Shubham Gajjar

About

I’m a graduate student in Artificial Intelligence at Northeastern University working on multimodal AI systems that combine vision and language models for biomedical applications.

My current research explores Vision Language Models and agentic AI systems designed to extract insights from complex medical data. I’m particularly interested in applying large language models and multimodal architectures to real world healthcare challenges.

Previously, I worked on deep learning models for medical imaging, including skin cancer classification and brain tumor segmentation. My work includes a Hybrid ResNet–ViT architecture for dermatology classification and attention-based segmentation models for MRI analysis.

Employment

• Northeastern University

Education

• Northeastern University Master's of Science
  2025 - 2027

Projects & Funding

Projects & funding information is unavailable.

Publications (2)

• A Hybrid ResNet-ViT Architecture for Skin Cancer Classification
  2025 DOI: 10.1109/AIC66080.2025.11212073
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• Vgg16-Mca Unet: A Hybrid Deep Learning Approach for Enhanced Brain Tumor Segmentation in Flair MRI
  Ssrn 2024 DOI: 10.2139/ssrn.5012843
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