Purvesh Kadam

Intern

Mumbai, IndiaSoftware Engineering and Cybersecurity
1roles
40skills
1education
3credentials

About

Computer Engineering graduate with a foundation in Java, Python, C++, object-oriented programming, and data structures and algorithms. Experienced in building full-stack applications and AI/ML tools, with additional exposure to cybersecurity, cloud security, data privacy, and GRC.

Experience

Intern

SecurWires Technologies and Services

Jan 2026 – Mar 2026 · Remote

Completed a 3-month industry-focused internship covering cybersecurity, cloud security, data privacy, and GRC, including 40+ hours of structured professional training. Studied data privacy principles and their application to technology and business operations, and built a foundational understanding of GRC practices and cloud security considerations.

Education

Rajiv Gandhi Institute of Technology, Mumbai

B.E., Computer Engineering

2026

Skills

JavaPythonC++JavaScriptTypeScriptSQLReact.jsNext.jsNode.jsExpress.jsFastAPIREST APIsSocket.ioTailwind CSSHTML5CSS3PostgreSQLMySQLMongoDBSQLitePandasNumPyLangChainOpenAI APIStreamlitGitGitHubLinuxVS CodePower BICybersecurity fundamentalsCloud SecurityData PrivacyGRCOperating SystemsComputer NetworksObject-Oriented ProgrammingData Structures and AlgorithmsSDLCSoftware Testing

Projects

Personal Book Manager

Academic full-stack web application built with Next.js, TypeScript, MongoDB, JWT, and Tailwind CSS. Implemented JWT-based authentication, protected routes, CRUD book management, search, filtering, ratings, tags, and reading-status tracking.

Real-Time Chat Application

Academic real-time messaging application built with React, Node.js, Express, Socket.io, and SQLite. Implemented instant messaging, live online-user tracking, REST APIs, and SQLite persistence across page refreshes.

AI Analytics Copilot

Academic AI-powered analytics tool built with Python, Pandas, NumPy, LangChain, OpenAI, and Streamlit. Implemented automated CSV/Excel data profiling, KPI generation, visualization, anomaly detection, and natural-language insight generation.

AI-Powered Genomics — Genetic Disorder Prediction

Academic machine learning project using Python, React, and an MLP-based model for multi-class genetic disorder prediction. Applied SMOTE, data preprocessing, feature scaling, batch normalization, GELU activation, and dropout.