People

 

Education
Ph.D. in Neuroscience, St. Louis University
M.S. in Neuroscience, St. Louis University
B.S. in Psychology, University of Massachusetts

Experience
2016 - present: Ghada Irani Chair in Neuroscience
2013 - present: Provost Professor of Ophthalmology, Neurology, Psychiatry, and the Behavioral Sciences, Radiology, Engineering and Biological Sciences at the Keck School of Medicine of USC
2013 - present: Director, USC Mark and Mary Stevens Neuroimaging and Informatics Institute
2013 - present: Director, USC Laboratory of Neuro Imaging
2010 - 2012: Associate Vice Provost of Informatics, University of California, Los Angeles
2010 - 2013: Associate Dean, David Geffen School of Medicine, University of California, Los Angeles
1993 - 2010: Professor, Department of Neurology, University of California, Los Angeles
1993 - 2013: Associate Director, Division of Brain Mapping, Neuropsychiatric Institute, University of California, Los Angeles
1987 - 2013: Director, Laboratory of Neuro Imaging, Department of Neurology, University of California, Los Angeles

Research
Dr. Toga’s research focuses on neuroimaging, informatics, mapping brain structure and function, and brain atlasing. He has developed multimodal imaging and data aggregation strategies and applied them in a variety of neurological diseases and psychiatric disorders, including neurodegenerative diseases, neurovascular diseases, and ocular diseases. His work in informatics includes the development and implementation of some of the largest and most widely used databases and data mining tools linking disparate data from genetics, imaging, clinical, and behavioral studies, and supporting global efforts in Alzheimer’s disease, Huntington’s Disease, and Parkinson’s Disease. His work also involves measurement of the dynamic brain during development and aging, and as a result of insult.

Skills
Neuroscience
Research
Management

 

Education
2017: Ph.D. in Neuroimaging, King’s College London
2006: M.S. in Aerospace Engineering, University of Maryland
2004: B.S. in Electrical Engineering, Johns Hopkins University

 

Education
2013: Ph.D. in Neuroscience, Brown University
2006: B.A. in Psychology, University of Colorado Boulder

Research
Dr. Ard aims to improve scientists’ understanding of neuroscientific data through novel visualizations, enabling human insight into highly complex datasets. Before joining LONI, he worked with USC’s Institute for Creative Technologies (ICT), where he mastered Virtual Reality techniques which he now applies to neuroimaging data.

 

Education
2012: Ph.D. in Neuroscience, University of Pittsburgh
2007: B.S. in Neuroscience, University of Pittsburgh

Research
Dr. Bienkowski is interested in characterizing brain cell types and understanding their susceptibility to neurodegenerative diseases like Alzheimer's disease and retinal degenerative diseases. His translational research laboratory (USC Center for Integrative Connectomics) uses state-of-the-art connectomics and transcriptomics approaches to investigate cell type-specific progressive changes to gene expression and connectivity in rodent and human brain tissue. A major goal of the lab is to build translational cell-type atlases to guide clinical drug development and enhance the effectiveness of treatment plans at progressive disease stages.

 

Education
2006: Ph.D. in Neuroscience, UCLA
1994: B.A. in Business Administration and Accounting, College of William and Mary

Experience
2019 - present: Assistant Professor of Neurology, USC
2019 - present: Director of Education, USC Stevens Neuroimaging and Informatics Institute
2013 - 2019: Assistant Professor of Research, USC
2011 - 2013: Assistant Researcher, UCLA
2009 - 2011: Post doctoral fellow, UCLA
2006 - 2009: Post doctoral fellow, UC Berkeley
2002 - 2006: Graduate student researcher, UCLA
2003: Teaching assistant to Dr. Arnold Scheibel, UCLA

Research
Dr. Braskie’s research evaluates how genetic and environmental risk factors for Alzheimer’s Disease (AD) relate to brain structure, function, and connectivity throughout adulthood, with an emphasis on metabolic risk. She primarily studies cognitively intact adults and those with early mild cognitive impairment, studying how AD risk-related biological mechanisms and signaling pathways are associated with brain changes, using relevant blood and cerebrospinal fluid measures, as well as multimodal imaging (structural and functional MRI, diffusion tensor imaging, and PET).

