, and she will continue her education at Warren Alpert Medical School (class of 2028). Currently, her projects include the application of deep learning to improving outcomes of glioblastoma patients and the use of auto-segmentation techniques in pancreatic tumors.
Dr. Atalay Is a graduate of Princeton University (physics) and The John’s Hopkins School of Medicine where he obtained MD and PhD degrees (biomedical engineering) through the Medical Scientist Training Program. His PhD research focused on the imaging of myocardial oxygenation using MRI. Following medical internship at the Beth Israel Hospital in Boston and a research fellowship at Massachusetts General Hospital’s Charlestown Navy Yard, he completed residency and fellowship training in radiology at John’s Hopkins Hospital.
Dr. Atalay specializes in cross-sectional imaging and cardiac MR and CT. Since 2003 he has been on faculty at The Warren Alpert Medical School of Brown University. He is currently Professor of Diagnostic Imaging and Medicine (Cardiology), Vice-Chair of Imaging Research, and Director of Cardiac MR and CT. He also oversees the Brown Radiology Advanced Imaging Lab (BRAIL) and is the Medical Director of the Brown Radiology Human Factors Lab.
He is the professor and Chair of Computer Science. He received his undergraduate and masters degrees in Turkey and then came to University of Maryland for his doctoral studies. He joined Brown right after He completed my PhD in 2001. His work strives to facilitate the management and analysis of data under challenging situations, for example, when there is lots of data or scarce computing resources. For the last few years, he has worked on tools and systems that can quickly process and analyze high-rate data streams. He is now moving on towards supporting big data and self-managing systems. He likes to teach classes that draw on principles and mechanisms from several sub-areas of computer science, such as databases, distributed systems and networking. For the last three years, he has also enjoyed teaching a freshman class on introduction to computer science.
He is the professor of Engineering. He received his BA, MA and PHD degrees in McGill University. Vision has emerged as an exciting and interdisciplinary area of investigation. Professor Kimia’s research in vision is mainly concerned with the problem of recovery, representation, and recognition of two and three-dimensional shape from real images. Professor Kimia’s research interests are in the areas of computer vision, image processing, medical imaging, perception, and psychophysics. A focus of his program is the problem of object recognition from shape.
Dr. Nikos Tapinos received his MD/PhD degrees from the National University of Athens, Greece. His PhD dissertation was conducted in the Department of Pathophysiology with a focus on Molecular Immunology. This work culminated in cloning a strain of Coxsackie virus as the underlying trigger of an autoimmune syndrome in humans and earned several awards in international meetings.
A postdoctoral training at The Rockefeller University (New York, NY) introduced Dr. Tapinos to the field of Molecular Neuroscience where he studied how pathogenic Leprosy Bacteria invade and regulate the glial cells of the peripheral nervous system to produce peripheral neuropathy. This work revealed for the first time a mechanism for non-immune mediated demyelination and uncovered new signaling pathways that regulate glial cell functions. Following his postdoctoral training at Rockefeller, Dr. Tapinos joined the Faculty at Geisinger Clinic where he established the Molecular Neuroscience and Neuro-Oncology Laboratory and held the position of Director of Neurosurgery Research.
Boxerman, Jerrold L.
Dr. Boxerman graduated from Harvard University and completed a residency in Diagnostic Radiology at The Johns Hopkins Hospital, where he was also chief resident. He subsequently completed a fellowship in Diagnostic Neuroradiology at The Johns Hopkins Hospital. His special interests are in MRI and neuroradiology, including perfusion-weighted MRI for characterizing and determining the treatment response of brain tumors, and multi-center imaging trials related to brain tumors. Dr. Boxerman is a senior member of the American Society of Neuroradiology and holds a certificate of additional qualification (CAQ) in Neuroradiology and is a Fellow of the American College of Radiology. He is the Section Director of Neuroradiology, Medical Director of the Brain Science Program MRI Research Facility, and a Professor of Diagnostic Imaging at the Warren Alpert Medical School of Brown University.
Dr. Lourenco received her undergraduate degree from Harvard University in 1998. She then received her medical degree from the University of Massachusetts Medical School in 2002. She completed her residency in diagnostic radiology at The Warren Alpert Medical School of Brown University in 2007 and then completed a fellowship in women’s imaging at the Beth Israel Deaconess Medical Center in 2008. Dr. Lourenco’s primary focus is in women’s imaging. She is a Professor of Diagnostic Imaging and Diagnostic Radiology Residency Program Director at The Warren Alpert Medical School of Brown University. Dr. Lourenco is fluent in Portuguese and Spanish. She is a Fellow of the Society of Breast Imaging.
Dr. Maxwell completed a fellowship, interventional radiology, at Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, New York, NY. He did a diagnostic radiology residency at The Warren Alpert Medical School of Brown University, Brown University-affiliated hospitals in Rhode Island and an internship at Newton-Wellesley Hospital, Harvard Medical School/Tufts University School of Medicine in Massachusetts. Dr. Maxwell earned a BS degree, honors biochemistry, magna cum laude, from the University of Washington, Seattle, WA and his MD from The Robert Larner, M.D. College of Medicine at The University of Vermont. He is a member of the American College of Radiology, Radiological Society of North America and the American Roentgen Ray Society, among others.
Undergraduate Research Assistant
Luoyun Wang is a freshman undergraduate at Brown, studying Computational Biology. She is very interested in the intersection of human health, microbiology, and CS. Her research interests include computational microbiology and virology. She is currently working on the clinical trials of a radionics and deep learning-based pipeline in the lab.
Andy is a first-year studying Applied Math-Computer Science at Brown. He is originally from Philadelphia, PA. He’s interested in applying machine learning to improve the lives of others, especially through healthcare.
Justin is a senior pursuing a BS in Biology at Brown University. He has expertise in COVID-19 retrospective epidemiology studies. He is currently applying unsupervised learning and large language models to predict long COVID outcomes.
Taishi is an undergraduate student from Japan studying Applied Math-Computer Science at Brown. His interests include deep learning and its applications in healthcare.
(Radiology, Harvard Medical School)
(Radiology, The Warren Alpert Medical School of Brown University)
(Interventional Radiology, The Warren Alpert Medical School of Brown University)
(Anesthesiology, Weill Cornell Medical Center)
Choi, Ji Whae
(Urology, Rutgers University – NJ Medical School)
Tran, Thi My Linh
(Medicine, Johns Hopkins School of Medicine)
(Medicine, Weill Cornell Medical Center)
(Radiology, Xiangya Hospital)
(MD student, Weill Cornell Medical Center)
(School of Informatics, Hunan University of Chinese Medicine)