Computational phenotyping
Identify interpretable subgroups, trajectories, and patterns that average effects can obscure.
Biomedical engineering · data science · brain health
Raha Dastgheyb
Biomedical EngineerTranslational Data Scientist
Computational NeuroscientistScientific Software Builder
Assistant Professor of NeurologyDivision of NeuroimmunologyJohns Hopkins School of Medicine
Designing computational tools and analytical workflows that help researchers find meaning in complex biomedical data.
Research focus
From complex measurements to questions researchers can act on.
I build methods and tools for making high-dimensional clinical, cognitive, biomarker, imaging, and molecular data easier to inspect, interpret, and use in translational research.
Browse research threadsBiomarker systems
Relate molecular signals to cognition, clinical outcomes, and mechanisms of brain health.
Scientific software
Turn analytical approaches into tools and reports that collaborators can understand and extend.
Featured software
Tools for analysis that stays visible, reusable, and collaborative.
Released tools, active development, and capability areas are labeled clearly so visitors can see what is ready to use today.
Published, citable MATLAB app for multi-electrode array analysis.released
MEAnalyzer
A downloadable point-and-click tool for spike-train statistics, burst detection, functional connectivity, periodicity analysis, visualization, and provenance-aware exports.
Open-source biomedical data analysis and reporting infrastructure.released
SciDataReportR
Supports metadata-aware QC, statistical workflows, biomarker analysis, visualization, and reproducible scientific reasoning.
Reveals latent cognitive and biomarker patterns across heterogeneous cohorts.capability area
Computational Phenotyping Pipelines
Moves beyond average effects toward clinically and biologically interpretable hidden structure.
Turns analysis workflows into publication-ready scientific reports.capability area
Scientific Reporting Frameworks
Makes reproducible research outputs traceable, interpretable, shareable, and ready for collaborators.
Selected work
Research questions, methods, and publications in context.
Research threads
Hidden structure
Computational Phenotyping
Unsupervised learning, cognitive profiles, and interpretable models for heterogeneous brain health data.
Molecular signals
Biomarker Systems
Computational pipelines for linking multi-omics, neuroimaging, inflammation, and cognition.
Reusable systems
Scientific Software & Infrastructure
Open-source tools, reporting frameworks, dashboards, and analysis interfaces that make science reproducible.
Selected publications
BRACE-ing for the future: Establishing iPad-based norms for cognitive function in the MACS/WIHS Combined Cohort Study (Preprint)
JMIR mental health
Establishes regression-based iPad cognitive norms for BRACE in the MACS/WIHS Combined Cohort Study.
Identifying and distinguishing cognitive profiles among virally suppressed people with HIV.
Neuropsychology
Identifies six cognitive profiles among virally suppressed people with HIV and the factors that distinguish them.
Machine learning approaches to understand cognitive phenotypes in people with HIV
The Journal of infectious diseases
Frames machine learning as a tool for discovering cognitive biotypes in people with HIV.
People & mentorship
Research grows through shared work, training, and long-term collaboration.
This is a network of trainees, alumni, collaborators, and teaching relationships—not a formal laboratory roster.
Meet the peopleRoles & affiliations
Leading and contributing across interdisciplinary research settings.
Leadership role
Brain Health Program
Co-director, Data Science and Mathematical Modeling Core, with Yanxun XuA translational engine for integrating cognitive data, biomarkers, neuroimaging, and computational methods across HIV, Long COVID, aging, and related brain health questions.
Leadership role
Johns Hopkins Center for the Advancement of HIV Neurotherapeutics (JH-CAHN)
Co-director, Biomarker Core, with Rebecca VeenhuisA collaborative infrastructure role focused on biomarker discovery, validation, and interpretation for HIV-associated neurocognitive and neuroimmune conditions.
Contact
Collaborations, talks, trainees, and software questions are welcome.
For interdisciplinary research partnerships, speaking invitations, or questions about the work, please get in touch.