• Engineered scalable full-stack e-commerce solutions using Spring Boot, Angular, NgRX State Management, and Hibernate, optimizing UI responsiveness and reducing page load time by 20%, leading to boosted customer retention.

• Refined RESTful APIs for product catalogs, shopping carts, and order processing using Spring Boot and JAX-RS, leveraging AWS ALB for load balancing, S3 for static storage, ElastiCache for caching, ensuring 99.9% service uptime and seamless transactions.

• Enhanced database performance in PostgreSQL and MySQL by optimizing SQL queries, indexing, and schema design, reducing query execution time by 40%, enabling real-time inventory updates and order tracking for accelerated order fulfillment speed.

• Implemented Elasticsearch-driven product search, optimizing indexing, query tuning, and relevancy scoring, reducing query latency by 40%, and enhancing user experience autocomplete, synonym handling, and faceted search, delivering faster, more relevant results.

• Strengthened security by integrating OAuth 2.0, JWT, and Spring Security, ensuring secure customer authentication, protecting payment transactions, and safeguarding sensitive data, ultimately enhancing user trust and compliance.

• Built an authentication system with JWT and Firebase, ensuring secure user login and session management.

• Formulated JUnit and Selenium test cases with Software Analysis and approaches such as Boundary Value Analysis, and Decision Trees, identifying and addressing issues in 35% of the functions.

• Automated CI/CD pipelines using GitHub Actions and Docker, reducing deployment time by 40%.

• Engineered a pandas+scikit‑learn preprocessing pipeline for 22,000 Fall 2023–2024 undergraduate records, performing data

cleaning, feature encoding, normalization, and dimensionality reduction to optimize model inputs.

• Developed and optimized a PyTorch neural network for university admission prediction, achieving 96.55% test accuracy,

87.59% F1 score, and 94.91% AUROC.The model leveraged MPS GPU acceleration, embedding layers for categorical

features, and advanced deep learning techniques like class-weighted loss to handle imbalanced datasets, further enhancing its

predictive power and model efficiency.

• Performed inference on Fall 2025 admission data with a total of 12,569 applications, and the model correctly predicted 1,055

out of 1,288 deposits, achieving a recall of 81.91%, demonstrating the model’s strong ability to accurately identify admitted

students and its effectiveness in real-world prediction tasks

• Utilized Slate CRM as a Graduate Assistant to support GPA calculations in enrollment operations and enhance the graduate

international student application process, optimizing workflows and ensuring the efficient processing and management of

application data.

• Built and optimized responsive web applications using React.js, TypeScript, and Redux, improving UI performance and reducing page load time by 25%.

• Collaborated with cross-functional teams to integrate RESTful APIs (Node.js / Spring Boot) and implement JWT-based authentication, accelerating

feature delivery by 30% while maintaining secure access controls.

• Refactored theAndroid and iOS cross platform code base to introduce reusability and maintainability paradigms that resulted in reducing the overall development time by 20% achieving a cost saving of $1000 annually.

• Redesigned the Pizza Hut checkout page using usability testing, improving navigation and supporting localization for 10+ countries, resulting in a 15% increase in global checkout completion rates.

• Implemented agile methods and sprint planning to use Jira, leading to a 75% reduction in testing issues through streamlined communication with the Quality Assurance team saving $2,875 in potential post-release bug-fix.

• Applied Clean Code principles such as consistent formatting and naming conventions to refactor Android/IOS codebase, reducing technical debt by 30% and enabling reusable modules for future scalability.

• Developed a cybersecurity analytics dashboard using React.js, D3.js, and Node.js, improving data visualization and reducing data retrieval time by 30%, leading to a 20% increase in user engagement.

• Optimized website performance and resolved backend inefficiencies using Chrome DevTools and Express.js, boosting Lighthouse performance scores by 43%.

• Delivered 3 full-stack websites for external clients using React.js, Node.js, and MongoDB, achieving 100% on-time delivery and increasing satisfaction scores from 3.7/5 to 4.8/5.

• Migrated a landing page codebase from JavaScript to React.js and integrated a backend API, reducing load time by 0.5 seconds and driving a 15% revenue increase from improved customer retention.

• Ensured mobile responsiveness and cross-browser compatibility through usability testing and BrowserStack, optimizing UI for 92% of screen sizes across mobile, tablets, and desktops.