Neha Reddy

About

Computer Science Engineering student with skills in Python, SQL, and AI/ML, and a strong foundation in data analysis, DBMS, and algorithms. Experienced in building data-driven solutions involving NLP, machine learning, and document analysis.

Education

• Bachelor of Engineering in Computer Science Engineering
  Keshav Memorial Engineering College
  Computer Science Engineering · Jun 2023 – Jun 2027

Skills

• SQL <3 months
• Artificial intelligence <3 months
• Data Analysis <3 months
• FastAPI <3 months
• Python <3 months
• Machine Learning <3 months
• Prompt Engineering <3 months
• Java <3 months
• JavaScript <3 months
• Operating Systems <3 months
• API Integration Understanding <3 months
• Statistical Analysis <3 months
• Natural Language Processing <3 months
• RAG <3 months
• LLMs <3 months
• Transformers <3 months
• Data Structures and Algorithms <3 months
• Oop <3 months
• Advanced DBMS <3 months
• ReactJS (preferred) <3 months

Tools / apps / platforms

• Docker <3 months
• Git <3 months
• GitHub Copilot <3 months
• MongoDB <3 months
• MySQL <3 months
• VS Code <3 months

Projects

• GrabPic – Event Image Sharing Platform
  Spring Boot, ReactJS, Azure Blob Storage

  Developed an event-based image sharing platform handling 1.6k+ real-time image upload and retrieval requests. Built scalable backend services using Spring Boot and integrated ReactJS for responsive user interaction. Designed LRU + TTL caching mechanisms to optimize backend response time and reduce redundant processing. Secured image access using Azure Blob SAS URLs with temporary expiry and signed token validation.

• FinanceGPT – AI Financial Document Assistant
  React Native, FastAPI, Generative AI, NLP

  Developed a financial document assistant for summarization, classification, Q&A, and sensitive data masking. Built frontend interfaces using React Native (Expo) and backend APIs using FastAPI for workflow management. Integrated T5, Gemini AI, RoBERTa, and LLaMA models for contextual document understanding and responses. Implemented secure and modular processing pipelines for efficient financial document analysis.

• Automatic Disfluency Detection from Audio
  Machine Learning, Speech Processing, NLP

  Developed a speech-processing model to detect pauses, repetitions, revisions, and restarts from audio signals. Implemented acoustic and multimodal fusion techniques to improve disfluency detection accuracy. Built preprocessing pipelines for speech feature extraction and timestamp-based prediction generation. Trained and evaluated the model using the Switchboard dataset for speech analysis tasks.

🏆 Achievements & awards

• Winner – SmartDhee Vibeathon

  Winner at Keshav Memorial Engineering College.

• Runner-up – Tech Expo

  Runner-up at Keshav Memorial Engineering College.

• Solved 200+ Data Structures and Algorithms problems across coding platforms