Demo Data from EDBT 2026 / reviewers in the wild / expert
Mohamad Eid
dblp:412/1111
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2026
0000-0002-6940-7891ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2 · 2 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
1 paper |
Haptics and multimodal interaction · 77% Learning and educational technologies · 23% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Learning and educational technologies
embodied learning |
0.3 | 1 | 2026 | FretFlow: Adaptive Haptics for Rhythm and Articulation in Guitar Learning · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
user study · 1.0formative study · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | FretFlow: Adaptive Haptics for Rhythm and Articulation in Guitar LearningabstractRhythm and articulation are essential for expressive guitar performance. Existing tools provide basic beat cues, whereas beginners often struggle to align with these cues when playing complex techniques, such as strumming and muting. Informed by a formative study with five instructors and grounded in embodied learning theories, we present FretFlow, a haptic vest-based tool that simulates common instructional practices to guide learners through physical interactions like tapping. The key to FretFlow is its design space that maps rhythmic and articulation patterns in various playing techniques to distinct haptic patterns, enabling authoring of haptic scores. FretFlow further dynamically adapts haptic intensity based on learners’ real-time performance accuracy, accompanied by multimodal guidance across haptic, visual, and audio channels. We iteratively refined haptic designs across two rounds with 46 participants, followed by a two-week user study with 20 beginners. Results show that FretFlow improves learners’ rhythmic accuracy and expressive performance. Xin Shu 0009, Lei Shi 0003, Yiran Lin, Tingting Luo, Justice Ou, Mohamad Eid, Xinhuan Shu |
CHI | 7 |
| 2025 | Editorial for special issue on multimodal human-computer interaction for pervasive computing
Dangxiao Wang, Ying-Qing Xu, Mohamad Eid |
CCF Trans. Pervasive Comput. Interact. | 3 |