 

Dr. Ching's research focuses on large-scale, international neuroimaging and genomics studies of mental illness. He is part of the core leadership of the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium where he designs and implements standardized processing and analysis techniques used to improve study replicaton and generalizability in a wide range of brain disorders. He chairs the ENIGMA Bipolar Disorder Working Group (https://enigma.ini.usc.edu/ongoing/enigma-bipolar-working-group/).

Education
2019: Ph.D. in Neuroscience, UCLA
2006: B.A. in Neuroscience and Philosophy, Pomona College

 

Education
2016: Ph.D. in Biomedical Engineering and Neuroscience, University of Queensland
2010: M.Sc. in Information Technology Engineering & Signal Processing, Sharif University of Technology
2008: B.Sc. in Information Technology Engineering, Sharif University of Technology

 

Education
2013: Ph.D. in Electrical Engineering, Yale University
2007: B.S. in Mathematics and Polish Literature, University of Chicago

Research
Dr. Duncan’s expertise lies in the development of analytical tools to extract information from biomedical data. Both her Ph.D. and postdoctoral research used EEG data to isolate patterns indicating the onset of epileptic seizures. She has worked on developing algorithms, such as Unsupervised Diffusion Component Analysis, to identify early signs of Alzheimer's disease in patients using structural MRI data. Her recent projects include identifying biomarkers to predict epilepsy following a traumatic brain injury and using Virtual Reality to improve segmentation, a manual error-correction process required to analyze brain imaging data.

 

Education
2012: Ph.D. in Biomedical Engineering, UCLA
2006: B.A. in Biomedical and Electrical Engineering, Johns Hopkins University

Research
Dr. Jahanshad is part of INI’s Imaging Genetics Center, where she researches genetic influences on brain structure using high-resolution structural and diffusion imaging. She also develops protocols for large-scale meta-analyses of brain structure and connectivity for the ENIGMA consortium. Her work with diffusion imaging involves monitoring the effects of infectious diseases, such as HIV, on the brain.

 

Education
2009: Ph.D. in the Faculties of Medicine, Science and Veterinary Medicine, University of Bern
2004: Dipl. Sc. Nat. in Biology (Neuroscience focus), Swiss Federal Institute of Technology

Experience
2016: Assistant Project Scientist at the Laboratory of Functional MRI Technology, Ahmanson-Lovelace Brain Mapping Center, UCLA
2016: Postdoctoral researcher at the Laboratory of Functional MRI Technology, Ahmanson-Lovelace Brain Mapping Center, UCLA
2010 - 2013: Postdoctoral researcher at the Department of Psychiatric Neurophysiology, University Hospital of Psychiatry, University of Bern, Switzerland
2009 - 2010: Research assistant at the Department of Psychiatric Neurophysiology, University Hospital of Psychiatry, University of Bern, Switzerland

Research
Dr. Jann develops analytical tools and clinical translations of functional MRI technology. He studies the relationship between functional connectivity, complexity and metabolism of brain networks. His multimodal approach involves a combination of fMRI, connectivity measures, cerebral blood flow, Transcranial Magnetic Stimulation (TMS) excitation and inhibition, and Magnetic Resonance Spectroscopy (MRS). He is also exploring the use of neuromodulation, such as TMS, in the treatment of various neuropsychiatric disorders.

 

Education
2016: Postdoctoral Fellowship in Imaging of Neurodevelopment, UC San Francisco
2012: Ph.D. in Biomedical Engineering (specialty: brain image analysis), McGill University
2011: Ph.D. in Biomedical Engineering, Montreal Neurological Institute, McGill University
2003: M.S. in Biomedical Engineering, Hanyang University
2000: B.S. in Mechanical Engineering, Hanyang Unversity

Research
Dr. Kim’s research spans an interdisciplinary cross-section of medical image processing, machine learning and neuroscience, covering both clinical neurology and neuropsychiatry. He studies multicontrast image registration and segmentation as well as surface modeling of both cortical and subcortical structures. One of his current projects involves the prediction of neurodevelopmental outcomes for preterm babies. He is also developing an online neuroimaging data quality control (image QC) system.

