VLDB 2026 Research / reviewers in the wild / expert
Xinyue Chen 0001
dblp:124/5261-1
· DBLP profile ↗
10ranked-venue papers
6as first author
9since 2021 · last 2026
0000-0002-0774-223XORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 10 · 6 first-author · 9 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | From Conversation to Human-AI Common Ground: Extracting Cognitive Workflows for Reuse in Sense-making TasksabstractKnowledge workers increasingly rely on conversational AI for sense-making tasks (e.g., conducting market analysis), yet must repeatedly reconstruct context and intent to meet their goals. A formative study (N=10) showed that workflow reuse with AI often failed. Current tools either only remember preferences or enforce rigid, predefined workflows—neither adapts to evolving goals. We present ThinkFlow, a system that maintains a dynamic common ground through a cognitive workflow schema, enabling users to express intent and AI to adapt and reuse workflows across contexts. An expert-rating study shows that the schema can accurately capture the collocutor’s reasoning process, and when reused for a similar task, improves the AI’s responses compared to when the schema isn’t present. A user study with eight knowledge workers demonstrates that ThinkFlow supports awareness of evolving workflows, intent expression, and flexible application across contexts. Xinyue Chen 0001, Varun Manjunatha, Xu Wang 0016, Alexa F. Siu |
CHI | 1 |
| 2025 | Designing Interfaces that Support Temporal Work Across Meetings with Generative AIabstractPeer Reviewed Rishi Vanukuru, Payod Panda, Xinyue Chen 0001, Ava Scott, Lev Tankelevitch, Sean Rintel |
Conference on Designing Interactive Systems | 3 |
| 2025 | Are We On Track? AI-Assisted Active and Passive Goal Reflection During MeetingsabstractMeetings often suffer from a lack of intentionality, such as unclear goals and straying off-topic. Identifying goals and maintaining their clarity throughout a meeting is challenging, as discussions and uncertainties evolve. Yet meeting technologies predominantly fail to support meeting intentionality. AI-assisted reflection is a promising approach. To explore this, we conducted a technology probe study with 15 knowledge workers, integrating their real meeting data into two AI-assisted reflection probes: a passive and active design. Participants identified goal clarification as a foundational aspect of reflection. Goal clarity enabled people to assess when their meetings were off-track and reprioritize accordingly. Passive AI intervention helped participants maintain focus through non-intrusive feedback, while active AI intervention, though effective at triggering immediate reflection and action, risked disrupting the conversation flow. We identify three key design dimensions for AI-assisted reflection systems, and provide insights into design trade-offs, emphasizing the need to adapt intervention intensity and timing, balance democratic input with efficiency, and offer user control to foster intentional, goal-oriented behavior during meetings and beyond. Xinyue Chen 0001, Lev Tankelevitch, Rishi Vanukuru, Ava Scott, Payod Panda, Sean Rintel |
CHI | 1 |
| 2025 | LADICA: A Large Shared Display Interface for Generative AI Cognitive Assistance in Co-located Team CollaborationabstractPeer Reviewed Zheng Zhang 0043, Weirui Peng, Xinyue Chen 0001, Luke Cao, Toby Jia-Jun Li |
CHI | 3 |
| 2025 | MeetMap: Real-Time Collaborative Dialogue Mapping with LLMs in Online MeetingsabstractVideo meeting platforms display conversations linearly through transcripts or summaries. However, ideas during a meeting do not emerge linearly. We leverage LLMs to create dialogue maps in real time to help people visually structure and connect ideas. Balancing the need to reduce the cognitive load on users during the conversation while giving them sufficient control when using AI, we explore two system variants that encompass different levels of AI assistance. In Human-Map, AI generates summaries of conversations as nodes, and users create dialogue maps with the nodes. In AI-Map, AI produces dialogue maps where users can make edits. We ran a within-subject experiment with ten pairs of users, comparing the two MeetMap variants and a baseline. Users preferred MeetMap over traditional methods for taking notes, which aligned better with their mental models of conversations. Users liked the ease of use for AI-Map due to the low effort demands and appreciated the hands-on opportunity in Human-Map for sense-making. Xinyue Chen 0001, Nathan Yap, Xinyi Lu 0004, Aylin Gunal, Xu Wang 0016 |
Proc. ACM Hum. Comput. Interact. | 1 |
| 2024 | Looking Together ≠ Seeing the Same Thing: Understanding Surgeons' Visual Needs During Intra-operative Coordination and InstructionabstractShared gaze visualizations have been found to enhance collaboration and communication outcomes in diverse HCI scenarios including computer supported collaborative work and learning contexts. Given the importance of gaze in surgery operations, especially when a surgeon trainer and trainee need to coordinate their actions, research on the use of gaze to facilitate intra-operative coordination and instruction has been limited and shows mixed implications. We performed a field observation of 8 surgeries and an interview study with 14 surgeons to understand their visual needs during operations, informing ways to leverage and augment gaze to enhance intra-operative coordination and instruction. We found that trainees have varying needs in receiving visual guidance which are often unfulfilled by the trainers’ instructions. It is critical for surgeons to control the timing of the gaze-based visualizations and effectively interpret gaze data. We suggest overlay technologies, e.g., gaze-based summaries and depth sensing, to augment raw gaze in support of surgical coordination and instruction. Vitaliy Popov, Xinyue Chen 0001, Michael Kemp, Gurjit Sandhu, Taylor Kantor, Natalie Mateju, Xu Wang 0016 |
