Shiva Singh Tomar

About

Full Stack Developer skilled in Next.js, React.js, TypeScript, Node.js, Express.js, and MongoDB, with experience building production-ready web applications. Strong in REST API integration, authentication, responsive development, and modern software engineering practices, with 300+ DSA problems solved.

Experience

• Full Stack Developer Intern
  Creation PropTech Pvt. Ltd.
  Aug 2026 – Present
• Frontend Developer Intern
  Creation PropTech Pvt. Ltd.
  Apr 2026 – Jul 2026

Education

• B.Tech in Computer Science & Engineering
  Madhav Institute of Technology & Science
  Computer Science & Engineering · Sep 2023 – Jul 2027

Skills

• C
• Computer Networks
• Express.js
• Python
• CSS3
• JavaScript
• Node.js
• Tailwind CSS
• React
• Responsive Design
• TypeScript
• Operating Systems
• Next.js
• Rendering
• API Integration Understanding
• HTML5
• Data Structures and Algorithms
• MVC Architecture
• RBAC
• JWT Authentication
• Redux Toolkit
• Mongoose
• APIs and integrations
• Figma
• Advanced DBMS

Projects

• Finance Dashboard System (FDS)
  Next.js, Node.js, TypeScript, MongoDB Atlas, JWT, Zod

  Developed a scalable financial dashboard using Next.js, TypeScript, and MongoDB, implementing Role-Based Access Control (RBAC) for secure data management. Built RESTful APIs using Next.js API Routes with Zod validation, integrated MongoDB Atlas using Mongoose, and implemented CRUD operations for secure financial data management. Implemented JWT-based Authentication, Authorization, Protected Routes, and Role-Based Access Control (RBAC), ensuring secure access to application resources and financial data.

• PhytoCure
  React.js, Tailwind CSS, Express.js, Flask, EfficientNet-B4

  Engineered a plant disease detection system using deep learning–based image classification to identify plant diseases and recommend treatments. Developed a full-stack application using React.js, Tailwind CSS, Express.js, and Flask, integrating ML predictions via REST APIs. Implemented EfficientNet-B4 (transfer learning) trained on PlantVillage dataset, achieving approximately 98% accuracy in disease classification and enabling early crop disease diagnosis.

🏆 Achievements & awards

• Solved 300+ Data Structures and Algorithms problems

  Solved 300+ Data Structures and Algorithms problems on LeetCode and GeeksforGeeks, achieving 1612 rating.

• Top 30 teams in Smart India Hackathon (SIH)

  Ranked among Top 30 teams in Smart India Hackathon (SIH), demonstrating strong problem-solving and collaboration skills.

• 5th place in Code Coalescence Hackathon

  Secured 5th place in Code Coalescence Hackathon, showcasing competitive programming and analytical skills.