Demo Data from SIGIR 2026 / reviewers in the wild / expert
Maheshya Weerasinghe
dblp:172/4908
· DBLP profile ↗
7ranked-venue papers
3as first author
5since 2021 · last 2025
0000-0003-2691-601XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 4 · 3 first-author · 4 since 2021Human-computer interaction and ubiquitous computing · 2 · 1 since 2021Artificial intelligence and machine learning · 1
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
5 papers |
Learning and educational technologies · 43% Collaborative and social computing · 18% Immersive interaction · 12% | |
| Computer graphics and multimedia
3 papers |
Virtual and augmented reality · 75% Multimedia systems and quality of experience · 25% | |
| Network and information security
1 paper |
Usable security · 100% |
Topics — the 6 heaviest of 11, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Learning and educational technologies › immersive learning
augmented reality learning |
1.1 | 2 | 2022 | Arigatō: Effects of Adaptive Guidance on Engagement and Performance in Augmented Reality Learning Environments · IEEE Trans. Vis. Comput. Graph. 2022 VocabulARy: Learning Vocabulary in AR Supported by Keyword Visualisations · IEEE Trans. Vis. Comput. Graph. 2022 |
Collaborative and social computing › collaborative virtual environments
social virtual reality |
0.9 | 1 | 2025 | Beyond Mute and Block: Adoption and Effectiveness of Safety Tools in Social VR, from Ubiquitous Harassment to Social Sculpting · IEEE Trans. Vis. Comput. Graph. 2025 |
Usability and user experience research
simulator sickness |
0.6 | 1 | 2022 | Quantifying the Effects of Working in VR for One Week · IEEE Trans. Vis. Comput. Graph. 2022 |
Immersive interaction › virtual reality
virtual reality for knowledge work |
0.6 | 1 | 2022 | Quantifying the Effects of Working in VR for One Week · IEEE Trans. Vis. Comput. Graph. 2022 |
Learning and educational technologies › language learning
vocabulary learning |
0.6 | 1 | 2022 | VocabulARy: Learning Vocabulary in AR Supported by Keyword Visualisations · IEEE Trans. Vis. Comput. Graph. 2022 |
Virtual and augmented reality
augmented reality |
0.3 | 2 | 2022 | Arigatō: Effects of Adaptive Guidance on Engagement and Performance in Augmented Reality Learning Environments · IEEE Trans. Vis. Comput. Graph. 2022 VocabulARy: Learning Vocabulary in AR Supported by Keyword Visualisations · IEEE Trans. Vis. Comput. Graph. 2022 |
Methods — techniques the papers use, named apart from their topics
user study · 3.1survey · 1.7design space exploration · 0.8comparative user study · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Text-to-Image Generation for Vocabulary Learning Using the Keyword MethodabstractThe ‘keyword method’ is an effective technique for learning vocabulary of a foreign language. It involves creating a memorable visual link between what a word means and what its pronunciation in a foreign language sounds like in the learner’s native language. However, these memorable visual links remain implicit in the people’s mind and are not easy to remember for a large number of words. To enhance the memorisation and recall of the vocabulary, we developed an application that combines the keyword method with text-to-image generators to externalise the memorable visual links into visuals. These visuals represent additional stimuli during the memorisation process. To explore the effectiveness of this approach we first run a pilot study to investigate how difficult it is to externalise the descriptions of mental visualisations of memorable links, by asking participants to write them down. We used these descriptions as prompts for text-to-image generator (DALL-E 2) to convert them into images and asked participants to select their favourites. Next, we compared different text-to-image generators (DALL-E 2, Midjourney, Stable and Latent Diffusion) to evaluate the perceived quality of the generated images by each. Despite heterogeneous results, participants mostly preferred images generated by DALL-E 2, which was used also for the final study. In this study, we investigated whether providing such images enhances the retention of vocabulary being learned, compared to the keyword method alone. Our results indicate that people did not encounter difficulties describing their visualisations of memorable links and that providing corresponding images significantly increases memory retention. Nuwan T. Attygalle, Matjaz Kljun, Aaron J. Quigley, Klen Copic Pucihar, Jens Grubert, Verena Biener, Luis A. Leiva, Juri Yoneyama, Alice Toniolo, Angela Miguel, Hirokazu Kato 0001, Maheshya Weerasinghe |
IUI | 12 |
| 2025 | Beyond Mute and Block: Adoption and Effectiveness of Safety Tools in Social VR, from Ubiquitous Harassment to Social SculptingabstractHarassment in Social Virtual Reality (SVR) is a growing concern. The current SVR landscape features inconsistent access to non-standardised safety features, with minimal empirical evidence on their real-world effectiveness, usage and impact. We examine the use and effectiveness of safety tools across 12 popular SVR platforms by surveying 100 users about their experiences of different types of harassment and their use of features like muting, blocking, personal spaces and safety gestures. While harassment remained common-including hate speech, virtual stalking, and physical harassment-many find safety features insufficient or inconsistently applied. Reactive tools like muting and blocking are widely used, largely driven by users' familiarity from other platforms. Safety tools are also used to proactively curate individual virtual experiences, protecting users from harassment, but inadvertently leading to fragmented social spaces. We advocate for standardising proactive, rather than reactive, anti-harassment tools across platforms, and present insights into future safety feature development. Maheshya Weerasinghe, Shaun Alexander Macdonald, Cristina Fiani, Joseph O'Hagan, Mathieu Chollet, Mark McGill, Mohamed Khamis |
IEEE Trans. Vis. Comput. Graph. | 1 |
