Current Lab Members

Pierre Nedelec, MS, MTM
Computational Data Scientist
Pierre is a Data & Computer Scientist in the lab, focusing on developing new methods and tools to enable the lab’s various research projects.
UCSF Bio

Ryan Michael Nillo
Research Assistant, BA
Ryan is a research assistant who graduated from Carleton College. He is interested in the physical brain changes that occur in patients with neurodegenerative disease and psychiatric disorders (i.e. differences in cortical thickness/volume, diffusion, and functional activity).
UCSF Bio

Aditya Murali
Research Assistant
Aditya is a junior at UC Berkeley majoring in Bioengineering. As of now, he’s currently working on classifying radiology protocols using free clinical text as input.

Neel Banerjee
Research Assistant
Neel is a fourth-year undergraduate at Georgetown University majoring in Neurobiology. His research interests include mapping white matter abnormalities in pediatric brain cancer survivors.

Rahul Ravishankar
Research Assistant
Rahul is a second-year undergraduate at UC Berkeley majoring in Computer Science. His research is centered around clustering methods for MRI diagnoses.

Gunvant Chaudhari
Research Assistant, MS4
Gunvant is a fourth-year MD student at UCSF applying into Diagnostic Radiology residency. His research interests include developing explainable machine learning-based tools to aid radiologists in interpreting imaging and generating radiology reports.
Samuel Lashof-Regas
Yearlong Research Fellow, MS4
Samuel is a research fellow supported through the Yearlong Inquiry program through the UCSF School of Medicine Inquiry Office. Samuels’ work is centered around understanding behavior and neuropsychiatric disease through the combination of neuroimaging, big data, and electrophysiology to improve both our fundamental understanding and patient care.
Stephen Wahlig, MD
Diagnostic Radiology Resident, PGY-4
Stephen received his MD from Duke University in 2019 and is currently a third-year diagnostic radiology resident at UCSF. His research interests include developing deep learning-based tools to streamline the radiology workflow, specifically with regard to the interpretation of brain MRI exams for follow-up of multiple sclerosis.
Josh Chen
Research Assistant, MS4
Josh Chen is a 4th year MD student at UCSF interested in diagnostic radiology. Josh completed his undergraduate degree in Public Health at UC Berkeley in 2018. Josh’s current research involves deep learning algorithms in assisting radiologists’ with the interpretation of infant myelination status on MRI.
Simon Pan, MD PhD
PGY-1 Medicine Intern, Incoming UCSF Radiology Resident
Simon Pan is a graduate of the UCSF MSTP program and an incoming diagnostic radiology resident at UCSF who is interested in neuroradiology. His research interests are centered on using informatics methods to investigate multimodal interactions of environmental, genetic, and socioeconomic factors on brain development, plasticity, and neuropsychiatric disease.
Reza Eghbali, PhD
Health Innovation Fellow, UCSF, UC Berkeley
Reza Eghbali is a Health Innovation fellow and UCSF/UC Berkeley. Reza Eghbali received his Ph.D. in Electrical Engineering and a master's degree in Mathematics from the University of Washington, Seattle. He has a B.Sc. in Electrical Engineering from Sharif University of Technology, Tehran.
Yannan Yu, MD
Diagnostic Radiology Resident, R-1
Yannan Yu is a first-year diagnostic radiology resident at UCSF. Her research focused on neuroimaging, especially stroke imaging, including MR/CT perfusion, diffusion-weighted imaging, and vessel wall imaging.
Collaborators
Jeffrey D. Rudie, MD PhD
Adjunct Assistant Professor, University of California San Diego, Dept of Radiology
Staff Emergency/Neuroradiologist, Scripps Radiology Clinic
Dr. Jeffrey Rudie completed his MD PhD at UCLA in neuroscience, followed by radiology residency at U Penn and Neuroradiology fellowship at UCSF. He is an emergency/neuroradiologist at Scripps Clinic in San Diego and an adjunct assistant professor of Radiology at UCSD. He is actively involved in both academic research and industry projects focused on developing artificial intelligence tools that can be integrated into the clinical workflow to improve the accuracy and efficiency of neuroradiology. This includes tools for automated segmentation and longitudinal assessment of intracranial metastases and diffuse gliomas.
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