Praniti Kumbhar

Built AI Career Copilot, a full-stack Flask web app that analyzes resumes against career goals using OpenAI’s GPT API.
Designed relational database schema with SQLAlchemy ORM on TiDB for user auth and analysis history.
Implemented PDF/DOCX resume parsing using PyPDF2 and python-docx.
Built user authentication and session-based access control for protected routes.
Generated AI-driven skill gap analysis, learning roadmaps, and interview questions from resume data, managed secure API key handling using environment variable python dotenv.

Built a Text-to-SQL in Python that converts natural language queries into SQL using Google Gemini.
Designed a 3-agent architecture: schema pruning agent that selects only relevant tables, RAG retrieval agent that fetches similar Q→SQL examples via ChromaDB, and SQL generation agent for reducing prompt size and improving query accuracy.
Implemented RAG-based few-shot prompting using ChromaDB for vector storage and cosine similarity search to retrieve the most relevant example queries at runtime.

Programmed logic to interface with analog + digital I/O, translating raw sensor input into precise stepper motor commands for 3-axis control.
Wrote motor control algorithms to coordinate 3 stepper motors simultaneously via A4988 driver ICs, managing timing, direction, and step sequencing.
Implemented servo control logic for automated gripper actuation, synchronized with positional motor movements.
Debugged and tested embedded code iteratively on hardware, resolving timing issues and signal noise to achieve stable, repeatable motion control.

Developed an automated Ball Mill control system using Arduino Uno.
Implemented stepper motor control with clockwise and anticlockwise rotation.
Designed a real time LCD dashboard to display system status, runtime, RPM, cycle count, and motor direction.
Optimized control logic using modular programming and state-based execution.

Covered Python fundamentals through advanced concepts including OOP and data structures.

Covered statistical concepts including probability, distributions.

Worked with Python libraries Pandas, NumPy for data analysis and visualization.