The Team

The Team

Principal Investigators


Leo Sugrue

Leo Sugrue, MD, PhD

Bio

Dr. Leo Sugrue is a neuroscientist and neuroradiologist who researches the brain networks responsible for complex thought and behavior and their involvement in neuropsychiatric illness. He has a joint appointment in the Department of Psychiatry and works closely with colleagues at the Weill Institute for Neurosciences and the Dolby Center for Mood Disorders to develop novel network-based approaches to image and treat brain disorders using closed-loop brain stimulation and brain-directed focused ultrasound. 

Dr. Sugrue directs the Laboratory for Precision Neuroimaging (LPN) at UCSF, which emphasizes the integration of advanced brain imaging with genetic, health, and behavioral data to better understand, diagnose, and treat brain disorders in individual patients. He is also a co-investigator for the national Adolescent Brain and Cognitive Development Study (ABCD), and his group works to leverage “big data” from studies like ABCD to understand the neuroscience of brain development, health, and disease. 

Dr. Sugrue completed his undergraduate education and PhD in Neuroscience at Stanford University and received his MD from Johns Hopkins University School of Medicine. He completed residency in diagnostic radiology and fellowship in Neuroradiology at UCSF before joining the faculty in 2014. In 2022 he co-founded the Focused Ultrasound in Neuroscience program at UCSF. Dr. Sugrue grew up in Dublin and visits Ireland regularly; in his spare time, he enjoys cooking, gardening, and tinkering with old motorcycles.

 

Andreas Rauschecker, MD, PhD

Bio

Dr. Andreas Rauschecker is Principal Investigator of the Brain Research in Artificial Intelligence and Neuroimaging (BRAIN) laboratory at UCSF.  Dr. Rauschecker is a neuroradiologist and a neuroscientist by training.  He is interested in better understanding brain function and dysfunction through the use of magnetic resonance imaging, and specially through the use of advanced image analytics and artificial intelligence applied to brain imaging data.  Dr. Rauschecker completed his undergraduate education in Biology and Psychology at Georgetown University and a Master's in Neuroscience at Oxford University.  He obtained his MD and PhD (Neuroscience) degrees at Stanford University.  He then completed his residency training in diagnostic radiology at the University of Pennsylvania and his neuroradiology fellowship at UCSF.  In addition to directing his laboratory, Dr. Rauschecker is attending neuroradiologist at UCSF and Benioff Children’s Hospital, Associate Program Director of UCSF’s Neuroradiology Fellowship Program, co-Executive Director of the Scientific Research Group of UCSF’s Center for Intelligent Imaging (ci2), and co-chair of UCSF’s Research Data Science Council.  In his spare time, Dr. Rauschecker loves exploring the outdoors, eating great food, and traveling to new places, especially with his family.

 


 

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.