Peter Michael
About Peter Michael
Peter Michael is a research intern with a strong academic background in computer science and engineering. He has held various internships and research positions, including roles at Microsoft, NASA, and Oak Ridge National Laboratory.
Work at Runway
Peter Michael currently holds the position of Research Intern at Runway, a role he has been in since 2021. His work focuses on advancing research initiatives within the organization, contributing to projects that leverage his expertise in computer science and machine learning.
Education and Expertise
Peter Michael is pursuing a Master of Science in Computer Science at the University of Washington, a program he has been enrolled in since 2021. He previously earned a Bachelor of Science in Computer Engineering from the same institution, completing his studies in 2021. His foundational education includes an Associate of Science in Electrical and Computer Engineering from Edmonds Community College, which he achieved in 2018.
Background
Peter Michael has a diverse background in research and internships across various prestigious organizations. He has interned at Microsoft, NASA, and Oak Ridge National Laboratory, gaining experience in software engineering, machine learning, and research methodologies. His early career also includes a role as a STEM tutor at Edmonds Community College.
Research Contributions
Peter has presented his research work at the SPIE Medical Imaging 2020 conference, showcasing his contributions to the field. He is a member of the Facial Expressions Research Group at the University of Washington, where he has been mentored by notable faculty members in the area of facial expression transfer and recognition.
Technical Skills and Focus Areas
Peter Michael possesses a strong academic foundation in various technical subjects, including advanced linear algebra, optimization, computer architecture, digital design, embedded systems, signal and image processing, machine learning, databases, and distributed systems. His current research focuses on few-shot semantic segmentation algorithms, reflecting his commitment to advancing knowledge in computer vision.