I’m passionate about using AI and technology to solve real-world problems. I currently serve as Junior Technical Executive
at PCCOE AiMSA and SDW Sports Cell Coordinator at PCCOE. I completed my internship as a Project Development Intern at
CampusDekho.ai and lead Team SynthoMind, a hackathon team creating innovative, data-driven projects. I believe that engineering
is the power behind possibilities, and as an engineer, I strive to use that power to transform ideas into impactful solutions.
Technical Skills
Python
Data Science
Machine Learning
Deep Learning
Agentic Ai
C++
C
DSA
JavaScript
HTML/CSS
Node.js
MySQL
MongoDB
PostgreSQL
n8n
Key Achievements
Winner of IEEE Innoquest 2025 Hackathon
National-level innovation hackathon organized by Deccan Education Society, Pune, aimed at fostering creativity, technical excellence, and real-world problem-solving among students across diverse domains.
2 x Winner of INNS Nurathon Competition
Neurothon 2025 is an AI-focused hackathon organized by PCCOE’s International Neural Network Society Cell, promoting innovation and creativity in neural network and Natural Language Processing applications.
Finalists at the IEEE TechSangam 2025 Hackathon
National-level hackathon organized by MIT ADT University, Pune, bringing together innovators and technologists to solve real-world challenges through cutting-edge AI, IoT, and data-driven solutions.
Project Development Intern at CampusDekho.ai
Successfully completed my Project Development Internship at CampusDekho.ai, where I built MHT CET data tools and automated college prediction and preference systems using the MERN stack.
My Projects
A collection of my work in machine learning, data science, and full-stack development
Engimate
EngiMate is an AI-powered platform that simplifies the MHT-CET admission process through smart college predictions, a personalized counselling chatbot, transparent analytics, and a dynamic preference list generator. Using AI, fuzzy logic, and multi-year data, it empowers students to make informed, data-driven decisions for their academic future.
HTMLCSSJava ScriptNode.jsPostgreSQLPineconen8nGemini/OpenAi API
All-in-one badminton management platform enabling players to register, view upcoming and completed matches, and track scores. Referees can manage matches with dynamic rules and real-time scorecards, while admins oversee players, generate schedules, allocate matches, and handle complete event management efficiently.
A machine learning model for plant health detection
with 93% accuracy, using ensemble techniques and PCA
to classify diseases through leaf images with
explainable AI.
This is a web-based Slot Booking System that allows users to book time-based slots on specific days. The system features a user-friendly interface for selecting available slots and includes an admin panel for managing bookings, time slots, and user data. It is ideal for services requiring scheduled appointments or reservations.
Predicts MHT CET percentile using student's marks, exam date, and shift. Helps students estimate their score before results. Simple, fast, and easy to use.
A Natural Language Processing project using Logistic Regression, TF-IDF Vectorization, Ordinal Encoding, and Scikit-learn to classify customer complaints into product categories from noisy financial service data.
This paper focuses on detecting whether a plant leaf
is healthy or not using machine learning. It compares six different ML
algorithms like SVM, Random Forest, and XGBoost to find out which one works
best. The team used images of leaves from plants like mango, bell pepper,
potato, and Pongamia Pinnata. Since the image data was large, they used PCA
to reduce its size while keeping important information. After training and
testing all the models, SVM gave the best results with 93.63% accuracy.
This approach can help farmers detect diseases early and take better care
of their crops.
A comprehensive guide featuring hands-on implementations of essential machine learning algorithms from scratch, with detailed code explanations to enhance understanding and mastery of core ML concepts and techniques.
These HTML notes cover the fundamentals of web development, including tags, elements, attributes, and structure, helping learners build and design basic web pages efficiently.
These CSS notes provide a concise overview of Cascading Style Sheets, covering selectors, properties, layouts, and styling techniques essential for designing visually appealing web pages.
These JavaScript notes cover essential concepts, syntax, and examples to help beginners understand and practice JS fundamentals for web development and interactive programming.
These Node.js notes cover core concepts, modules, asynchronous programming, and server creation, providing a concise guide for building scalable, efficient backend applications using JavaScript.
SQL notes cover essential concepts, commands, and queries for database management, ideal for beginners and developers to understand, practice, and master SQL efficiently.
Mongo DB notes cover essential concepts, commands, and queries for database management, ideal for beginners and developers to understand, practice, and master Mongo DB efficiently.
Hands-on data science code implementations covering data preprocessing, visualization, machine learning models, and evaluation techniques for real-world problem-solving using Python and popular libraries.
