Sanket Koli

• Architected and developed a scalable micro frontend ecosystem comprising 4 independent React applications (Home, Site Monitoring, Admin, Flow Diagram) using Module Federation (Webpack 5) and CRACO, enabling seamless cross-app navigation and reducing deployment dependencies and improving release efficiency by ~30% • Automated build and release workflows by implementing Azure DevOps CI/CD pipelines using YAML-based configurations, reducing manual deployment effort by ~70% and decreasing release time by ~35% • Implemented scalable data visualization and geospatial analytics using 6 Highcharts variants and Google Maps API, enabling real-time monitoring across both short-term and long-term time windows, reducing issue detection time and improving operational efficiency by 25%

• Built a real-time chat system using SignalR with WebSocket-based communication, enabling low-latency messaging and improving responsiveness of live user interactions • Engineered an interactive flow diagram editor using JointJS (Rappid), enabling dynamic visualization and manipulation of complex system workflows within the application, supporting the creation of flow diagrams for 500+ sites

• Mentored over 40 students to provide support in understanding computer architecture, operating systems, control path design, pipelining and Objective-C programming language • Facilitated over 25 students in providing technical support in Ubuntu and Linux environments followed by grading assignments and giving feedback

• Initiated and executed the integration of innovative features – a date range filter and search bar – using the Material UI library, resulting in a substantial 30% augmentation of application usability • Achieved a 15% faster page loading speed by implementing client-side lazy loading and pagination optimization for 14K+ videos, reducing application load-time • Elevated app performance, scalability, and accessibility by seamlessly transitioning from 35+ SVG icons to Material UI counterparts, reducing code volume by an impressive 40%, optimizing overall efficiency • Collaborated with cross-functional teams in an agile environment to design, develop, maintain and deliver scalable solutions with cross-browser compatibility, utilizing Next.js, TypeScript, Cypress, Redux, and Webpack

• Led a team of four front-end developers in designing, developing, testing, and deploying cross-platform social media and social identification verification apps for Android and iOS, utilizing Figma, Flutter, Postman, Xcode, and TestFlight • Enhanced application security and user trust by seamlessly incorporating third-party APIs like Twilio and Passbase for social identity verification, bolstering user confidence and experience • Integrated 35+ backend RESTful APIs into frontend, leveraging Redux for robust state management, resulting in streamlined data processing, and a more responsive user experience • Implemented TDD (Test Driven Development) with Jest and React Testing Library for unit, integration, and end-to-end tests, leading to a 40% reduction in post-release bug reports and a 15% acceleration in development cycles • Collaborated with UI/UX designers and back-end engineers, strategically developing front-end architecture and translating over 105 UX wireframes and design mockups into functional frontend user interfaces, resulting in 25% increase in user engagement

I graduated from Pace University, NYC in May 2023 with a master's degree in Computer Science. The Seidenberg School of CSIS provides a variety of courses in computer science. The courses that I liked the most were Mobile Web Development, Product Development Project, Algorithms and Computing Theory, Database Management Systems, Human-computer Interaction, and Computer Science Project I & II. I was actively part of the study-abroad program at Pace University's NYC Design Factory enrolled in the Product Development Project in association with Aalto University in Espoo, Finland. With a team of 3 software engineers and 7 mechanical engineers, we built a "Drone Detection System" from scratch. The focus of the project was to build a low-cost drone detection system to detect drones in confidential areas such as military bases, airports, etc.