Stanford University
Showing 191-200 of 13,134 Results
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Ali Akbarisehat
Postdoctoral Scholar, Radiology
Current Research and Scholarly InterestsBiosensing, electrochemical sensing
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Franz Ake
Postdoctoral Scholar, Pathology
BioDr. Ake is a computational biologist specializing in single-cell transcriptomics, alternative polyadenylation, and isoform regulation. His research focuses on developing computational methods and bioinformatic pipelines to characterize post-transcriptional regulation and differential isoform usage at single-cell resolution. During his PhD under the mentorship of Dr. Mireya Plass at the University of Barcelona and the IDIBELL Research Institute in Barcelona, Spain, he developed approaches for isoform quantification and the analysis of differential isoform usage in single-cell datasets.
Currently, his research at Stanford University focuses on multi-omics data integration, with a particular emphasis on spatial transcriptomics and cancer genomics to study tumor biology, tissue heterogeneity, and disease-associated molecular programs from high-dimensional sequencing data. -
Teddy J. Akiki, MD
Clinical Assistant Professor, Psychiatry and Behavioral Sciences
Current Research and Scholarly InterestsDr. Akiki's research focuses on advancing precision psychiatry through computational neuroscience approaches. His work centers on developing transformer-based foundation models for functional neuroimaging that can predict treatment responses and symptom trajectories in psychiatric disorders. Using multimodal connectomics (combining structural, functional, and diffusion MRI), he maps neural circuits underlying stress-related conditions, with particular emphasis on identifying dysconnectivity patterns in PTSD and depression. Dr. Akiki develops novel analytical methods for neuroimaging data, including network-restricted metrics and community detection frameworks optimized for functional time series. His translational work includes neuroimaging-augmented clinical trials of novel therapeutics for treatment-resistant psychiatric disorders, with the goal of implementing data-driven, personalized interventions based on individual neurobiological profiles.
