From IEEE Awards to 6 Million Users: How Parthsarthi Rawat Is Democratizing AI in Youth Sports

Parthsarthi Rawat is a computer vision engineer and AI innovator on a mission to make artificial intelligence accessible to everyday people, starting with youth sports. As one of the minds behind the FilmRoom feature for GameChanger by Dick’s Sporting Goods, Rawat has helped deliver ESPN-quality video analysis to athletes, coaches, and parents using nothing more than a mobile camera. What was once the domain of professional analysts is now a tool for millions of families, with FilmRoom already reaching over six million users worldwide.

Rawat’s path to this point has been a deliberate blend of curiosity, technical mastery, and a drive to see AI serve a meaningful purpose. His journey spans award-winning robotics competitions, reviewing IEEE research papers, and now large-scale, real-world AI systems that impact millions of people each day. Each step, he says, has reinforced his belief that artificial intelligence can be both powerful and practical, provided it’s grounded in strong fundamentals. “If your basis is strong for a concept, your created AI models will surpass what your peers can comprehend,” Rawat reflects.

Foundations of a Builder

Before he became known for his work in computer vision, Parthsarthi Rawat was drawn to the mechanics of how things worked and how they could work better. He began his academic journey in mechanical engineering, a field that honed his analytical mindset and gave him an early appreciation for structure, precision, and process.

It was during his undergraduate years that Rawat first encountered robotics, not through coding experiments, but through hands-on design challenges. Competing in the ASME Student Design Competition (SDC), he led his team to first place in the Asia-Pacific region in 2018, an achievement that revealed a new dimension of problem-solving: teaching machines to move and think autonomously.

That spark of curiosity soon became a commitment to understanding how technology could interpret the physical world. Rawat began exploring computer vision, using cameras and sensors to replicate aspects of human perception. His first major research milestone came two years later, when his paper on vision-based AI earned the Best Paper Presentation Award at the 2020 IEEE International Conference on Control, Automation, and Robotics (ICCAR).

Driven by the desire to merge theory with application, he pursued a master’s degree in Robotics Engineering at Worcester Polytechnic Institute (WPI). There, he deepened his knowledge of reinforcement learning and automation systems, translating classroom rigor into hands-on experimentation. “Mechanical engineering gave me a foundation in structure,” Rawat says. “Robotics showed me how to build intelligence within that structure.”

The Sports Tech Journey

After completing his studies, Rawat began his career at SportsViso, Inc., where he worked as a machine learning engineer. During this role, he built the company’s AI pipeline, helping structure the technology that later supported the company’s successful $3 million seed funding round in 2023. 

The achievement marked a milestone early in his career, but for Rawat, it also brought a moment of clarity. Despite the success, he realized that something was missing: the tangible connection between his work and the people it was meant to serve.

“It was lacking something that was customer acquisition,” he says. “I wanted to see how helpful the AI I built could be for real people in their day-to-day lives.”

That insight led him to GameChanger by Dick’s Sporting Goods, a leading platform for youth sports scorekeeping, video, and data. Rawat joined as one of the first hires on a newly formed five-person Computer Vision team, a position that gave him both creative freedom and the opportunity to make a measurable difference. His focus was clear: bring the kind of professional-grade video analysis once exclusive to elite sports to the millions of players, parents, and coaches who make up the grassroots level of athletics.

The result was FilmRoom, a feature that uses AI to automatically detect and remove downtime from game footage, creating seamless highlight reels in minutes. By turning raw footage into watchable, action-packed content, FilmRoom not only saves time but also allows users to relive the best moments of every game. The feature’s intuitive design and underlying AI model quickly made it one of the app’s most celebrated tools, drawing over 6 million users and coverage from major media outlets.

Building on that foundation, Rawat’s AI architecture has since expanded to support other sports such as baseball and basketball, offering automated clips and highlights. His invention of a downtime classification system, which forms the basis of FilmRoom’s core functionality, has been submitted for patent protection. “I’m proud that my work has democratized ESPN-quality coverage in youth sports,” he says. “It’s the kind of project that connects AI directly to everyday people.”

Continuing to Make AI Mainstream

Rawat sees AI’s mainstream acceptance as an opportunity for even greater innovation. “I see myself providing more AI functionality for people to use in their day-to-day,” he says. “Since AI is mainstream now, my peers and I will face fewer roadblocks when creating something bold, because people believe in this technology.”

For Rawat, the journey from academic research to youth sports technology represents something larger than personal success. It reflects a broader movement toward inclusivity in AI, where complex tools are no longer confined to labs or tech giants but are instead empowering communities, one innovation at a time.