Srushti Warad — Digiprofile

About

Full-stack developer with hands-on internship experience building responsive web applications using React.js, Node.js, MongoDB, and REST APIs, plus applied machine learning and computer vision experience from a data science internship. Comfortable across the stack, from Figma wireframes through backend authentication and cloud deployment on AWS. Seeking an entry-level software development role to build scalable, real-world applications and continue growing technical depth.

Experience

Full Stack Development Intern

VTU's VRIF

2026-02-01 – 2026-05-01

Developed responsive web applications using HTML, CSS, JavaScript, React.js, Node.js, and MongoDB. Designed user interfaces and wireframes in Figma. Built and integrated frontend and backend modules with REST APIs, implementing authentication and dashboard functionality. Contributed to the AI-Based Disease Outbreak Warning System (AIDOWS). Used Git/GitHub for version control and deployed applications to cloud platforms.

Data Science Intern

Shriram Solutions

2024-04-01 – 2024-06-01

Applied Python, machine learning, and computer vision techniques for problem-solving. Built a Leaf Disease Prediction System to detect plant diseases from leaf images. Performed image preprocessing (segmentation, feature extraction, enhancement) to improve model performance. Used Python, OpenCV, TensorFlow/PyTorch, NumPy, Pandas, and Scikit-learn for data analysis and model development.

Education

Master of Computer Applications (MCA)

Gogte Institute of Technology

2024 – 2026

Bachelor of Computer Applications (BCA)

BLDEA's A.S. Patil College of Commerce

2021 – 2024 · 8.12 CGPA

Projects

AI-Based Disease Outbreak Warning System (AIDOWS)

Full-stack disease surveillance and healthcare analytics platform supporting real-time outbreak detection, vaccine tracking, and clinical decision support. Integrated WHO live data feeds, role-based multi-user authentication, doctor-patient consultation workflows, and country-level geo-spatial analysis to help monitor disease spread.

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Nexus AI Dashboard

Scalable full-stack web application with an interactive analytics dashboard, secure multi-device authentication, social login integration, role-based access control, and a responsive, animated UI.

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Leaf Disease Prediction System

Plant disease detection system trained on leaf image datasets to identify early signs of crop disease and support timely preventive action by farmers. Applied image segmentation and feature extraction, then trained CNN and SVM models for disease classification.

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Campus Complaint Management System

College complaint management platform with role-based authentication for students and administrators, including secure registration and login. Deployed on AWS Free Tier.

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