About Me
name: 'Harmanpreet Singh',
education: 'B.Tech CSE',
role: 'AI Engineer & Full Stack Dev',
core_skills: ['MERN', 'Next.js',
'Python', 'AI/ML'],
interests: ['Computer Vision',
'Machine Learning'],
passion: 'Building real-world solutions'
};
CS Graduate Turning Ideas into Intelligent Software
I'm a Computer Science Engineering graduate from Punjab with a relentless passion for building technology that solves real problems. My journey began with a fascination for how machines can learn and perceive the world — leading me deep into Artificial Intelligence, Computer Vision, and full-stack engineering.
My expertise spans from core CS fundamentals — Data Structures, Algorithms, Operating Systems — to building production platforms with the MERN stack and Next.js. After specialized AI/ML training at NIELIT Ropar, I've been bridging the gap between software development and predictive analytics, creating systems that don't just function, but think.
Whether it's training a VGG16 model to detect brain tumors from MRI scans, building a unified road safety platform with 6 CV models, or publishing open-source Python packages — I'm driven by the belief that great engineering starts with understanding the problem deeply.
My Journey
From learning the fundamentals to building production AI systems.
B.Tech Computer Science Engineering
Completed my bachelor's degree in Computer Science Engineering, mastering core subjects including Data Structures, Algorithms, DBMS, Operating Systems, Computer Networks, and Software Engineering. Built a strong foundation for both systems programming and AI.
NIELIT Ropar — AI/ML Training
Completed specialized training in Artificial Intelligence and Machine Learning at NIELIT Ropar. Gained hands-on experience with supervised/unsupervised learning, neural networks, computer vision, and model deployment.
Major AI & Full-Stack Projects
Built 10+ production-grade projects spanning AI/ML and full-stack development. Highlights include NeuroScan AI (brain tumor detection with 95%+ accuracy), RoadSense AI (6 computer vision models), Stash Finance (Next.js), Medicura (MERN), and Pristinizer (published Python library).
Continuous Learning
Currently deepening expertise in advanced Computer Vision architectures, transformer models, and scalable cloud deployment. Exploring GenAI, LLM fine-tuning, and edge AI for real-time applications.
Career Goals
Seeking to join innovative AI startups or top tech companies where I can apply my skills in AI engineering and full-stack development to build products that make a meaningful impact. Passionate about roles at the intersection of AI research and production engineering.
Experience & Involvement
Academic projects, collaboration, and contributions that shaped my skills.
Academic Projects
Built 10+ projects across AI, ML, and full-stack domains as part of coursework and self-directed learning. Each project targeted real-world problems — from healthcare diagnostics to financial management.
Presentations
Presented AI/ML projects including NeuroScan AI and RoadSense AI at academic showcases, explaining complex computer vision architectures to technical and non-technical audiences.
Research
Explored transfer learning techniques (VGG16, ResNet), ensemble methods (XGBoost, Random Forest), and computer vision pipelines. Applied research findings directly in deployed applications.
Team Collaboration
Collaborated on multi-developer projects using Git workflows, code reviews, and agile practices. Campus-Connect and Medicura were built with team coordination and clear role delegation.
Open Source Contributions
Published the Pristinizer Python package on PyPI. Actively maintaining repositories on GitHub and exploring opportunities to contribute to larger open-source ML and developer tool projects.
Training & Workshops
Completed specialized AI/ML training at NIELIT Ropar. Attended workshops on cloud deployment, DevOps fundamentals, and modern frontend development frameworks.
Certifications & Credentials
Professional certifications and completed training programs.