David Eng
About David Eng
David Eng is a Co-Founder of Bunkerhill Health, where he has worked since 2019. He has a background in computer science, with experience as a researcher and software engineering intern at various prestigious institutions, including Stanford University and Facebook.
Work at Bunkerhill Health
David Eng has served as Co-Founder at Bunkerhill Health since 2019. In this role, he contributes to the development and implementation of innovative health solutions. His experience in technology and healthcare enables him to drive projects that aim to enhance patient care and streamline healthcare processes.
Education and Expertise
David Eng holds a Master’s Degree in Computer Science and a Bachelor of Science (BS) in Computer Science from Stanford University. His academic background provides a strong foundation in software engineering and artificial intelligence. He has also gained practical experience through various internships and research positions, enhancing his expertise in machine learning and software development.
Background
David Eng began his academic journey at Saratoga High School before pursuing higher education at Stanford University. His early research experience includes a position at UCLA as a researcher from 2010 to 2011. He later worked at Stanford University in various capacities, including as a Course Assistant, Course Instructor, and Researcher, where he led projects focused on deep learning and AI applications in healthcare.
Internship Experience
David Eng has completed several internships that have shaped his career in technology. He interned at Citadel LLC in 2015, where he gained experience in software engineering. In 2016, he furthered his skills with internships at Facebook as a Software Engineering Intern (ML) and at Robinhood as a Software Engineering Intern (Backend), both of which contributed to his understanding of machine learning and backend development.
Research Contributions
David Eng has made significant contributions to research during his time at Stanford University. He led a team that trained a deep-learning algorithm to assess skeletal age using radiographs. Additionally, he conducted a multicenter controlled trial to evaluate AI performance across multiple sites, showcasing his ability to integrate technology with clinical research.