She was awarded the "14th Invention Entrepreneurship Award - Individual Award"

Lin Yandan, Professor at the School of Information Science and Engineering, Fudan University, and jointly appointed Professor in the Department of Human Genetics and Anthropology. She has long been engaged in research on the relationship between light environment and visual task safety, efficiency, and health, applying her findings to national defense, major transportation sectors, medical health, and smart lighting. In key pillar manufacturing industries such as aircraft, trains, and automobiles, she addresses common mechanisms of lighting safety and photobiological health, tackling key technologies that affect safe driving.

has won the Shanghai Science and Technology Progress Award (Second Class) twice, received the CSA Ten-Year Contribution Award, won the Shanghai Women's Innovation Rising Star Award, was recognized as a Shanghai March 8th Red Banner Holder, awarded as a Leading Figure in Audio-Visual Health Technology Innovation, received the Outstanding Woman in Engineering Award from the World Federation of Engineering Organizations () (the fifth recipient globally), and was named one of the "Top Ten Technological Innovation Pioneers" in the Lingang New Area. Published over 190 academic papers, including more than 50 indexed by SCI journals and EI; applied for over 40 patents.

Professor Lin Yandan invented a multi-objective optimization algorithm for light environments based on light and visual perception experiments, as well as a multi-dimensional visual assessment method, solving the complex assessment problems of light environments across multiple dimensions and scenarios. Conducting a series of human factors experimental studies on the impact of glare, light distribution, spectrum, illuminance, and color quality parameters in visual space on human visual performance and comfort, she explored the optical mechanisms affecting visual performance, visual comfort, and visual fatigue. On this basis, she established a multi-objective optimization algorithm for visual safety based on the GPR-NSGA framework under complex application scenarios, providing theoretical basis and application guidance for ensuring the safety of visual light environments in major demand scenarios such as cars, ships, and vessels.

Invented new algorithms for color, glare, and visual accommodation of images and display quality in complex light environments based on human eye perception, supplementing the theoretical foundation for human eye perception evaluation of light environments including displays and images, and applied to automotive headlight design to enhance driving safety. Conducted full-reference image quality assessment based on visual saliency of color appearance and gradient similarity, approaching human eye evaluation effects more closely, and established a dimming model for high dynamic range displays with aircraft cockpits as typical application scenarios.