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AR Prototyping at Niantic

AR Prototyping at Niantic

June - April 2022

Niantic Inc.

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About The Project:

Technology & Mediums:

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Technology & Mediums:

June - April 2022

PROCESS:

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AR Advertisement Prototyping

Exploring the future of advertising was a priority for my team, so we regularly experimented with how new technology could be used to enhance our features. In particular, we wanted to more closely integrate our content into the real world around the player so I had the opportunity to work on a variety of AR prototypes for games like Peridot and Pokémon GO. This experimentation pushed the boundaries of Niantic's computer vision and geolocation technology, using features like semantic segmentation, image recognition, and plane mapping to create compelling, boundary-pushing AR experiences. I also fully brought the parallel reality feature into Pokémon GO that responded in real time to the player’s location as they walked.

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Implementing Ad Activations in Our Games

Once a feature was defined, I was also responsible for ensuring they were seamlessly integrated into the gameplay of popular titles. During the prototyping phase, this meant closely collaborating with a game’s UX designers to ensure features were noticeable, positive experiences for players that did not disrupt the game’s overall progression. Once we were satisfied with an experience, implementation required me to efficiently adapt to the game’s code base, generally in C# for Unity, and maintain features long-term as games continued to grow. As our games involved large numbers of players across using a variety of mobile devices, efficiency, latency, and cross-platform compatibility were major considerations I learned to take into account.

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Full-Stack Contributions

Because the Sponsorship team was small and agile, my work often extended beyond Unity development. I regularly contributed to our full-stack development, helping to build and maintain server components for our games in Java, as well as web portals for our advertising partners in Angular and React. This gave me an in-depth understanding of our advertising pipeline from end to end and allowed me to identify points where generalizations could be made to reduce redundant work.

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