Experience

Project Intern - Defense Research and Development Organization, Delhi (Aug 2025 - Present)

As part of this paid internship at DRDO, I am working on artificial intelligence and machine learning integrated full-stack web application to support automated candidate evaluation and interview management.
Building the backend services using python and MYSQL to securely process candidate data and store performance based scoring. Applying speech-to-text (STT) and text-to-speech (TTS) techniques for voice-based interaction during interview.
Utilizing the Natural Language processing (NLP) methods such as semantic similarity, sentiment analysis, intent recognition to evaluate the candidates responses.
Techstack: Python, machine learning, NLP, teamwork, and leadership.

Machine Learning Trainee - Amazon ML Summer School,Remote (July 2025 - Aug 2025)

Implemented supervised, unsupervised, and complex machine learning algorithms using a suite of Python libraries such as scikit-learn, NumPy and pandas.
Developed machine learning models for diverse projects using advanced algorithms and tools, achieving accuracy rates exceeding 95%.
Gained hands-on experience with cloud-based ML tools and model deployment techniques.
Techstack: Python, machine learning, NLP, Aritificial intelligence, GenAI.

FullStack developer Intern - Vbest Education Pvt. Ltd, Hyderabad (Dec 2024 - Mar 2025)

Developed scalable and responsive web applications using HTML, CSS, JavaScript, Node.js, React.js, and MySQL, enhancing UI responsiveness by 30%.
Designed and maintained robust data models, and optimized SQL queries for high-performance backend operations.
Built and tested RESTful API endpoints using Express.js and Postman, ensuring seamless client-server communication in production environments.
Techstack: Python, Fullstack developemnt, teamwork, React.js , Node.js , HTML, CSS, JS, MYSQL,PostgreSQL.

Machine Learning Intern - National Institute of Technology, Warangal (May 2024 - July 2024)

Developed and optimized a CNN model in TensorFlow for real-time meat freshness classification, achieving 98% accuracy and reducing model size by 62% via TensorFlow Lite for edge deployment.
Improved prediction speed by 25%, making the model suitable for low-latency, resource-constrained environments.
Applied deep learning, data preprocessing, and deployment techniques to enhance model performance and scalability.
Techstack: Python, machine learning, deep learning, Aritificial intelligence, GenAI.

Education

SR University - (2022-2026)

Bachelor of Technology in Computer Science (Artificial Intelligence and Machine Learning)
CGPA: 9.4/10
Coursework
- Data Structures and Algorithms
- Operating System
- Database Management Systems
- Computer Networks
- Artificial Intelligence & Machine Learning

Projects

Blood Aid

Developed a responsive web application enabling blood donors to donate, view history, and request blood. Admins efficiently process requests. Designed a consistent and intuitive frontend UI using HTML, CSS, JavaScript, AJAX, and jQuery for seamless user engagement across platforms. Integrated backend APIs using Flask and Node.js with MySQL to streamline workflows. Enhanced system response by 20% through database query optimization.

Technology Stack

Programming Languages: Flask, Python, Node.js, jQuery, AJAX
IDE: Postman, VS Code
Database: MySQL

Crop Disease Prediction

Developed "Crop Disease Prediction" with 95% accuracy using CNN to classify plant leaf conditions into three categories: healthy, rust, and powdery mildew. Designed a dynamic UI with Streamlit, reducing data visualization response time by 25%.

Technology Stack

Tools: Machine Learning Algorithms, Power BI, Streamlit
Programming Languages: Python
IDE: Google Colaboratory

EduGrader

EduGrader is a web-based automated grading application utilizing Python Flask and MySQL. Leveraging the Gemini API for AI-powered grading, it provides instant feedback for students and enhances exam preparation. Handles up to 500 concurrent users with an average response time of 1 second per query.

Technology Stack

Tools: Machine Learning Algorithms, Gemini API, Bootstrap
Programming Languages: Python, Flask
Database: MySQL

Customer Segmentation

Created a customer purchasing dataset and applied K-Means clustering to segment behavior patterns, achieving a 30% improvement in clustering accuracy. Designed a dynamic UI with Streamlit, enhancing real-time insights and user experience.

Technology Stack

Tools: Machine Learning Algorithms, K-Means Clustering, Power BI
Programming Languages: Python, Streamlit
IDE: Google Colab

Loksabha Election Data Analysis

Designed an interactive Power BI dashboard to analyze 2014 and 2019 Loksabha election data. Leveraged Power BI’s Power Query to create intuitive visualizations, improving data storytelling by 20%.

Technology Stack

Tools: Power BI
Programming Languages: Python, Pandas
IDE: Google Colab

Hello I'm

Poojitha Devireddy

And I'm good at FrontEnd Development

Experience

Project Intern - Defense Research and Development Organization, Delhi (Aug 2025 - Present)

Machine Learning Trainee - Amazon ML Summer School,Remote (July 2025 - Aug 2025)

FullStack developer Intern - Vbest Education Pvt. Ltd, Hyderabad (Dec 2024 - Mar 2025)

Machine Learning Intern - National Institute of Technology, Warangal (May 2024 - July 2024)

Education

SR University - (2022-2026)

Coursework

Skills

Programming Languages

Frameworks

Databases & Tools

Domain Knowledge

Projects

Blood Aid

Technology Stack

Crop Disease Prediction

Technology Stack

EduGrader

Technology Stack

Customer Segmentation

Technology Stack

Loksabha Election Data Analysis

Technology Stack

Connect