Resume

Education

Dr. D. Y. Patil Institute Of Technology, Pimpri, Pune-18, Nov 2022 - June 2026
B.E in Computer Engineering. CGPA: 7.86

Core Computer Science: Programming Languages (C++, Python, Java), Object Oriented Programming, Data Structures & Algorithms, Operating Systems
Database & Systems: Database Management System, Computer Networks & Security, Cloud Computing
Artificial Intelligence & Data: Artificial Intelligence, Machine Learning, Data Science & Analytics
Web & Software Technologies: Web Technology
Achievements: Winner – First Year Project Based Learning (PBL) Presentation

Shri Nath Collage, Paithan, Chh.Sambhajinagar, March 2022
Higher Secondary (12^th) – Science (PCMB)
Percentage: 80.50%

Shri Nath High School, Paithan, Chh.Sambhajinagar, March 2020
Secondary School (10^th)
Percentage: 84.60%

Data Analyst Intern, Dec 2024 – Jan 2025
Codtech IT Solutions, Remote working

Worked on a Customer Churn Analysis project to identify key factors affecting customer retention.
Performed data cleaning, preprocessing, and exploratory data analysis (EDA) using Pandas and NumPy.
Implemented machine learning models to predict customer churn and generate actionable business insights.
Developed a Stock Price Analysis project to study market trends and build predictive models for forecasting stock prices.
Applied ETL techniques and data visualization methods to analyze large datasets and present meaningful insights.
Gained hands-on experience in data-driven decision making, reporting, and analytical problem-solving.

Data Analyst Trainee, Aug 2024 – Oct 2024
Godrej Infotech Ltd., Pune

Successfully completed the Data Analytics Program conducted by Godrej Infotech under the CSR initiative.
Worked extensively on Data Visualization using Power BI to create insightful dashboards and reports.
Gained hands-on experience in ETL (Extract, Transform, Load) processes for data preparation and analysis.
Performed data cleaning, transformation, and analysis to extract meaningful insights from structured datasets.
Completed multiple practical projects focused on data analysis, visualization, and reporting.

Medical Equipment Failure Prediction System
Team Size: 8 Live : Click

Led an 8-member team in the Hackathon to develop a predictive maintenance solution for medical equipment.
Built a Gradient Boosting Machine Learning model achieving 91% prediction accuracy for equipment failure detection.
Performed data preprocessing, feature engineering, and exploratory data analysis on operational datasets.
Designed a risk scoring and maintenance recommendation system to reduce equipment downtime and improve patient safety.
Applied AI-driven insights to support proactive maintenance and operational decision-making.

Food Health Evaluation System
Team Size: 3

Developed an AI-driven food quality assessment system using OCR (Tesseract) to extract ingredient information from food labels.
Implemented Convolutional Neural Networks (CNN) to predict food health scores and classify items as Good, Moderate, or Bad.
Integrated the Edamam API to enrich nutritional data and improve ingredient-level analysis.
Designed an end-to-end ETL pipeline for data extraction, preprocessing, and health evaluation.
Built an automated system to help users make informed dietary decisions through transparent nutrition insights.

AI Image Generator (MERN Stack), June 2025 – July 2025
GitHub: Click

Developed a full-stack AI-powered image generation platform using MERN stack integrated with Stable Diffusion API.
Built RESTful APIs using Node.js and Express.js for image generation, storage, and community sharing.
Implemented Cloudinary for image hosting and MongoDB (Mongoose) for managing user posts and prompts.
Designed a responsive UI using React, styled-components, and MUI with support for light/dark themes.
Enabled features like image search, gallery browsing, and prompt-based filtering for enhanced user experience.

MERN E-Learning Platform, May 2025 – June 2025
Full Stack Web Application (Team-2)
GitHub: Click

Developed a full-stack E-Learning platform using MongoDB, Express.js, React.js, and Node.js.
Implemented JWT-based authentication with role-based access for students, instructors, and admins.
Built RESTful APIs for course creation, enrollment, quizzes, assignments, and progress tracking.
Integrated Cloudinary and Multer for secure video and resource uploads.
Designed a responsive UI using React, Redux, and Bootstrap/Tailwind CSS with secure password handling via bcrypt.

Stock Price Analysis & Prediction, Dec 2024 – Jan 2025
Data Analytics Project
GitHub: Click

Analyzed historical stock data to identify trends and market patterns.
Performed data cleaning, preprocessing, and feature engineering using Pandas and NumPy.
Built predictive models using Linear Regression, Random Forest, and Gradient Boosting.
Evaluated models using MSE and achieved up to 0.85 R² score.
Visualized results using charts and proposed improvements for real-time forecasting.

Customer Churn Analysis, Dec 2024 – Jan 2025
Data Analytics Project
GitHub: Click

Analyzed customer data to identify key factors influencing churn, focusing on contract type, payment method, and customer tenure.
Identified that 42% of month-to-month customers churned compared to only 3–11% of long-term contract users.
Discovered that customers using electronic check payments had a 45% churn rate, significantly higher than other payment methods.
Performed data cleaning, preprocessing, and exploratory data analysis using Pandas and NumPy.
Visualized churn trends using charts and graphs and provided data-driven recommendations to improve customer retention.

Programming Languages: Python, C++, Java
Web & Full Stack Development: HTML, CSS, React.js, Node.js, Express.js, REST APIs
Data Science & Machine Learning: Pandas, NumPy, Machine Learning, CNN, Data Analysis, ETL
Databases: MongoDB, MySQL
Cloud & AWS: AWS Cloud Practitioner Essentials, EC2, S3, IAM, VPC, Cloud Fundamentals
AI & Emerging Technologies: OCR (Tesseract), Stable Diffusion, Generative AI
Tools & Platforms: Git, GitHub, Power BI, Cloudinary, Jupyter Notebook
Other Skills: SQL, Object-Oriented Programming (OOPs), Operating Systems, Cloud Basics

Platform Link: LeetCode, Codechef.

Management Coordinator – Sanskriti Cultural Club

Actively managed and coordinated cultural events, handled team operations, and supported planning and execution of college-level programs.
Member – National Service Scheme (NSS)

Participated in social service activities, awareness campaigns, and community development initiatives organized under NSS.

Research Papers

S. Patil, R. Mandal, Sanket Kanase, S. Haridas, and V. Gavali, "Smart Nutrition Analysis: AI-Based Food Quality Assessment", Proceedings of the 9th International Conference on Computing, Communication, Control and Automation (ICCUBEA), Pune, India, 2025, pp. 1–5. (View Paper)