PhD Candidate · University of South Carolina

Deepa Tilwani

PhD candidate researching computational neuroscience, statistical and Bayesian modeling, generative brain models, and trustworthy AI through interdisciplinary collaborations.

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Columbia, South Carolina Computational neuroscience, statistical analysis, Bayesian methods, and trustworthy AI

Current focus

Current work focuses on model-driven and Bayesian analysis of brain activity, generative neural models, effective connectivity, and citation-grounded evaluation for trustworthy AI and language systems.

Publications

Citations

Awards

Research

Research areas

Core themes across computational neuroscience, statistical analysis, Bayesian methods, AI, healthcare, and language systems.

What I work on

Interpretable methods for science and high-stakes AI

The goal is to build AI systems that are analytically useful, scientifically grounded, and reliable enough for healthcare and other high-stakes settings.

How I work

Study brain activity with generative models, inversion, statistical analysis, Bayesian methods, machine learning, and deep learning.
Turn evaluation gaps in AI and language systems into concrete benchmarks and measurement tools.
Collaborate across research labs, workshops, and mentoring environments.

Publications

Selected publications

Recent papers across computational neuroscience, healthcare AI, neurosymbolic AI, explainability, legal AI, and trustworthy language-system evaluation.

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Experience

Research and professional experience

Recent roles across research labs, industry, and interdisciplinary collaborations.

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Recognition

Awards and recognition

Recent scholarships, travel support, and research honors.

Contact

Interested in collaborating on computational neuroscience, healthcare AI, or trustworthy language systems?

I’m especially excited by work on generative brain models, statistical and Bayesian methods, healthcare AI, neurosymbolic AI, and language technologies with real-world accountability.

Contact me View CV

News

News Appearances

Recent feature stories and external coverage.

Writing

Blogs

Notes, reflections, and research-facing writing will appear here.