Tiffany Yu

Engineering at Applied Intuition

Tiffany Yu has a diverse work experience in the field of engineering and software development.

Tiffany started working at Applied Intuition in 2022 as an Engineering team member.

Before that, they were a Software Engineer at Uber from 2021 to 2022, where they focused on developing machine learning models and platforms to combat fraud in Uber's payment systems.

From 2018 to 2021, Tiffany was actively involved in the CMU Robotics Club. Tiffany served as a Project Liaison from 2020 to 2021, Vice President from 2019 to 2020, and Treasurer from 2018 to 2019. As a Treasurer, they managed a budget of over $20,000 to support and maintain the Roboclub makerspace, oversaw funding and logistics for events, and managed funding for small and mid-sized projects within the club.

Tiffany also had internships at Uber as a Software Engineering Intern in 2020, where they gained experience in software development, and at Facebook as a Software Engineer Intern in 2019, where they worked on creating contextual profiles and generating unit tests.

Additionally, Tiffany worked as a Research Assistant at CMU CHIMPS Lab in 2019, where they expanded an annotations plugin for Android Studio IDE and developed an Android app for testing.

Lastly, they were involved in the CMU Robotics Club (Robobuggy) from 2017 to 2019, serving as the Operations Lead and being a member of the Electrical Team.

Overall, Tiffany has shown expertise in various engineering roles and has gained valuable experience through their internships and involvement in clubs and research projects.

Tiffany Yu attended Carnegie Mellon University from 2017 to 2021. During their time there, they pursued a Bachelor of Science degree in Computer Science. Additionally, they were also involved with the CMU Human-Computer Interaction Institute, although the specific details about their degree or field of study in this institute were not provided.

Location

Mountain View, United States

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Applied Intuition

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Applied Intuition offers simulation software and infrastructure tools to safely test and validate autonomous vehicles at scale.


Employees

201-500

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