Yinglan Ma
About Yinglan Ma
Yinglan Ma is a Machine Learning Engineering Manager at Adobe, focusing on integrating machine learning with Photoshop to improve user experience. He holds a Master's degree in Computer Science from Stanford University and a Bachelor's degree from the University of Illinois at Urbana-Champaign.
Work at Adobe
Yinglan Ma currently serves as a Machine Learning Engineering Manager at Adobe, a position held since 2023. In this role, Ma focuses on integrating machine learning technologies with Photoshop to improve user experience. Prior to this position, Ma worked at Adobe in various capacities, including Applied Research Engineer and Computer Scientist. Ma's tenure at Adobe spans from 2016 to the present, with significant contributions made in machine learning and AI integration.
Education and Expertise
Yinglan Ma holds a Master's degree in Computer Science from Stanford University, where studies were completed from 2015 to 2017. Prior to this, Ma earned a Bachelor of Science (B.S.) in Computer Science from the University of Illinois at Urbana-Champaign, graduating in 2015. This educational background provides a strong foundation in computer science principles and machine learning applications.
Achievements
In recognition of contributions to technology at Adobe, Yinglan Ma received the Adobe 2022 Tech Excellence Award. This award highlights Ma's commitment to advancing technology and enhancing user experiences through innovative machine learning solutions.
Background
Yinglan Ma began working at Adobe as a Technology Transfer Research Intern in 2016. Following this internship, Ma progressed to roles such as Computer Scientist from 2017 to 2021 and Applied Research Engineer from 2021 to 2023. Ma's career trajectory at Adobe reflects a focus on research and application of machine learning in software development.
Advocacy for Responsible AI
Yinglan Ma advocates for responsible AI practices in technology development. This advocacy emphasizes the importance of ethical considerations and accountability in the deployment of machine learning technologies, ensuring that advancements benefit users and society as a whole.