🎓 Master’s in Computer Science, George Mason University (GPA: 3.77)
💻 Passionate about software engineering, backend systems, and scalable full-stack development
📫 prangana@gmu.edu | LinkedIn | GitHub

I am a software engineer with a strong foundation in computer science, data structures, and object-oriented programming.
My interests lie in building high-quality, maintainable, and efficient software solutions.
With experience across backend microservices, UI development, and cloud-based deployment,
I focus on delivering reliable, user-centric systems that solve real-world problems.

Jul 2025 – Present

• Built and deployed full-stack web applications using Next.js and Tailwind CSS, boosting portal engagement by 30% and serving 10K+ active users.
• Developed backend data integration services using Python (Pandas, NumPy) and SQL for cleaning and validating student datasets.
• Created dynamic visualizations and analytics dashboards in Power BI and Matplotlib, improving reporting visibility by 40% across five student categories for the Registrar & Financial Aid teams.

Aug 2023 – May 2025

• Engineered a full front-end redesign of GMU’s Patriot Web portal using React, JavaScript, MUI, CSS, improving navigation & accessibility for 30K+ students.
• Refactored multiple UI components, applied modern accessibility standards (ARIA/WCAG), and optimized rendering paths, resulting in 25% faster page loads.
• Supported the production build release on Railway, coordinating with university teams for accessibility and performance compliance.

Jan 2025 – May 2025

• Engineered a rooted Android automation framework to simulate voice input in Google Gemini using OS-level commands (am, input, dumpsys), Text-to-Speech, and Accessibility Services.
• Implemented a high-accuracy real-time logcat parser for audio-trigger detection with 95% mic synchronization accuracy validated over 100+ trials.
• Removed dependency on ADB by designing a direct, on-device mic-activation pipeline, reducing latency and enabling fully hands-free voice interaction.

Aug 2022 – Aug 2023

• Developed and shipped backend Spring Boot microservices supporting 100K+ daily banking transactions, collaborating across Agile teams in 3 time zones.
• Integrated Apache Kafka for real-time credit decisions, reducing reconciliation time by 80% and improving system throughput for customer evaluations.
• Refactored legacy Java/Spring Boot services to improve API efficiency by 30% and enhance modularity, enabling faster feature iteration.
• Automated CI/CD pipelines using Jenkins, reducing manual deployment effort by 40%, increasing release stability, and accelerating production rollout.

Aug 2021 – Aug 2022

• Optimized PL/SQL batch-processing jobs for internal dashboards, improving execution time by 25% for 50K+ users.
• Built internal enterprise modules using Spring MVC, JSP, JavaScript, Oracle DB, reducing helpdesk ticket resolution time by 35%.
• Executed functional testing across 10+ Agile sprints, identifying 20+ critical bugs and improving final production quality.
• Managed UAT and production deployments using Jenkins and Bitbucket, improving accuracy and reducing release rollbacks.

George Mason University, Fairfax VA — M.S. in Computer Science (2025)
Jawaharlal Nehru Technological University, Hyderabad IN — B.Tech in Information Technology (2021)

• Architected a fully containerized survey management platform using Spring Boot for backend microservices and MySQL (Amazon RDS) for persistent data storage.
• Containerized all services using Docker and orchestrated deployments with Kubernetes (Rancher on AWS EC2) for high availability and scalability.
• Implemented end-to-end CI/CD pipelines using GitHub Actions + Jenkins, automating build, test, and deployment workflows.

(Also part of the Research Assistant work)

• Engineered a rooted Android automation system to simulate real-time mic input in Google Gemini, using OS commands (am, input, dumpsys) and TTS.
• Implemented a logcat-driven audio trigger pipeline with 95% accuracy across 100+ trials for mic activation detection.
• Eliminated ADB dependency by creating an on-device event and audio-injection workflow, reducing latency and enabling hands-free interaction.

• Built a FastAPI backend that parses legal documents using regex and Python string-processing techniques to detect placeholders and incomplete clauses; ; integrated an OpenAI API token for secure LLM calls.
• Designed an LLM-powered filling engine where users provide a short value summary, and the system auto-generates context-accurate legal text to populate all detected placeholders.
• Deployed a simple, intuitive Streamlit UI for uploading documents, visualizing extracted fields, and previewing the LLM-completed draft.

• Developed an end-to-end machine learning pipeline using HR analytics data with preprocessing, Z-score normalization, and PCA-based dimensionality reduction.
• Applied SMOTE to balance minority classes and compared multiple models (Random Forest, SVM, KNN, Logistic Regression).
• Achieved 91% accuracy using Logistic Regression and performed SHAP explainability analysis to interpret features and evaluate fairness across employee groups.

• Built a real-time gesture-controlled cursor system combining a custom CNN with MediaPipe hand landmark detection.
• Trained the gesture classification model on custom datasets, achieving 84% accuracy in recognizing 5 distinct gestures.
• Integrated computer vision and system control to translate gestures into OS-level mouse actions (click, drag, swipe, movement).
• Optimized frame processing and detection pipeline to maintain smooth on-screen cursor movement.

• Analyzed ~641K user records to define key KPIs, identifying a low 2.7% completion rate and major drop-offs in the user funnel.
• Built an interactive Power BI dashboard with DAX measures (Completion Rate, Avg Grade) to monitor user conversion and engagement.
• Derived insights showing high engagement correlates with completion (~84% avg grade), recommending improvements in retention and onboarding.

Languages & Backend:
Python, Java, JavaScript, SQL, PL/SQL, C, C++, C#, Spring Boot, REST APIs, Hibernate, .NET

Frontend & UI:
React, JSP, MUI, HTML, CSS, Figma, Next.js, Tailwind CSS, Angular, Node.js

DevOps & Tools:
AWS (EC2, RDS), Jenkins, Docker, Kubernetes, GitHub Actions, Bitbucket, Jira, Azure, Rancher

AI/ML & Data:
OpenAI API, scikit-learn, Pandas, NumPy, Matplotlib, Power BI, LangChain

Databases & Other:
Oracle SQL, MySQL, PostgreSQL, JUnit, TDD, AI-assisted coding (GitHub Copilot, Claude, ChatGPT)

"Turning ideas into scalable, high-quality software solutions."
LinkedIn • Email • GitHub