The Team

Here's a little bit about the folks behind Gojurn

Tim Wang

CEO

A former engineer at both Zynga and Google, Tim's love of technology and games sparked the idea that would later evolve into Gojurn. Tim's a world traveler and foodie at heart, and he's always looking to share a great recommendation or two on either topic.

Matteo Marinucci

Client Engineer

After helping to build some of the most popular and beloved titles at Zynga and paying his dues at Ampush, Matteo joined Gojurn with the hope of creating something that let him connect with others on this two most favorite topics: movies and video games.

Will Tian

Client Engineer

A graduate of UC Berkeley, Will left the world of finance to work on solving data analytics issues in the the Bay Area startup community. He joined Gojurn to help apply his insights towards building a better recommendation experience for people all over the world.

Josh Hsu

Business Development

Josh is a tech industry verteran with experience in entertainment and gaming. He joined Gojurn with the purpose building a network of shared experiences and journeys around the globe. His favorite topics are Music Festivals, EDM, outdoor activities, and sports.

Elizabeth Schweizer

QA Lead

Elizabeth gets her start in QA from testing mobile games. She came aboard to help ensure Gojurn runs smoothly as well as track user feedback as it evolves. She loves sweet shops, sushi spots, and binge-watching cartoons, and she can't wait to recommend them all.

Kelly Xu

UI Design

A former Lead Designer at Zynga. Kelly joined Gojurn team to help create a clean and cohesive user experience on mobile devices. She has a strong passion on UI design and she continues to design products that makes impact on people's everyday lives.

Tyler Wishnoff

Customer Development

A former marketing and analytics lead at Cisco Systems, Tyler joined up with Gojurn to help build a useful tool for people seeking trustworthy recommendations from their peers. An avid reader, he is always happy to share a few book recommendations.