About Me
I’m Yash Maini, an undergraduate AI and ML student at GGSIPU who is interested in the convergence of research and production-grade engineering. I work on the entire AI stack, from model creation and medical imaging research to MLOps, cloud infrastructure, and scalable deployment pipelines.
My work has resulted in two IEEE research papers and various applicable systems, such as full-stack ML deployments and healthcare AI tools.
Currently Working On
💼 NetoAI — SDE-1 Intern (AI/ML & LLM)
Position: SDE-1 Intern (AI/ML & LLM)
Jan 2026 - Present · Remote
Working on cutting-edge AI/ML solutions and Large Language Model applications, contributing to production-grade systems and scalable AI infrastructure.
Experience
🏥 MP4-to-DICOM Conversion — AIIMS Delhi
Mentor: Prof. Dr. Deepak Agrawal (Neurosurgery)
Completed
Developed a DICOM automation pipeline for radiological video data, focused on reproducibility, compliance, and integration with clinical workflows. While independently initiated, the project was aligned with ICMR objectives and built in collaboration with the AIIMS Delhi clinical research ecosystem.
Key Focus Areas
- Applied AI in healthcare and diagnostics
- MLOps and full-lifecycle model infrastructure
- AWS-native deployment (SageMaker, Lambda, CDK)
- Model evaluation: calibration, uncertainty quantification
- Medical imaging, DICOM workflows, and reproducible pipelines
Learn More
Explore detailed sections below:
| Section | Description |
|---|---|
| Projects | Applied systems, ML pipelines, dev tools |
| Publications | IEEE research contributions |
| Experience | Research, internships, collaborations |
| Skills | Technical stack & toolkits |
| Blogs | Implementation notes & deep dives |
| Achievements | certifications and recognitions |
| CV | Full PDF resume |
Contact
For collaborations, internships, or project discussions:
📧 mainiyash2@gmail.com
🔗 LinkedIn
💻 GitHub