VLDB 2026 Research / reviewers in the wild / expert
Vuthea Chheang
dblp:255/9361
· DBLP profile ↗
8ranked-venue papers
3as first author
7since 2021 · last 2026
0000-0001-5999-4968ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 7 · 2 first-author · 7 since 2021Systems, architecture and hardware · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Re-Evaluating Virtual Reality Manipulation Techniques for Precise Alignment of Complex 3D ObjectsabstractPrior research has developed a number of manipulation techniques that can achieve precise object placement in virtual reality, but studies of these techniques typically use simple objects. We conducted a study comparing two existing techniques, (AMP-IT and WISDOM), during alignment of objects with complex geometry to evaluate the potential influence of geometric complexity on performance, usability, workload and preference. Our findings indicate that participants had faster completion times and higher trial completion rates with AMP-IT on high-precision alignment tasks, contrary to earlier findings that used simple objects. Yet WISDOM is still preferred and considered more usable, despite increased workload and poorer performance, exposing participants' willingness to trade objective performance for comfort during use. Cherelle Connor, Alexander Giovannelli, Leonardo Pavanatto, Francielly Rodrigues, Haichao Miao, Vuthea Chheang, Brian Giera, Peer-Timo Bremer, Doug A. Bowman |
IEEE Trans. Vis. Comput. Graph. | 6 |
| 2025 | Investigating the Influence of Playback Interactivity during Guided Tours for Asynchronous Collaboration in Virtual RealityabstractCollaborative virtual environments allow workers to contribute to team projects across space and time. While much research has closely examined the problem of working in different spaces at the same time, few have investigated the best practices for collaborating in those spaces at different times aside from textual and auditory annotations. We designed a system that allows experts to record a tour inside a virtual inspection space, preserving knowledge and providing later observers with insights through a 3D playback of the expert’s inspection. We also created several interactions to ensure that observers are tracking the tour and remaining engaged. We conducted a user study to evaluate the influence of these interactions on an observing user’s information recall and user experience. Findings indicate that independent viewpoint control during a tour enhances the user experience compared to fully passive playback and that additional interactivity can improve auditory and spatial recall of key information conveyed during the tour. Alexander Giovannelli, Leonardo Pavanatto, Shakiba Davari, Haichao Miao, Vuthea Chheang, Brian Giera, Peer-Timo Bremer, Doug A. Bowman |
VR | 5 |
| 2025 | Exploring Bichronous Collaboration in Virtual EnvironmentsabstractVirtual environments (VEs) empower geographically distributed teams to collaborate on a shared project regardless of time. Existing research has separately investigated collaborations within these VEs at the same time (i.e., synchronous) or different times (i.e., asynchronous). In this work, we highlight the often-overlooked concept of bichronous collaboration and define it as the seamless integration of archived information during a real-time collaborative session. We revisit the time-space matrix of computer-supported cooperative work (CSCW) and reclassify the time dimension as a continuum. We describe a system that empowers collaboration across the temporal states of the time continuum within a VE during remote work. We conducted a user study using the system to discover how the bichronous temporal state impacts the user experience during a collaborative inspection. Findings indicate that the bichronous temporal state is beneficial to collaborative activities for information processing, but has drawbacks such as changed interaction and positioning behaviors in the VE. Alexander Giovannelli, Shakiba Davari, Cherelle Connor, Fionn Murphy, Trey Davis, Haichao Miao, Vuthea Chheang, Brian Giera, Peer-Timo Bremer, Doug A. Bowman |
VRST | 7 |
| 2025 | LatticeAnalytics: Strut-Level Visualization and Inspection of Additively Manufactured Lattice StructuresabstractAdditive manufacturing (AM) is revolutionizing the production of custom components with complex internal geometries, essential for high-performance applications in diverse fields such as medicine and defense. These AM parts optimize strength while minimizing weight by utilizing internal lattice structures consisting of large quantities of small interconnected struts. However, the complexity of these structures, combined with the challenges of using X-ray Computed Tomography (XCT) data, makes validation of part reliability difficult. This ultimately inhibits the development of novel parts for our collaborating material scientists. We introduce LatticeAnalytics, a novel framework specifically designed for visual inspection of defects in these lattice structures. Our framework offers an end-to-end solution that includes the data management of XCT scans, enables remote access for geographically dispersed teams through a web-based dashboard, and incorporates novel visualizations. Our analysis is facilitated by a coarse alignment between the lattice's nominal model, a spatial graph, and the XCT data. We employ a simple VR-based approach for fast and rough alignment, followed by an offline registration and identification of the struts. With the nodes and struts aligned and identified in the volume, our framework allows querying of subvolumes containing a single strut at multiple resolutions. This avoids computation over the entire lattice and also allow for easy parallelization of down-stream computations, such as strut-specific metrics. To depict a fast overview of the strut quality, we introduce two innovative visual encodings, crucial for our collaborators' research in creating novel AM parts: the Contour View and the Roughness Map, which depict critical geometrical and surface features of individual struts in standardized two 2D views. We evaluated the integrated system through expert interviews. The feedback confirms the framework's practicality and its effectiveness in enhancing current inspection workflows. It solves major bottlenecks for our collaborators, ultimately helping them create novel parts with advanced properties. Haichao Miao, Saurabh Narain, Vuthea Chheang, Garrett Hooten, Raiyan Seede, Pavol Klacansky, Kaila Morgen Bertsch, Gabe Guss, Brian Giera, Peer-Timo Bremer |
IEEE Trans. Vis. Comput. Graph. | 3 |
| 2024 | Advanced liver surgery training in collaborative VR environmentsabstractVirtual surgical training systems are crucial for enabling mental preparation, supporting decision-making, and improving surgical skills. Many virtual surgical training environments focus only on training for a specific medical skill and take place in a single virtual room. However, surgical education and training include the planning of procedures as well as interventions in the operating room context. Moreover, collaboration among surgeons and other medical professionals is only applicable to a limited extent. This work presents a collaborative VR environment similar to a virtual teaching hospital to support surgical training and interprofessional collaboration in a co-located or remote environment. The environment supports photo-realistic avatars and scenarios ranging from planning to training procedures in the virtual operating room. It includes a lobby, a virtual surgical planning room with four surgical planning stations, laparoscopic liver surgery training with the integration of laparoscopic surgical instruments, and medical training scenarios for interprofessional team training in a virtual operating room. Each component was evaluated by domain experts as well as in a series of user studies, providing insights on usability, usefulness, and potential research directions. The proposed environment may serve as a foundation for future medical training simulators. Vuthea Chheang, Danny Schott, Patrick Saalfeld, Lukas Vradelis, Tobias Huber, Florentine Huettl, Hauke Lang, Bernhard Preim, Christian Hansen 0001 |
Comput. Graph. | 1 |
| 2024 | Visual feedback and guided balance training in an immersive virtual reality environment for lower extremity rehabilitation
Sydney Segear, Vuthea Chheang, Lauren Baron, Kangsoo Kim, Roghayeh Barmaki |
Comput. Graph. | 2 |
| 2021 | A collaborative virtual reality environment for liver surgery planning
Vuthea Chheang, Patrick Saalfeld, Fabian Joeres, Christian Boedecker, Tobias Huber, Florentine Huettl, Hauke Lang, Bernhard Preim, Christian Hansen 0001 |
Comput. Graph. | 1 |
| 2020 | Natural embedding of live actors and entities into 360° virtual reality scenes
Vuthea Chheang, Sangkwon Jeong, Gookhwan Lee, Jong-Sung Ha, Kwan-Hee Yoo |
J. Supercomput. | 1 |