 

The overarching aim of Dr. Lawrence's research is to improve our understanding of the neural mechanisms underlying neurodevelopmental conditions, with the long-term goal of contributing to personalized medicine approaches for interested individuals. Her work leverages large-scale multimodal neuroimaging data—including diffusion-weighted MRI and resting-state functional MRI—together with advanced imaging and statistical methods. Her primary line of research characterizes the neurobiological underpinnings of brain-based conditions such as autism and attention-deficit/hyperactivity disorder (ADHD). In her other main branch of research, she investigates typical brain development and moderating factors in large-scale population-based samples.

 

Website: https://chan.usc.edu/npnl/

Education
2012: PhD In Occupational Science, concentration in Cognitive Neuroscience, USC
2008: M.A. in Occupational Therapy, USC
2006: B.A. in Kinesiology and English, Rice University

Research
Sook-Lei Liew is an Associate Professor and Director of the Neural Plasticity and Neurorehabilitation Laboratory at the University of Southern California. She has joint appointments in the divisions of Occupational Science and Occupational Therapy, Biokinesiology and Physical Therapy, Biomedical Engineering, Neuroscience, and Neurology, is a member of the USC Stevens Neuroimaging and Informatics Institute. She is the Chair of the ENIGMA Stroke Recovery Working Group, which aims to meta-analyze high-resolution brain imaging and behavioral outcomes in individuals after stroke from thousands of patients collected across over 50 research cohorts worldwide. She also is a co-Director and co-founder of the USC SMART-VR (SensoriMotor Assessment and Rehabilitation Training) Center (smartvr.usc.edu), and lead PI for the NIH-funded R25 Reproducible Rehabilitation Research (ReproRehab) Educational Program (reprorehab.usc.edu).

 

Education
2019: Ph.D. in Neuroscience, USC
2010: B.S. in Honors Neuroscience, Brown University

Experience
2011 - 2013: Research Assistant, Developmental Cognitive Neuroimaging Laboratory, Children

Research
Structural and functional lateralization of perisylvian language centers; development of diffusion MRI microstructural measures; cortical microstructure and neuroanatomy

 

Education
1999: M.S. in Computer Science, UCLA
1997: Ph.D. in Physics, UCLA
1993: M.S. in Physics, UCLA
1991: B.S. in Physics and Mathematics, University of Wisconsin

Experience
2002 - 2013: UCLA Laboratory of Neuro-Imaging
1998 - 2002: UCLA Department of Radiological Sciences

Research
Dr. Neu’s research involves the management and visualization of neuroinformatics data. He develops numerical methods for image classification and feature extraction. At LONI, he is a key contributor to the Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Global Alzheimer’s Association Interactive Network (GAAIN), the Parkinson’s Progression Markers Initiative (PPMI), and other projects.

Skills
JAVA, C++/C, Fortran, JSP, EJB, J2EE, JDBC, OOD, UML, XML, HTML, SQL, X/Motif
UNIX, Solaris/SunOS, MS Windows, X-Windows

 

Education
2019: Ph.D. in Neuroscience, USC
2007: B.A. in Cognitive Science, University of California, Berkeley

Research
Dr. Nir’s research focuses on identifying early and reliable microstructural brain MRI biomarkers of neurodegeneration in multi-site studies of aging, Alzheimer’s disease, and HIV.

