Saideep Yamsani

Aspiring Software Developer with hands-on experience in full-stack development using Node.js and React.js, and a solid background in backend programming with C++ and Java. I served as a grader and mentor for Data Structures and Algorithms during my master's program, strengthening core problem-solving skills and the ability to communicate complex concepts effectively. Eager to contribute to impactful software projects and grow within a collaborative, innovation-driven development team.

Drill and Practice – AI-Powered Python Learning Platform

• Developed a dynamic web-based platform for practicing Python programming problems, targeting learners at beginner to intermediate levels.
• Integrated a live Python code editor and an AI assistant (OpenAI API) to provide real-time code hints, debugging support, and contextual help.
• Implemented features such as user progress tracking, automated hint generation, and problem-solving analytics to enhance learning outcomes.
• Utilized MySQL for backend data storage and PHP for server-side logic, ensuring responsive and interactive user experience.

Tools & Technologies: Python, PHP, MySQL, HTML, CSS, OpenAI API

Cyber Crime Estimation and Identification using Machine Learning: 

• Developed a machine learning model to forecast criminal activities and analyze their geographical and categorical origins using real-world datasets sourced from official government websites.
• Implemented Random Forest and Decision Tree algorithms to classify and predict crime types based on historical data features.
• Conducted data preprocessing, feature engineering, and model evaluation to improve accuracy and interpretability.
• Enabled data-driven insights for potential law enforcement applications through visualizations and predictive modeling.

Tools & Technologies: Python, Random Forest, Decision Tree, Pandas, Scikit-learn

Ore Estimation via Image Processing

• Built an AI-powered tool to analyze and estimate mineral ore size using image recognition and classification techniques.
• Employed OpenCV for preprocessing and feature extraction from ore sample images, enabling accurate shape and size analysis.
• Used TensorFlow to develop and train a model that classifies ore types and estimates quantity based on photographic input.
• Designed for use in large-scale mining operations and quarries to facilitate quick, non-invasive ore evaluation and decision-making.

Tools & Technologies: OpenCV, TensorFlow, Python

Inventory Management System

• Developed a dynamic inventory management application with full CRUD operations, real-time database connectivity, and an intuitive frontend built with React.js.
• Enabled inter-store transfer tracking, allowing seamless monitoring of items moved between store locations.
• Integrated low-stock alerts to notify users when inventory levels fall below predefined thresholds, ensuring proactive restocking.
• Included custom reporting tools to visualize stock trends, usage statistics, and inventory history.
• Deployed services on Google Cloud Platform (GCP) to ensure high availability and scalability.
• Awarded "Most Practical Project" for its functionality, usability, and real-world impact.

Tools & Technologies: PHP, SQL, React.js, Google Cloud Platform (GCP)

• Hackathon Winner - University Innovation Challenge
• Solved 200+ problems on HackerRank, CodeChef using Python, Java, and C

Salesforce Developer Certification. - Issued by Salesforce.

Python Developer Certification - Issued by Hackerrank.

Data Structures and Algorithms Certification - Issued by Hackerrank

AWS Certified Developer - Associate (In Progress)