May 31, 2024
Hancheng Cao, Stanford University
From collaborative software to generative AI, computing technologies are redefining the way we work, communicate and collaborate. Yet with the growing complexities of computing platforms, it becomes increasingly challenging to foresee their impacts on human behavior, leading to not only poor user experience but also problematic applications that mirror and amplify societal issues. How can we better understand machine behavior and machine-mediated user behavior over computing platforms? How can we build applications that align with our needs and values with emerging computing technologies? My research aims to answer these questions through developing novel empirical measurements, technical methods and design. In this talk, I will present my work demonstrating this approach in the future of work context, where I have established data-driven, AI-powered and human-centered methods to understand, evaluate and design information systems at the workplace. I will present an analysis of remote meeting experience through mining millions of meetings, a study on how an AI algorithm can be built to predict team fracture, and a development and evaluation study on a generative AI-based scientific feedback system for researchers. These projects exemplify the opportunities to leverage computation to better understand, support and augment work practices.
About the speaker:
Hancheng Cao is a final year PhD candidate in computer science (with a PhD minor in management science and engineering) at Stanford University. He works in the field of computational social science and human computer interaction, where he mines large-scale data, develops algorithms and builds systems to study human behavior. Recognized as a Stanford Interdisciplinary Graduate Fellow, he has published 30 academic papers across fields, with three works he led recognized as Best Paper (CHI 2023) or Honorable Mention (CSCW 2020, CHI 2021) awards. His research has also appeared in leading social science journals (e.g. American Sociological Review). His research has been widely covered in the media, including Wired, Forbes, New Scientist, TED among others.
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21 авг 2024
