People

Faculty

Bai, Harrison

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.

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.

Postdoc

Wu, Jing

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.

Medical Students

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.

 

Graduate Students

Yi, Thomas

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.

 

Halsey, Kasey

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.

Wang, Robin 

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).

 

Eweje, Sope

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.

Hsieh, Celina

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.

 

 

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Undergraduate Students

Purkayastha, Subhanik

Subhanik is a junior at Brown studying Computational Biology. He is originally from the great city of Philadelphia, PA. His academic and intellectual interests lie in the intersection between health and computer science. He is very interested in introducing aspects of technology and computation to issues surrounding human health. In the lab, He is developing a radiomics-based machine learning pipeline to predict various health indications from MR images. He hopes one day such technology can seamlessly integrate itself into the clinical workflow and boost the performance of our clinicians in diagnosing, characterizing, and treating all forms of cancer.

 

Kim, Chris

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.

Collaborators

Centintemel, Ugur

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.

Kimia, Benjamin

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

Wang, Luoyun

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.

 

Delworth, Andy

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.

 

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