INTERN
Highlights
Enhanced Recorder Software using Python, integrating extensive shell scripting and constructing RPMs.
Created user-friendly GUI applications in Python for lightweight Linux servers, enhancing usability.
Improved system performance and user interaction by 30%, optimizing functionality and efficiency.
MEMBER OF TECHNICAL STAFF
Highlights
Served as an integral part of a cross-functional team in architecting and implementing three pivotal micro-services, which dramatically increased the cost-effectiveness of VMware Cloud on AWS by 15% within Q1 of deployment.
Managed a wide range of networking requirements for complex hybrid cloud infrastructure, implementing optimizations that reduced network latency by up to 20%.
Coordinated the successful migration of the Skyscraper Networking service to the Runway Concourse CI/CD framework which automated 95% of manual deployment tasks, enhancing the service's scalability and reliability.
Introduced a series of key performance indicators (KPIs) and analytics tools to monitor micro-service performance, leading to an overall improvement of 22% in system efficiency and response time.
INTERN
Highlights
Developed Virtual Cluster Memory (vCM), a new system offering enhanced data reliability and storage efficiency. Successfully onboarded over 10 internal clients.
Augmented the initial vCM prototype by incorporating mirroring and compression functionalities, effectively reducing storage requirements by 15% and increasing data integrity without compromising on speed.
INTERN
Highlights
Constructed a GUI tool specifically designed for bio-medical researchers, facilitating the plotting and analysis of ECG and EEG signals. This application promoted the productivity of users by approximately 20%.
Utilized MathWorks' proprietary Ul components to build an intuitive and user-friendly interface. The tool received a user satisfaction rating of 90% during internal reviews.
SOFTWARE DEVELOPMENT INTERN
Highlights
Engineered an OCR-focused solution that analyzed invoices to discern consumer behavior patterns through the application of Machine Learning algorithms, processing in excess of 500 invoices in its beta phase.
Designed a website for visualizing these consumer usage patterns, handling 3000+ data points. The web-based dashboard offered interactive charts and graphs, thereby facilitating easier decision-making for retailers.
Java, C++, Python, C, Go, R, SQL, Bash, Shell, MATLAB.
Spring, SpringBoot, REST API, Micro-services, Hadoop, Spark, React, Angular, JavaScript, HTML5, CSS.
Git, AWS, GCP, Docker, Kubernetes, Jenkins, Runway Concourse, Helm, POSTMAN, MongoDB, DynamoDB, LogZ.
Summary
Architected a spatial analytics platform using Three.js and React to render complex 3D visualizations of cancer cell data, enabling researchers to analyze spatial relationships and patterns in cellular structures. Implemented a scalable backend infrastructure using Flask and Google Cloud Platform for efficient storage and retrieval of high-dimensional spatial data, optimizing query performance for large-scale cancer cell datasets.
Summary
Developed an end-to-end medical transcription system utilizing Assembly Al API, Claude and Gemini LLM APIs for automated report generation from doctor-patient conversations, achieving up to 88.6% accuracy. Engineered a full-stack application with React.js frontend and FastAPI backend to process clinical audio files, implementing HIPAA-compliant system that handled 100+ simulated respiratory case conversations.