Ang L.
About Ang L.
Ang L. is a Software Engineer II at TuSimple, where he has contributed to autonomous driving technology since 2021. He holds a Master's degree in Software Engineering from Carnegie Mellon University and has experience in mentoring and advisory roles in software engineering education.
Work at TuSimple
Currently, Ang L. serves as a Software Engineer II at TuSimple, a role he has held since 2021 in San Diego, California. In this position, he contributes to the development of autonomous driving technology, focusing on integrating machine learning models into scalable software systems. Prior to this role, he was a Software Engineer Intern at TuSimple in 2020 for three months, where he gained practical experience in the field.
Education and Expertise
Ang L. holds a Master of Software Engineering in Scalable Systems from Carnegie Mellon University, which he completed in 2020. He also earned a Bachelor's degree in Computer Software Engineering from Northeastern University (CN) in 2019. Additionally, he studied Computer Science and Engineering at UC San Diego as an exchange undergraduate for 11 months in 2018. His educational background is complemented by a Data Analytics program completed at Udacity in 2017.
Background
Ang L. began his career as a Research Intern at Northeastern University (CN) in 2016, where he worked for six months in Shenyang, Liaoning, China. He later served as a Research Assistant at the same institution from 2017 to 2018 for ten months. He also gained experience as an Algorithm Engineer Intern at Alibaba Group in 2018 for one month in Hangzhou, Zhejiang, China.
Advisory Roles and Mentoring
Since 2021, Ang L. has been an Advisory Board Member for the Design Thinking program at UC Riverside Extension, where he provides insights into software engineering and technology trends. He actively engages in mentoring activities, supporting students and young professionals interested in software engineering and technology.
Projects and Contributions
Ang L. has participated in projects that apply big data techniques to optimize software performance. His work at TuSimple has involved significant contributions to the development of autonomous driving technology, showcasing his expertise in integrating machine learning models into scalable software systems.