报告人
Jing Qian New York University 时间 2025年5月6日 星期二 下午 14:00-15:00 地点
102 会议室
Abstract Human-AI collaborative systems aim to offer new experiences and support human decision-making, work efficacy, and skill capabilities. However, current systems fail to understand the rich semantic meaning of the user's actions and of the surrounding interactive environment, and are not optimized for overall task efficacy and intuitiveness. As a result, these systems suffer in scalability, efficacy, and practicality. My vision is to enable intuitive, efficient, and context-aware interactive systems to promote overall practicality and scalability in domain-specific and everyday settings. Specifically, I design, build, and evaluate AI-assisted augmented reality (AR) and virtual reality (VR) to improve users' task efficacy, interaction intuitiveness, and cognitive load in both high-stake domain applications and real-life tasks. My research spans two main areas: 1) understanding the user and its environment to support efficient task execution and 2) adaptive and fluid interfaces to support natural interaction with AI systems. The talk will present four works to cover how I achieved these goals by combining design, cognitive, and HCI theories with statistical models and AI systems. Looking forward, I aim to explore long-term human-AI symbiosis with multi-user interactions to support our life goals and expectations by exploring how AI can efficiently and ethically support our decisions and augment our skill capabilities.
Biography Jing Qian is a research assistant professor at New York University in the Tandon School of Engineering, focusing on human-AI collaboration and Extended reality(XR). His work uses AI combined with interdisciplinary methods to improve users' task performance and workflow while enabling intuitive interaction in the XR environment. Jing has published as first-author and co-last author at top-tier HCI conferences such as ACM CHI, UIST, UbiComp, and IEEE VR with a broad social impact. His open-source systems have drawn over 1.6 million views on major news outlets such as VentureBeat and Sina and over 2 million playbacks on Snapchat. Jing participated in several grants, such as NSF, DARPA, and NIH, and has been awarded research gifts from Adobe and Pixar. Aside from Jing's doctoral degree in Computer Science from Brown University, he also holds an MFA from the University of Pennsylvania and used to work as an interactive designer in Shanghai.
