James Landay Recognized for ACM SIGCHI Lifetime Research Award
Stanford HAI is pleased to announce that Vice Director James Landay has been acknowledged by the Association for Computing Machinery (ACM) for a SIGCHI Lifetime Research Award.
The SIGCHI (special interest group on computer-human interaction) Awards honor leaders in the field of human-computer interaction. The lifetime research award in particular recognizes the best, more influential research contributions, given to an individual for a lifetime of innovation and leadership.
Landay is a professor of computer science and the Anand Rajaraman and Venky Harinarayan Professor in the School of Engineering at Stanford University. He co-founded Stanford HAI and leads all research efforts at the institute. His contributions to the HCI field include technology to support behavior change, demonstrational interfaces, mobile and ubiquitous computing, and user interface design tools. Landay is well known for founding and building vibrant HCI and human-centered AI research communities at Berkeley, Washington, and Stanford.
The awardees will be formally recognized at the upcoming ACM CHI 2024 conference in May.
Related News
The new center will examine AI's real-world impacts on jobs, teams, and organizational performance.
The new center will examine AI's real-world impacts on jobs, teams, and organizational performance.
More than 200 academic teams submitted proposals to the AI for Organizations Grand Challenge, exploring how artificial intelligence will transform teamwork and collaboration.
More than 200 academic teams submitted proposals to the AI for Organizations Grand Challenge, exploring how artificial intelligence will transform teamwork and collaboration.
HAI Executive Director Russell Wald talks about the AI competition between the U.S. and China, and the advent of “world models” that predict what might happen in real-world environments.
HAI Executive Director Russell Wald talks about the AI competition between the U.S. and China, and the advent of “world models” that predict what might happen in real-world environments.