Stanford Interdisciplinary Graduate Fellowships

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Stanford Interdisciplinary Graduate Fellow shares his research on "Simulating the impact of sensorimotor deficits on reaching performance" at a poster session.

Training the next generation of interdisciplinary neuroscientists

The Stanford Interdisciplinary Graduate Fellowship (SIGF) is a competitive, university-wide program that awards three-year fellowships to outstanding doctoral students engaged in interdisciplinary research. Three independent institutes, Bio-X, Wu Tsai Neurosciences Institute, and Sarafan ChEM-H award these graduate fellowships in the biosciences. 

The Wu Tsai Neurosciences Institute partners with the Vice Provost for Graduate Education and Stanford BioX to award Stanford Interdisciplinary Graduate Fellowships (SIGFs) in the area of neuroscience. We are grateful to Bio-X and the Bio-X Leadership Council for incorporating the SIGFs affiliated with the Institute into this year’s round of their long-standing and successful program.

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2023 SIGF Application

Funded SIGF projects

Funded research
Wu Tsai Neurosciences Institute
Mechanistic insights into glycerophospholipid metabolism in the lysosome

Phospholipid dysregulation is implicated in the pathogenesis of lysosomal storage disorders (LSDs). We found that glycerophosphodiesters (GPDs) accumulate in lysosomes derived from Batten disease models, a life-limiting LSD whose pathological mechanism remains elusive. GPDs are the degradation products of glycerophospholipid catabolism by phospholipases.

Funded research
Wu Tsai Neurosciences Institute
Leveraging screenomics to identify mental illness: Detecting bipolar disorder through computational analysis of smartphone screen data

Mental illnesses like bipolar disorder affect millions of people around the world, but early symptoms are often difficult to detect. Working across the disciplines of clinical psychology, communication, and computer science, my research will develop a novel computational tool to identify signals of mania and depression in real-time.

Funded research
Wu Tsai Neurosciences Institute
Design and development of a high-performance intra-cortical speech BCI

Many neurological injuries and diseases such as brainstem stroke and Amyotrophic Lateral Sclerosis (ALS) result in severe speech impairment, drastically reducing quality of life. Recent progress in brain-computer interfaces (BCI) has allowed these individuals to communicate, but performance is still far lower than typical spoken conversation speeds.

Funded research
Wu Tsai Neurosciences Institute
Inference via Abstraction: A framework for efficient Bayesian cognition

We propose a novel framework for efficient Bayesian cognition called Inference via Abstraction (IvA), which learns to approximate complex world models with simpler abstractions that capture main dependencies, but leverage structure in the prior distribution for efficient inference. We instantiate IvA with a combination of probabilistic graphical models and deep neural networks.

Funded research
Wu Tsai Neurosciences Institute
Elucidating mechanisms of microglial tiling

In a process called tiling, homeostatic microglia homogenously organize in a grid-like fashion to achieve efficient surveillance of the brain. The molecular mechanisms underlying tiling are unknown. I hypothesize that microglia use cell-surface proteins to sense density of neighboring microglia, thereby contributing to constant cell-to-cell distances.

Funded research
Wu Tsai Neurosciences Institute
Magnetic Resonance Imaging of Epileptogenesis

Absence epilepsy is a form of pediatric epilepsy which causes seizures with brief lapses in awareness. Electron microscopy results in a murine model of absence epilepsy support the hypothesis that maladaptive myelination plays a role in disease progression.