Medical AI
Robust segmentation and classification for MRI, CT, ultrasound, and clinical text.
View research →PhD Candidate · AI Researcher · Educator
Building intelligent systems that matter.
I develop rigorous, interpretable AI for medical imaging, healthcare, and cybersecurity—and bring that same curiosity and clarity into the classroom.
Computer VisionMedical AICybersecurity
Research profile13 publications
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Open toFaculty opportunities
Research with reach
At the intersection of rigor, relevance, and real-world impact.
My work applies machine learning and deep learning to the places where reliable decisions matter most—from segmenting brain tumors in multimodal MRI to detecting evolving threats in network traffic.
I am especially interested in efficient, interpretable models and in helping students connect strong technical foundations to consequential problems.
What I bring
Three threads. One purpose.
Research and teaching grounded in technical depth, cross-disciplinary collaboration, and practical outcomes.
Adaptive Systems
Continual learning and uncertainty-aware methods built for changing real-world environments.
See publications →Student Growth
Patient, practical mentoring that develops confidence, independence, and critical thinking.
Teaching approach →
Research in actionFrom model to meaningful outcome.
Selected contribution
Advancing brain tumor segmentation with diffusion models.
DMCIE improves MRI brain tumor segmentation by learning from both multimodal inputs and error signals—an example of my broader focus on models that are accurate, efficient, and clinically relevant.
Read the publication ↗Let’s build what’s next
Looking for a faculty colleague who can connect AI, impact, and students?
I welcome conversations about faculty opportunities, research collaborations, and student mentorship.
Start a conversation ↗