Team

I have more than 15 years experience in computer vision, signal processing, graph theory, medical imaging and informatics. I have had continuous and successive experiences in forming and leading research teams comprising of basic and clinical scientists in executing NIH-funded research projects. I have published more than 100 peer reviewed papers ranging from microwave engineering, superconductivity, image/signal processing, vision, graph theory and neuroscience, and two US patents. I have attracted several NIH grants, on graph algorithms for accelerated MRI, theoretical neuroscience and network modeling of dementia and Parkinson’s. These include the prestigious EUREKA and BRAIN Initiative grants by the NIH.

The defining characteristic of my work has been inter-disciplinarity: finding innovative ways to apply computation and algorithms to biomedical applications. My group was an early adopter of mathematical models of brain connectivity networks, a subject that marries computer science with neuroradiology. I have deep interest in the graph properties of brain networks, and how they are altered in neurological disorders like epilepsy, dementia, movement disorders, traumatic brain injury and stroke. My team has developed novel image reconstruction algorithms for fast MRI, motion correction for MR angiography, and new methods in tractography, Q-ball imaging, brain connectivity networks and computational neurology. 

My lab now focuses on computational and graph theoretical modeling of the brain, using neuroimaging technologies combined with mathematical modeling. My research program is perfectly poised to help bring the fields of neurology and radiology into the era of personalized, precision medicine, using mathematical modeling and data science.

• PhD, 05/2005 - Electrical and Computer Engineering, Cornell University 
• BE, 12/1998 - Electrical Engineering, University of Auckland

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Huaqing Jin is a post-doctoral researcher at Raj Lab, where he focuses on uncovering the intricate relationships between functional and structural connectivity using sophisticated mathematical models. With a strong interest in neuroimaging data analysis, Huaqing aims to develop robust statistical methods to extract valuable biomarkers from various neuroimaging modalities, such as MEG, EEG, and fMRI, to better understand different diseases.

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Daren is a Machine Learning Specialist in the Raj Lab. His research interests include the modeling of Alzheimer’s Disease, Brain Segmentation, Parcellation, and other applied Deep Learning methods in Neuroscience. His recent project is concentrated on predicting cognitive ability using subjects’ T1-weighted MRI scans from the ADNI dataset. Daren is also responsible for handling the technical issues such as server maintenance in the lab.

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Farras is an Assistant Specialist in the Raj Lab. Farras’s interests lie in graph theory and its applications to brain modeling, and in particular in the dynamics between functional and structural networks, and how to obtain one from the other. His work on predicting function from structure via graph diffusion was well received in the neuroscience community. Farras is additionally interested in the emerging subjects of graph signal processing, graph wavelets, and their applications to brain networks. He previously worked on reconstruction of near infrared spectroscopy images, and prior to that pursued research on wavelet frames design. His orthogonal nearly symmetric wavelets are included in the Matlab Wavelets Toolbox. Farras is a pianist and a published and exhibited photographer.

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Ben is a BioEngineering PhD student in the Raj Lab. His interests are varied, but they center around ways to predict brain function from structure. We use linear mathematical models to understand the brain’s structure-function problem, and Ben seeks to understand how different model parameters relate to health, development, and consciousness. Ben also does much of the Raj Lab data processing, which includes structural and diffusion MRI processing through pipetography, functional MRI with fMRIPrep and XCPEngine. Outside of the lab, Ben enjoys reading fantasy, science fiction and philosophy, playing competitive games, painting, and hanging out with cats.

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Robin is a research assistant in Raj Lab. Her interests include understanding the relationship between structure and function as it pertains to neurodegenerative diseases, TBI, and altered states of consciousness. She particularly enjoys the intersection of cognitive neuroscience and philosophy of mind, as well as philosophy of science. Outside of the lab, Robin enjoys triathlon, rock climbing, and painting.. 

Chaitali is a post-doc in the Raj Lab. She is interested in understanding the factors affecting Alzheimer’s disease (AD) pathology progression, and uses the Network Diffusion Model as well as its extension - the Nexopathy in silico (Nexis) model to achieve that. Specifically, she is investigating AD pathology progression by combining the effects of network (connectome-mediated) spread, modulators of connectome-mediated spread (such as microglia), and cell-type-based regional vulnerability to the disease. In addition, Chaitali is highly interested in the translational aspects of understanding AD pathology and employs mathematical modeling on data acquired from mouse models of AD and human AD patients. She also has a joint appointment with the Chaumeil Lab  where she applies MR spectroscopy techniques to assess cerebral metabolism in mouse models of AD. Outside of lab, Chaitali enjoys going for runs by the Piers in SF, acrylic painting, and playing badminton. 

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