Austin Dill
About Austin Dill
Austin Dill is a Technical Lead at Motional, where he has worked since 2023. He has a strong background in machine learning and has held various research and teaching positions at prestigious institutions, including Carnegie Mellon University and Georgia Tech.
Work at Motional
Austin Dill currently serves as a Technical Lead at Motional, a role he has held since 2023. He also works as a Senior Machine Learning Research Engineer, a position he has occupied since 2022. His contributions at Motional include involvement with the Virtual World Infrastructure team at the Hyundai-Aptiv Joint Venture, where he focuses on applying machine learning techniques to enhance self-driving car technology. Prior to his current roles, he worked as a Machine Learning Research Engineer at Motional from 2020 to 2022.
Education and Expertise
Austin Dill holds a Master of Science in Machine Learning from Carnegie Mellon University, where he studied from 2018 to 2019. He completed his undergraduate studies in Computer Science at the Georgia Institute of Technology from 2014 to 2018. Additionally, he participated in a study abroad program at the University of Oxford in 2015. His research interests encompass generative models, deep learning, and learning theory, reflecting his expertise in advanced machine learning methodologies.
Background
Austin Dill has a diverse background in research and education. He worked as a Research Assistant at Carnegie Mellon University from 2018 to 2019 and later as a Teaching Assistant for four months in 2019. He also served as a Research Associate at Carnegie Mellon University for six months in 2020. Prior to his academic roles, he gained experience as a Research Intern at the Georgia Tech Research Institute from 2017 to 2018.
Research Contributions
Throughout his academic and professional career, Austin Dill has contributed to various research initiatives. His work at Carnegie Mellon University involved advising from notable faculty members Eunsu Kang and Barnabas Poczos. His research has focused on machine learning applications, particularly in the context of self-driving technology during his time at Motional and the Hyundai-Aptiv Joint Venture.