Shikhar Kumar

During my Data Science Fellowship at UCR, I worked on solving a major friction point students face every quarter when planning their courses. The process was highly fragmented and manual — students had to check course offerings, track completed courses, refer to recommended degree plans, and verify eligibility across multiple university systems, making planning time-consuming and often confusing. I led the design and development of a one-stop AI-powered solution to streamline this experience. The system intelligently combines student history, degree requirements, and real-time course availability to generate personalized schedules. As the project evolved, I expanded the system by integrating structured university data, enabling it to handle academic policies, constraints, and FAQs, making it a more comprehensive and practical tool for students.

At Nagarro, our team worked on a distributed system responsible for maintaining data consistency across multiple services for a large-scale automobile client. These systems needed to stay synchronized in near real-time, with changes flowing in both directions. This introduced challenges around handling continuous streams of events, ensuring reliability, and maintaining consistency across services even in the presence of failures. To address this, we built a robust event-driven synchronization system that processed incoming change events, propagated updates across services, and ensured data integrity. The system was designed to handle failures gracefully and maintain consistency at scale, while supporting reliable operation in a production environment.