Doctor of design with rich experience in human-computer interaction research, mobile application design, user experience research. The current leader of Baidu TPG user research team and has been responsible for user research of Baidu healthcare, Baidu search, DuerOS, Baidu map, Baidu input method, etc. Focusing on user experience research in fields of intelligent products and innovative interaction. Before joining Baidu, worked as interaction designer and user researcher in Nokia, Lenovo, Tencent and Alibaba.
More than twenty research papers were published in MobileHCI, HCI, INTERACT, OZCHI and domestic core journals, and more than twenty invention patents were filed. In recent years, be committed to promoting the upgrading of product intelligent experience through solid and professional user research.
Design belief: Successful products stem from in-depth user research.
With the development and application of AI technology, AI is driving more and more products innovation. In addition to the emergence of innovative intelligent hardware, AI also enables traditional products. The human-machine relationship changes dramatically, the focus of user research also changes simultaneously.
In this workshop, Baidu TPG user research team will introduce their recent three years’ research experience. For many types of AI products, how can user researchers provide scientific and reliable research support for product and business innovation through reasonable research planning. Under the background of AI technology driving product and experience innovation, how to build the comprehensive influence of user research. From the perspective of technology, product and experience, this workshop will provide an AI product user research course combining theory and practice.
This workshop will help user researchers understand the characteristics of AI product experience research, and quickly learn the typical research topics and research methods of AI products. And help designers, PM, engineers and other relevant practitioners in AI industry learn the basic knowledge of AI product research and be able to apply it in practical work.
The contents of the workshop include:
1. AI technology drives product and experience innovation
1.1 Voice, vision, AR/VR and interactive experience innovation
1.2 Two typical AI products: AI innovative products and transformed AI products
1.3 Challenges and difficulties of AI products user research
2. Two types of AI products research map and methodology
2.1 AI product user research type and research value
2.2 Impact of AI products type on research planning
2.3 AI products research map：goal, topic and method
3. User research practices of two types of AI products
3.1 Intelligent hardware user research cases: smart speakers and robots
3.2 Mobile applications user research cases: Baidu map and Baidu input method
4. AI products user research value and comprehensive influence
4.1 Industry influence, how to participate in the formulation of industry standards
4.2 Business influence, integrating platform capability, cooperation mode and innovation
4.3 Other influence
2、New topics of user research: AI driving product and experience upgrade
3、Value thinking and research map of AI products research: two typical AI products
4、Research cases: intelligent hardware products (smart speaker, robot) and mobile application products (Baidu map, Baidu input method)
5、AI user research influence construction: industry standard, trend report, platform capability, innovation tool
6、Exercise and discussion: grouping, research topic (conversational AI design), group discussion, research topics define and share, speaker comment
1、3-5 years user researchers
2、3-5 years product managers
3、Intermediate/senior interaction designers
4、Relevant practitioners in AI industry, and people who are interested in AI
1、Help user researchers understand the characteristics of AI product research, as well as the ideas and methods of research planning
2、Help designers and product managers to understand the typical research topics of AI products, as well as learn the basic knowledge of AI product research and can apply it in practical work
3、Participatory discussion and co-creation, and think forward together about the challenges facing future AI product design, and expanding knowledge boundaries in advance