CHI | 2 |
| 2023 | "My Culture, My People, My Hometown": Chinese Ethnic Minorities Seeking Cultural Sustainability by Video BloggingabstractEthnic minorities face challenges in sustaining their culture in regions dominated by ethnic majorities. With the growing popularity of video blogging (vlogging) in China, many ethnic minority vloggers are using vlogs to present and promote their ethnic culture online. In this study, we interviewed 16 vloggers onDouyin to understand why and how vlogs can be used to sustain ethnic culture. We found that both ethnic cultural experts and non-experts were involved in ethnic vlog making and sharing activities onDouyin, and cultural experts took more initiative in preserving and promoting ethnic culture while non-experts were more motivated by getting more traffic and income. Vloggers' imagined audiences included both intra-ethnic and mainstream viewers, impacting their vlog-making strategies, the utilized platform features, and the created vlog content. For example, vloggers taught ethnic language and built an identity for intra-ethnic viewers. Both ethnic minority vloggers and viewers protected their culture from misinterpretation by mainstream viewers. Our findings suggest the potential of using video blogging to address the challenges of cultural sustainability, providing design implications for future ICTs to support the cultural sustainability of ethnic minorities. Si Chen 0006, Xinyue Chen 0001, Zhicong Lu, Yun Huang 0003 |
Proc. ACM Hum. Comput. Interact. | 2 |
| 2023 | MeetScript: Designing Transcript-based Interactions to Support Active Participation in Group Video MeetingsabstractWhile videoconferencing is prevalent, concurrent participation channels are limited. People experience challenges keeping up with the discussion, and misunderstanding frequently occurs. Through a formative study, we probed into the design space of providing real-time transcripts as an extra communication space for video meeting attendees. We then present MeetScript, a system that provides parallel participation channels through real-time interactive transcripts. MeetScript visualizes the discussion through a chat-alike interface and allows meeting attendees to make real-time collaborative annotations. Over time, MeetScript gradually hides extraneous content to retain the most essential information on the transcript, with the goal of reducing the cognitive load required on users to process the information in real time. In an experiment with 80 users in 22 teams, we compared MeetScript with two baseline conditions where participants used Zoom alone (business-as-usual), or Zoom with an adds-on transcription service (Otter.ai). We found that MeetScript significantly enhanced people's non-verbal participation and recollection of their teams' decision-making processes compared to the baselines. Users liked that MeetScript allowed them to easily navigate the transcript and contextualize feedback and new ideas with existing ones. Xinyue Chen 0001, Shipeng Liu, Robin R. Fowler, Xu Wang 0016 |
Proc. ACM Hum. Comput. Interact. | 1 |
| 2022 | Scaling Mixed-Methods Formative Assessments (mixFA) in Classrooms: A Clustering Pipeline to Identify Student Knowledge
Xinyue Chen 0001, Xu Wang 0016 |
AIED (1) | 1 |
| 2020 | "I was afraid, but now I enjoy being a streamer!": Understanding the Challenges and Prospects of Using Live Streaming for Online EducationabstractThe outbreak of COVID-19 has led to a sharp transition from offline to online education in many countries and areas. This transition heightens the intensity of existing challenges of online education, such as student attendance and education equality. During this time of uncertainty, the vast disparities in teachers? online experience and technical backgrounds, students' education level and their families' economic status, and schools' support, further pose new challenges to teachers and students. In this work, we study how Chinese teachers and students addressed challenges during this transition. We interviewed 15 teachers and 18 students from diverse backgrounds at varying education levels (K-12 and college). Our work makes timely and new contributions to the literature of online education. For example, our results showed that teachers applied Live Video Streaming (LVS) on multiple social media platforms and re-purposed different entertainment features to deliver online teaching for better student engagement; some teachers came to enjoy this new form of instruction after being resistant to it in the beginning, and students developed a better sense of intimacy with their teachers after experiencing certain online interactions. Our work also reveals the remaining challenges and prospects of LVS-based online education and sheds light on the future design of collaborative technologies for online education. Xinyue Chen 0001, Si Chen 0006, Xu Wang 0016, Yun Huang 0003 |
Proc. ACM Hum. Comput. Interact. | 1 |