黑料导航

College of Engineering and Computing Sciences graduate student Rudriben (Rudri) Trivedi earned her bachelor鈥檚 degree in computer engineering at Gujarat Technological University in India. Then, she made the life-changing decision to leave everything behind and further her education in the United States by pursuing a master鈥檚 degree in computer science.

鈥淚 wanted to gain global exposure, access advanced learning opportunities, and build a career in technology,鈥� Trivedi says of her international move. 鈥満诹系己� stood out to me because of its strong focus on practical, hands-on learning and its location in New York City, which offers great opportunities to engage with the tech industry and work on real-world projects.鈥�

Trivedi recalls a constant curiosity about how computers work and how software applications are built, crediting her undergraduate years with discovering her passion for programming, data analysis, and machine learning. Working on projects and solving technical challenges in the field only deepened her interest and motivated her to pursue a graduate-level degree.

On the New York City campus, Trivedi is working on projects that fuel her fascination with how technology can solve real-world problems. As part of her coursework, she is tasked with analyzing historical Formula 1 racing data to forecast performance trends. Such analyses can impact predictive analytics, business forecasting, and data-driven decision-making.

At the same time, she is pursuing independent efforts exploring real-world applications of data analysis and machine learning鈥攖opics that are among her primary areas of interest.

One undertaking uses data analysis and information retrieval techniques to detect missing information. By identifying gaps in datasets and improving data quality, this work can strengthen decision-making systems. Another initiative uses a data analytics application to look at and interpret New York City transportation data and generate interactive, near-real-time insights into transit patterns like ridership trends, station activity, and operational data. She hopes this project will enable a better understanding of mobility patterns and demonstrate how data analytics can support smarter decision-making and city planning.

In March, Trivedi went the extra mile to support her understanding and practice in computer science disciplines when she attended two Google-sponsored events in New York City.

From March 7 through 8, she visited Columbia Business School for Google Developer Groups鈥� NYC Build with AI Hackathon. With a team of students and professionals, Trivedi worked on a web-based application, SignPulse AI, designed to translate sign language in real time and improve accessibility for non-verbal sign language speakers. The app used computer vision and machine learning models to detect hand gestures and facial expressions. It then generated natural speech to facilitate communication.

Days later, Trivedi visited Google鈥檚 SoHo office for another Build with AI event. This time, she was a listener as industry experts discussed how organizations can move from AI proofs-of-concepts to production-ready enterprise systems. In addition to attending lecture sessions, she networked with professionals and other students, exchanged ideas, and learned how AI solutions are applied in real-world scenarios.

鈥淓xperiences like these are incredibly inspiring and continue to motivate me to explore the future of AI systems, cloud infrastructure, and intelligent applications,鈥� she reflects. 鈥淚 enjoy exploring how intelligent systems can automate tasks, analyze large datasets, and help organizations make better strategic decisions.鈥�

With one year left before completing her program, Trivedi is planning for post-graduation life. A full-time role in data analytics or AI would be ideal, but simply being able to apply her skills and continue her professional growth is enough to excite her for the future.

鈥淎t 黑料导航, I have gained valuable technical skills as well as important professional perspectives,鈥� Trivedi says. 鈥淚 am excited to work on real-world problems and be part of a field that is continuously evolving and creating new possibilities.鈥