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Entry-level AI Engineer with Python, Machine Learning, and Web Development skills.
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Highly motivated Computer Science student specializing in AI/ML with strong foundational skills in data structures, algorithms, and full-stack development. Experienced in building AI models for image enhancement and medical QA, as well as developing web applications with modern frameworks. Actively participates in competitive programming and hackathons, demonstrating a strong problem-solving aptitude and a drive for continuous learning and innovation in technology.
Sharda University
Bachelor of Technology · Computer Science (AI/ML)
August 1, 2022 – June 30, 2026
BuyNest
May 1, 2026 – June 30, 2026
Built a full-stack e-commerce web application with Django REST Framework backend and React + Tailwind CSS frontend, supporting product browsing, cart management, checkout, and order history. Implemented JWT-based authentication with protected routes, automatic token refresh, and secure login/registration flow. Integrated Cloudinary for image storage and Neon PostgreSQL as the production database with full CRUD operations via DRF serializers and API views. Deployed frontend on Vercel and backend on Render; configured CORS, environment variables, and static files for production.
View ProjectEnhancement of Lunar PSR Images
February 1, 2026 – June 30, 2026
Built a CDAN-based model to enhance low-light lunar PSR images from the Moon's south pole. Used Dense Blocks, CBAM attention, and residual learning for brightness and detail restoration. Achieved 20.53 PSNR and 0.7995 SSIM on eval15; validation reached 18.31 PSNR and 0.8152 SSIM. Published a review paper; research paper based on the project is currently under publication process.
View ProjectRAG-Based Medical QA System
December 1, 2025 – June 30, 2026
Retrieval-Augmented Generation (RAG) based medical QA system using semantic retrieval and local open-source LLM. Implemented chunking, MiniLM embeddings, FAISS indexing, and top-K retrieval for grounded responses. Developed both CLI and Streamlit chat interfaces with conversation history and automatic logging for end-to-end deployment.
View ProjectReal-time Violence Detection System
January 1, 2025 – January 31, 2025
Developed a video-based violence detection model using MobileNetV2, achieving 96% accuracy on Kaggle dataset. Integrated OpenCV for real-time CCTV analysis, enabling sub-second detection of violent activities. Reduced training time by 30% through GPU acceleration while maintaining a 0.96 PR score.
View ProjectCultural Fit Analysis
The candidate's diverse project portfolio, ranging from academic research (Lunar PSR Images) to practical applications (Medical QA, Violence Detection) and even full-stack development (BuyNest), indicates a broad interest and adaptability. Their involvement in team-based competitions like Smart India Hackathon and Uhack 3.0 suggests a collaborative mindset and leadership potential, aligning well with a dynamic team environment. The focus on AI/ML projects directly aligns with an AI Engineer role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to learning and applying advanced AI/ML techniques. Participation in hackathons and competitive programming suggests strong problem-solving skills, teamwork, and the ability to perform under pressure. The detailed project descriptions demonstrate good technical communication.