 

Education
2019: Ph.D. in Clinical Neurosciences, Cambridge University, UK
2015: MSc. in Engineering, University of Florida, USA
2013: Diploma in Engineering, National Technical University of Athens, Greece

Research
Dr. Pappas aims to understand neuropathology in clinical populations such as stroke and Alzheimer's disease. He uses multi-modal brain imaging methods including functional MRI, diffusion imaging, perfusion imaging, and spectroscopy. Before joining LONI, he conducted post-doctoral research at UC Berkeley studying the neural mechanisms of recovery in stroke patients.

 

Education
2016: Ph.D. in Psychology-Behavioral Neuroscience, University of Missouri St. Louis
2014: M.A. in Psychology, University of Missouri St. Louis
2011: B.L.S. in Psychology and Writing, University of Missouri St. Louis

Research
Dr. Salminen studies biological markers of suboptimal brain health and leads the ENIGMA-Environment initiative to understand how environmental exposures such as air pollution affect the brain, an effort now jointly funded by the National Institutes of Environmental Health Sciences (NIEHS) and the National Institute on Aging (NIA). Her work uses advanced methods in brain imaging, big data, and artificial intelligence to understand the role of emotional distress and environmental toxins (e.g., air pollution, secondhand smoke) as critical drivers of suboptimal brain health in older adults. She is particularly interested in studying how demographic factors, mental health, lifestyle, and environment exposures interact to exaggerate brain aging and increase risk for Alzheimer’s disease.

 

Education
2019: Ph.D. in Biomedical Engineering, University of Southern California
2016: M.S. in Bioengineering, University of California, Los Angeles
2014: B.S in Engineering Physics, Tsinghua University

Experience
2022 - present: Assistant Professor of Research Radiology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California
2021 - present: Junior Fellow, ISMRM
2019 - present: Research Scientist, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California
2020 - 2021: Trainee representative, ISMRM perfusion study group

Research
Dr. Shao is Assistant Professor of Research Radiology at the USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine USC. His research focuses on developing ASL sequences with high spatial/temporal resolution. Currently Dr. Shao is working on a novel MR pulse sequence and modeling algorithm to quantify the water exchange rate (kw) across the blood–brain barrier (BBB) without contrast, and to evaluate its clinical utility in a range of neurological disorders including cerebral small vessel disease (SVD), Alzheimer's Diseases (AD), etc. Dr. Shao is also working on high resolution 7T ASL to quantify layer-dependent CBF and obtain concurrent measurement of CBV, BOLD and CMRO2.

 

Education
2005: Ph.D. in Electrical Engineering, Boston University
1999: M.S. in Electrical Engineering, Southeast University
1996: B.S. in Electrical Engineering, Southeast University

Experience
2009 - 2013: Assistant Professor, Department of Neurology, UCLA School of Medicine
2005 - 2009: PostDoctoral Fellow, Department of Neurology, UCLA School of Medicine

Research
Dr. Shi develops cutting-edge image analysis algorithms, which he applies to the study of human brain structure and function. He seeks to more accurately model the brain’s fibers in diffusion imaging using Fiber Orientation Distribution (FOD) reconstruction. He also studies anatomical shape modeling using the Laplace-Beltrami system, in order to create better brain mapping algorithms for use in researching Alzheimer’s Disease, retinopathies, and other disorders.

Skills
Level set algorithms, inverse problems and regularization, statistical signal processing.

 

Education
1998: Ph.D. in Neuroscience, UCLA
1993: M.A. in Mathematics and Philosophy, Oxford University
1991: B.A. in Greek and Latin Languages, Oxford University

Experience
- : Professor of Neurology, Professor of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA
- : Professor of Neurology, David Geffen School of Medicine, UCLA
- : Associate Professor of Neurology, David Geffen School of Medicine, UCLA
- : Assistant Professor of Neurology, David Geffen School of Medicine, UCLA
- : Fellow, Howard Hughes Medical Institute
- : Research Grantee, United States Information Agency, Washington, DC
- : Fulbright Scholar, U.S.-U.K. Fulbright Commission, London, England

