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Sitong Pan

dblp:399/2888 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2026
0009-0006-7729-6497ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 3 · 1 first-author · 3 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
2 papers
Learning and educational technologies · 56% User interface design and tools · 44%
Databases, data mining, and information retrieval
1 paper
Data models and query languages · 100%

Topics — the 1 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Learning and educational technologies › student modeling
simulated students		 0.312025
TutorUp: What If Your Students Were Simulated? Training Tutors to Address Engagement Challenges in Online Learning · CHI 2025

Methods — techniques the papers use, named apart from their topics

large language model · 2.6simulation · 0.9
YearPublicationVenuePosition
2026 TrajectoryCurer: Visual Analysis of Trajectory Data Quality
Xiaodan Miao, Sitong Pan, Shifu Chen, Di Weng, Yingcai Wu
 PacificVis2
2025 TutorUp: What If Your Students Were Simulated? Training Tutors to Address Engagement Challenges in Online Learning
abstract
CHI ’25, Yokohama, Japan
Sitong Pan, Robin Schmucker, Bernardo García Bulle Bueno, Salome Aguilar Llanes, Fernanda Albo Alarcón, Hangxiao Zhu, Adam Teo, Meng Xia 0002
 CHI1
2025 ReSpark: Leveraging Previous Data Reports as References to Generate New Reports with LLMs
abstract
Figure 1: ReSpark Overview.ReSpark helps users generate new data reports by reusing existing ones.It begins by ranking reports based on their alignment with the target dataset to assist in selecting a reference report (a).The selected report is then segmented into a sequence of analysis segments (b).For each segment, ReSpark extracts the analysis objective (c) and adapts it to the target dataset (d1).It then generates the corresponding code and charts (d2), followed by textual insights (d3).These elements are finally composed into a new report.
Sitong Pan, Weiwei Cui 0001, Dazhen Deng, Yingcai Wu
 UIST4