● Dataset Collection & Development:•Actively involved in curating a proprietary dataset for gesture synthesis.•Collaborated with friends and classmates who generously posed for data collection sessions.•Utilizing RGB cameras and Leap Motion controllers to capture high-fidelity gesture data, ensuring comprehensive representation of hand movements.● Gen AI Model Development: •Initiated the development of a groundbreaking AI model capable of synthesizing 3D hand gestures from textual input. •Employed datasets from RGB cameras and Leap Motion controllers to ensure accurate gesture modeling. •Future plans include the incorporation of both static and dynamic hand gesture capabilities to broaden application scope.● Gesture Recognition for American Sign Language: •Successfully pioneered a TensorFlow-based, image detection ASL gesture recognition model. •Leveraged Google's MediaPipe for precise hand gesture detection, achieving accurate recognition of ASL alphabets and numbers for static gestures.● Hand Gesture Machine Learning Analysis: •Expertly engineered and critically evaluated models such as SVM, Random Forest and Deep Neural Network to interpret hand gestures from data, enhancing the predictve accuracy of our gesture recognition system•Utilized advanced feature extraction techniques to meticulously analyze hand attributes sourced from JSON data files, enhancing gesture prediction accuracy.•Technologies Used: Python, TensorFlow, MediaPipe, OpenCV, Matplotlib.● Ongoing Research:•Actively working on enhancing the model's capabilities to encompass a broader range of hand gestures, targeting both static and dynamic gestures for comprehensive coverage

● Customer Hierarchy•Feature Toggle Implementation: Designed a toggle to prevent accidental releases on in-house systems, enhancing deployment safety and increasing frequency by 43%.•Database Optimization: Redesigned database tables to support Customer Hierarchy functionality, saving 12% in memory and enhancing system performance.•CRUD Operations Efficiency: Improved the efficiency of sales, billing, and pricing document operations by 8%, streamlining business processes.•Pricing Logic Enhancement: Integrated customer hierarchy details into the pricing mechanism, allowing automatic determination of prices or discounts based on hierarchy, improving code productivity by 11%.•Customization Contributions: Contributed significantly to the customization and configuration within the pricing application, focusing on new fields and access sequences for customer hierarchy, enhancing pricing strategies.•Quality Assurance Focus: Ensured the reliability and performance of pricing features through comprehensive testing, including unit and integration tests, to uphold system integrity.● Production Engineering and Operations •Agile Development: Contributed to agile development processes, collaborating with a team to adapt product features in response to client feedback from Germany.•Code Optimization and Unit Testing: Enhanced system efficiency by 18% through backend code re-engineering and comprehensive unit testing using ABAP Unit.•Issue Resolution Expertise: Addressed and solved over 10 critical issues, implementing best practices to improve product performance.•JIRA Ticket Management: Efficiently managed and resolved 25+ JIRA tickets, facilitating smooth backend development operations.•System Integration and Technical Implementation: Integrated SAP S/4HANA with ERP systems, leveraging BAPIs and BADIs for effective function calls and data exchanges.

•Developed a cache mechanism to optimize TLS connection stability, addressing a critical issue where employee email verification through LDAP failed a lot of time. By caching verified emails for 6 hours, the solution reduced data transfer errors by 46%, enhancing LDAP communication efficiency by 37%.• Automated performance tests for Xfinity boxes, saving 32 hours per release cycle and significantly accelerating the deployment process.

● Change-Based Testing FrameworkAs a Software Developer Intern, I independently developed a change-based testing framework, leveraging Python on Linux to parse .am Makefiles for automated dependency and component impact analysis. This innovative approach pinpointed exactly which components required testing following any code changes, dramatically streamlining the testing process.● Key Contributions:•Engineered a solution to analyze .am files, establishing a clear file-to-component dependency mapping.•Significantly reduced the scope of regression testing needed for each change, cutting down testing time by over 3 days and expediting the overall release process.•Collaborated closely with senior developers for guidance, integrating their expertise to refine and enhance the framework's effectiveness.This project not only showcased my technical skills and ability to contribute valuable improvements to the software development lifecycle but also highlighted my capacity to work effectively under the mentorship of experienced professionals.