Research
Dr. Paul M. Thompson is a Professor of Neurology, Psychiatry, Radiology, Pediatrics, and Engineering, at the University of Southern California where he directs the Imaging Genetics Center and is Associate Director for the Stevens INI. Dr. Thompson is also Principal Investigator and Co-founder of the ENIGMA Consortium (http://enigma.ini.usc.edu). ENIGMA has cooperatively analyzed data from over 45 countries to publish the largest worldwide neuroimaging studies of over 15 brain diseases and conditions, including Parkinson’s disease, epilepsy, ataxia and brain injury, PTSD, substance use disorder, bipolar disorder, major depression, and neurodevelopmental conditions including OCD, ADHD, and ASD. In parallel, the ENIGMA Consortium has led worldwide imaging genetics studies that discovered over 500 common and rare genomic variants that affect brain structure, disease risk, and brain connectivity. Recent efforts have discovered major factors influencing brain development and disease worldwide, in populations of diverse ancestry. Dr. Thompson also leads AI4AD—an $18M NIH initiative developing AI for automatic disease subtyping, genetic target discovery. and drug discovery in Alzheimer's disease.

 

Education
2010: M.S.C.E. in Clinical Epidemiology, University of Pennsylvania School of Medicine
1998: Ph.D. in Biophysics, University of Science and Technology of China
1993: B.S. in Biophysics, Fu Dan University

Experience
2016 - present: Professor, Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA
2016 - present: Director of Imaging Technology Innovation, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA
2016 - present: Professor (secondary), Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA
2012 - 2016: Executive Director, UCLA-Beijing Joint Center for Advanced Brain Imaging
2015 - 2016: Professor-in-Residence (secondary), Department of Radiology, UCLA David Geffen School of Medicine
2015 - 2016: Professor-in-Residence, Department of Neurology, UCLA David Geffen School of Medicine
2011 - 2015: Associate Professor-in-Residence (secondary), Department of Radiology, UCLA David Geffen School of Medicine
2010 - 2015: Associate Professor-in-Residence, Department of Neurology, UCLA David Geffen School of Medicine
2011 - 2013: Adjunct Associate Professor, Department of Radiology, University of Pennsylvania School of Medicine
2006 - 2010: Research Assistant Professor, Department of Neurology, University of Pennsylvania School of Medicine
2003 - 2010: Research Assistant Professor, Department of Radiology, University of Pennsylvania School of Medicine

Research
Dr. Wang runs the Laboratory of Functional MRI Technology (LOFT), where he develops techniques and clinical translations of arterial spin labeling (ASL) and performs cross-scale and modality complexity analysis of resting state fMRI and electrophysiology data. Dr. Wang leads projects to develop and validate imaging biomarkers of cerebral small vessel diseases (cSVD) and vascular cognitive impairment and dementia (VCID). He also researches electric current mapping of transcranial direct current stimulation (tDCS). Another current project involves the development of low-dose CT perfusion technology, which may help significantly reduce radiation exposure without compromising image quality.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Education
2019: M.S. in Electrical Engineering, University of Southern California
2017: B.E. in Electronics Engineering, Gujarat Technological University

Skills
Python, C++, Keras, Tensorflow, Numpy, Pandas, Scikit-Learn

 

Education
2018: Ph.D. in Electrical Engineering, Ohio University
2013: M.S. in Electrical Engineering, Ohio University

Experience
2018 - 2020: Post-doctoral Scholar, UCLA
2015: Software Engineer PhD Intern, Dermspectra LLC
2014: Image Processing Intern, Intel

Skills
Computer vision, deep learning, image processing, data science

 

Education
2019: M.S. in Computer Science, USC
2011: B.S. in Ecology and Evolutionary Biology, UCLA

Experience
2009 - 2010: SRP Student at LONI

 

Education
2012: M.S. in Computer Science, University of Houston-Clear Lake
2009: Bachelors Degree in Computer Engineering, K.K. Wagh I.E.E.R., University of Pune

Skills
JAVA/GWT, Android, HTML, Javascript, jQuery

 

 

 

 

Education
MLIS, University of California, Los Angeles
B.A. in English, California State University, Los Angeles (Magna cum Laude)

