Shafali S. Jeste

About

Shafali S. Jeste is a Professor and Department Chair of Pediatrics at UCLA's David Geffen School of Medicine. Her research focuses on neurodevelopmental disorders, particularly autism spectrum disorder (ASD), and she is involved in clinical trials and research activities aimed at understanding and predicting ASD in high-risk infants. Her work includes investigating electrophysiological biomarkers of sleep and cognition in syndromes such as Dup15q and Tuberous Sclerosis Complex, as well as exploring neural predictors of language function after intervention in children with autism. Dr. Jeste's contributions extend to studying developmental trajectories, neural responses to language, and social attention in neurogenetic syndromes, with a goal of informing clinical trial endpoints and advancing neuropsychiatric care for neurodevelopmental disorders.

Research topics

• Medicine
• Psychology
• Psychiatry
• Neuroscience
• Developmental psychology
• Computer Science
• Machine Learning
• Audiology
• Family medicine
• Genetics

Selected publications

• The Autism Biomarkers Consortium for Clinical Trials (ABC-CT): Scientific Context, Study Design, and Progress Toward Biomarker Qualification

  Frontiers in Integrative Neuroscience · 2020 · 134 citations

  Clinical research in neurodevelopmental disorders remains reliant upon clinician and caregiver measures. Limitations of these approaches indicate a need for objective, quantitative, and reliable biomarkers to advance clinical research. Extant research suggests the potential utility of multiple candidate biomarkers; however, effective application of these markers in trials requires additional understanding of replicability, individual differences, and intra-individual stability over time. The Aut…

  DOI

• Multivariate Neural Connectivity Patterns in Early Infancy Predict Later Autism Symptoms

  Biological Psychiatry Cognitive Neuroscience and Neuroimaging · 2020 · 62 citations

  Senior authorCorresponding
  DOI

• Electrophysiological signatures of visual statistical learning in 3‐month‐old infants at familial and low risk for autism spectrum disorder

  Developmental Psychobiology · 2020 · 11 citations

  Senior authorCorresponding

  Visual statistical learning (VSL) refers to the ability to extract associations and conditional probabilities within the visual environment. It may serve as a precursor to cognitive and social communication development. Quantifying VSL in infants at familial risk (FR) for Autism Spectrum Disorder (ASD) provides opportunities to understand how genetic predisposition can influence early learning processes which may, in turn, lay a foundation for cognitive and social communication delays. We examin…

  PublisherOA PDFDOI

• Visual Cortical Response Variability in Infants at High Familial Likelihood for Autism

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-03-09 · 1 citations

  articleOpen access

  Abstract Visual processing undergoes rapid refinement in the first year of life, supporting the emergence of higher-order cognitive, language, and motor functions. Visual evoked potentials (VEPs) provide a non-invasive measure of visual system maturation that may shed light on heterogeneous developmental trajectories among infants at high familial likelihood for autism. Infants with an older sibling with autism spectrum disorder (N = 177 at 6 months; N = 132 at 12 months) participated in the Inf…

  PublisherOA PDFDOI

• Conceptualizing Autism as a Behavioral Network: Transdiagnostic Associations with Co-occurring Psychiatric Conditions

  Research on Child and Adolescent Psychopathology · 2026-03-14 · 1 citations

  articleOpen access

  Autism is characterized by marked heterogeneity in behavioral presentation and high rates of co-occurring psychiatric symptoms, which hinder diagnostic precision, personalized intervention, and long-term quality of life. Approach and withdrawal behaviors—subserved by core motivational systems underlying action and emotion—may serve as transdiagnostic processes linking autism with common co-occurring conditions in childhood. Guided by this framework, we examined how autism-related approach–withdr…

  PublisherOA PDFDOI

Recent grants

• Administrative Core

  NIH · $138.5M · 2015–2026

• Genetics and Biomarkers Core

  NIH · $60.0M · 2007–2024

• Mechanisms of Change with Early Intervention in Tuberous Sclerosis Complex

  NIH · $2.6M · 2017–2023

Frequent coauthors

• Charles A. Nelson

  Harvard University

  126 shared

• Damla Şentürk

  University of California, Los Angeles

  91 shared

• Charlotte DiStefano

  82 shared

• Sara Jane Webb

  Seattle Children's Hospital

  78 shared

• Catherine A. Sugar

  Neurobehavioral Systems

  74 shared

• Mirella Dapretto

  61 shared

• Carly Hyde

  UCLA Health

  59 shared

• Susan Faja

  Harvard University

  58 shared

Education

• MD

  Harvard Medical School

  2002

• BA

  Yale University

  1997

Similar researchers at University of California, Los Angeles

• Kara Calkinsh-22
• Deborah Lehmanh-16
• Xiao B. Wangh-3