Final-year Computer Science student specializing in Artificial Intelligence and Medical Imaging
I am deeply committed to advancing healthcare through intelligent systems. My research focuses on developing efficient, accurate AI models for medical image analysisโbridging the gap between cutting-edge deep learning and practical clinical applications.
Current Research
Vision Transformers for 3D Medical Imaging | CT Scan Analysis | Model Optimization for Resource-Constrained Environments
Core Expertise
Machine Learning โข Deep Learning โข Medical Image Processing โข Backend Architecture
Technical Foundation
PyTorch, TensorFlow โข Python, Java โข Spring Boot โข Computer Vision
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AI-Powered DICOM Analysis System
๐น Multi-Model AI Integration (MedSAM, MedSigLIP, LLaVA-Med)
๐น Real-time CT/MRI Analysis with ROI Detection
๐น FastAPI Backend + React Frontend
๐น Google Cloud Integration
๐น Hounsfield Unit-based Tissue Classification
| Area | Focus |
|---|---|
| ๐ฌ Research | Fine-tuning Open-Source Medical AI Models |
| โ๏ธ Cloud | Cloud AI APIs & Large Model Inference |
| ๐ฎ RL | Reinforcement Learning with Java |
| ๐ง Optimization | Model Deployment on Constrained Hardware |
Expertise:
- Transformer Architectures: "ViT, Swin Transformer, 3D Scene Understanding"
- Medical AI: "CT/MRI Analysis, DICOM Processing, Lightweight Models"
- Backend: "Java Springboot + ML/AI Integration"
- Model Optimization: "CPU-based Inference, Model Compression"
- Research: "Vision Transformers, Multimodal AI"
Open_To:
- Collaboration: "AI/ML Projects, Research Papers"
- Mentorship: "AI for Healthcare, ML Deployment"
- Opportunities: "Graduate Studies Scholarships in AI/CS"| Degree | Institution | Specialization | Status |
|---|---|---|---|
| ๐ B.Sc. CSE | University | AI & Machine Learning | Final Year |
Key Coursework: Numerical Analysis, Algorithms, Machine Learning, Deep Learning, Computer Vision, Natural Language Processing
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