Skills
Planning and developing database and software applications supporting medical imaging and general laboratory operations

 

 

 

 

Education
2013: M.S. in Biomedical Visualization, University of Illinois at Chicago
1993: B.A. in Sociology, Minors in Music and Science, University of California, San Diego

Experience
3 years Biomedical Visualization for Aerospace Research and Education
5 years Scientific Graphic Design

 

 

 

Education
2007: M.S. in Biomedical Visualization, University of Illinois at Chicago
2001: B.A. in Studio Arts, Columbia College Chicago

Experience
2007 - 2014: Scientific Visualizer/3D Medical Animator, TheVisualMD.com (formerly known as Anatomical Travelogue)

 

Education
2019: Ph.D. in Biomedical Engineering, USC
2016: M.S. in Biomedical Engineering, USC
2012: Master of Engineering, Center for Earth Observation and Digital Earth, Chinese Academy of Sciences (CAS)
2009: Bachelor of Engineering, School of Automation Control and Electrical Engineering, Beihang University

Experience
Multimodal neuroimaging of neurovascular diseases.

Research
Machine Learning, Image Synthesis, Brain Aging, and Alzheimer’s Disease.

 

 

 

 

Education
2018: M.D. Sechenov University

Research
Traumatic brain injury, post-traumatic epilepsy, comprehensive EEG analysis.

 

 

 

 

 

 

 

Education
2016: Ph.D. in Neuroscience, University College London

Research
Brain connectivity and sex differences in Alzheimer's disease using machine learning and visualization of human datasets.

 

Education
2019: Ph.D. in Biomedical Engineering, USC
2008: M.S. in Biomedical Engineering, National University of Colombia
2003: M.D., Universidad Del Norte

Experience
MR & Neuroradiology Rotation - St. Joseph's Hospital, Bogota, Colombia

 

 

 

 

 

 

 

 

 

 

 

Laboratory of Neuro Imaging Keck School of Medicine of USC University of Southern California 2025 Zonal Avenue Los Angeles, CA 90033 Phone: 323-44-BRAIN

 

 

 

 

 

 

 

 

 

 

 

 

Education
2017: M.S. in Electrical Engineering, University of Southern California
2013: B.S. in Engineering, Sichuan University

Experience
Machine Learning in Medical image analysis

Research
Diffusion image analysis, Fiber bundles segmentation

 

 

Statistical Genetics, Bayesian Statistics, Computational Neuroscience

Education
2016: B.S. in Mathematics, Tsinghua University

Experience
Research Assistant in Imaging Genetics Center, USC Stevens Neuroimaging and Informatics Institute
Research Assistant in Scientific Computing and Applied Statistics group, Department of Mathematical Sciences, Tsinghua University
Research Assistant in Brain Imaging lab, Department of Psychology, Tsinghua University

Research
Fast Heritability Estimation Method using Linear Mixed Model
Statistical Analysis of Brain Images

 

 

 

 

 

 

 

 

 

 

Education
MPH, USC
BA, UCLA

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Education
2022: MS in Neuroimaging and Informatics, University of Southern California
2020: BS in Cognitive Science specializing in Neuroscience, University of California, San Diego

 

 

 

 

Education
2012: Ph.D. in Experimental Psychology, University of California, San Diego
2005: M.A. in Research Psychology, California State University, Los Angeles
2001: B.A. in Psychology, University of California, Los Angeles

Experience
2012 - 2017: Post Doctoral Fellow, University of California San Diego

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Computational neuroimaging analysis and the application to studies of neuroanatomy and brain connectivity networks and their relationship to development, aging and pathological conditions.

Education
20101: Ph.D. in Signal Processing, Tampere University of Technology
2005: M.Sc. in Signal Processing and Communication, University of Edinburgh
2004: B.Sc. in Electronics and Information Engineering, Harbin University of Science and Technology

Experience
2010 - 2015: Postdoctoral Research Fellow, Montreal Neurological Institute, McGill University