Co-director & Founder Dr. Harrison Bai is the Principal Investigator. 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. firstname.lastname@example.org
Co-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. 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.
Choi, Ji Whae
Ji Whae obtained her B.A. in Biological Sciences from Cornell University in 2018 and is now pursuing an M.D. at the Warren Alpert Medical School of Brown University. Her current research interests lie at the intersection of artificial intelligence and medicine using medical imaging.
Tran, Thi My Linh
Linh is a fourth-year medical student with an interest in AI and innovation in medicine. Her research interest includes developing clinical decision support tools powered by machine learning to assist interventional radiologists in patient selection and treatment planning. She also has four years of experience in surgical instrument design, business development, basic science, and AI research as well as a formal education in engineering and applied mathematics. In her free time, she likes to run, learn about stocks, travel, and hang out with her sister.
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.
Nicole Thomasian is a third-year medical student at Brown University. She graduated with Honors from Brown University with a BS in Neuroscience. Prior to matriculating at Brown’s Warren Alpert Medical School, she studied neural rewiring following stroke as a Fulbright Fellow in Japan. During medical school, Nicole worked on the implementation side of big data-driven decision support algorithms at the Emergency Digital Health Innovation Program. Nicole’s other projects explore the regulation of medical device cybersecurity, artificial intelligence, and nuclear technologies. She will attend the Harvard Kennedy School this fall as a Belfer Center Fellow with a focus on health security studies to pursue a combined MD/MPP.
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.
Thomas is a second year medical student at the Warren Alpert Medical School. He previously studied biomedical engineering and computer science at Johns Hopkins University where his research projects centered around image-guided surgery. Presently, he collaborates on a number of clinical big data projects.
He obtained his B.A. in Biochemistry from Colgate University in 2018 and is currently pursuing my M.D. at the Warren Alpert Medical School at Brown University. He works under Dr. Harrison X. Bai on interventional radiology publications involving lung tumor ablation and intra-procedural image guidance modalities.
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.
Celina graduated from Brown University with a B.S. in biomedical engineering and is currently a second-year medical student at the Warren Alpert Medical School. Her project involves using deep learning to predict cancer treatment response following embolization procedures.
Yang is a PhD student in Computer Science from China. Her current research interests are Machine Learning/Deep Learning for liver and tumor segmentation and response assessment personalized treatment planning and her research results have been widely published on medical image analysis journals.
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.
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.
Summer I-Team Collaboration Project Member
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.