| 2022 | Quantifying the Effects of Working in VR for One WeekabstractVirtual Reality (VR) provides new possibilities for modern knowledge work. However, the potential advantages of virtual work environments can only be used if it is feasible to work in them for an extended period of time. Until now, there are limited studies of long-term effects when working in VR. This paper addresses the need for understanding such long-term effects. Specifically, we report on a comparative study $i$, in which participants were working in VR for an entire week-for five days, eight hours each day-as well as in a baseline physical desktop environment. This study aims to quantify the effects of exchanging a desktop-based work environment with a VR-based environment. Hence, during this study, we do not present the participants with the best possible VR system but rather a setup delivering a comparable experience to working in the physical desktop environment. The study reveals that, as expected, VR results in significantly worse ratings across most measures. Among other results, we found concerning levels of simulator sickness, below average usability ratings and two participants dropped out on the first day using VR, due to migraine, nausea and anxiety. Nevertheless, there is some indication that participants gradually overcame negative first impressions and initial discomfort. Overall, this study helps lay the groundwork for subsequent research, by clearly highlighting current shortcomings and identifying opportunities for improving the experience of working in VR. Verena Biener, Snehanjali Kalamkar, Negar Nouri, Eyal Ofek, Michel Pahud, John J. Dudley, Jinghui Hu, Per Ola Kristensson, Maheshya Weerasinghe, Klen Copic Pucihar, Matjaz Kljun, Stephan Streuber, Jens Grubert |
IEEE Trans. Vis. Comput. Graph. | 9 |
| 2022 | VocabulARy: Learning Vocabulary in AR Supported by Keyword VisualisationsabstractLearning vocabulary in a primary or secondary language is enhanced when we encounter words in context. This context can be afforded by the place or activity we are engaged with. Existing learning environments include formal learning, mnemonics, flashcards, use of a dictionary or thesaurus, all leading to practice with new words in context. In this work, we propose an enhancement to the language learning process by providing the user with words and learning tools in context, with VocabulARy. VocabulARy visually annotates objects in AR, in the user's surroundings, with the corresponding English (first language) and Japanese (second language) words to enhance the language learning process. In addition to the written and audio description of each word, we also present the user with a keyword and its visualisation to enhance memory retention. We evaluate our prototype by comparing it to an alternate AR system that does not show an additional visualisation of the keyword, and, also, we compare it to two non-AR systems on a tablet, one with and one without visualising the keyword. Our results indicate that AR outperforms the tablet system regarding immediate recall, mental effort and task-completion time. Additionally, the visualisation approach scored significantly higher than showing only the written keyword with respect to immediate and delayed recall and learning efficiency, mental effort and task-completion time. Maheshya Weerasinghe, Verena Biener, Jens Grubert, Aaron J. Quigley, Alice Toniolo, Klen Copic Pucihar, Matjaz Kljun |
IEEE Trans. Vis. Comput. Graph. | 1 |
| 2022 | Arigatō: Effects of Adaptive Guidance on Engagement and Performance in Augmented Reality Learning EnvironmentsabstractExperiential learning (ExL) is the process of learning through experience or more specifically "learning through reflection on doing". In this paper, we propose a simulation of these experiences, in Augmented Reality (AR), addressing the problem of language learning. Such systems provide an excellent setting to support "adaptive guidance", in a digital form, within a real environment. Adaptive guidance allows the instructions and learning content to be customised for the individual learner, thus creating a unique learning experience. We developed an adaptive guidance AR system for language learning, we call Arigato (Augmented Reality Instructional ¯ Guidance & Tailored Omniverse), which offers immediate assistance, resources specific to the learner's needs, manipulation of these resources, and relevant feedback. Considering guidance, we employ this prototype to investigate the effect of the amount of guidance (fixed vs. adaptive-amount) and the type of guidance (fixed vs. adaptive-associations) on the engagement and consequently the learning outcomes of language learning in an AR environment. The results for the amount of guidance show that compared to the adaptive-amount, the fixed-amount of guidance group scored better in the immediate and delayed (after 7 days) recall tests. However, this group also invested a significantly higher mental effort to complete the task. The results for the type of guidance show that the adaptive-associations group outperforms the fixed-associations group in the immediate, delayed (after 7 days) recall tests, and learning efficiency. The adaptive-associations group also showed significantly lower mental effort and spent less time to complete the task. Maheshya Weerasinghe, Aaron J. Quigley, Klen Copic Pucihar, Alice Toniolo, Angela Miguel, Matjaz Kljun |
IEEE Trans. Vis. Comput. Graph. | 1 |
| 2019 | Augmentation not Duplication: Considerations for the Design of Digitally-Augmented Comic BooksabstractDigital-augmentation of print-media can provide contextually relevant audio, visual, or haptic content to supplement the static text and images. The design of such augmentation--its medium, quantity, frequency, content, and access technique--can have a significant impact on the reading experience. In the worst case, such as where children are learning to read, the print medium can become a proxy for accessing digital content only, and the textual content is avoided. In this work, we examine how augmented content can change the reader's behaviour with a comic book. We first report on the usage of a commercially available augmented comic for children, providing evidence that a third of all readers converted to simply viewing the digital media when printed content is duplicated. Second, we explore the design space for digital content augmentation in print media. Third, we report a user study with 136 children that examined the impact of both content length and presentation in a digitally-augmented comic book. From this, we report a series of design guidelines to assist designers and editors in the development of digitally-augmented print media. Matjaz Kljun, Klen Copic Pucihar, Jason Alexander, Maheshya Weerasinghe, Cuauhtli Campos, Julie Ducasse, Barbara Kopacin, Jens Grubert, Paul Coulton, Miha Celar |
CHI | 4 |
| 2015 | Real-Time Simulation of Aero-optical Distortions Due to Air Density Fluctuations at Supersonic Speed
Najini Harischandra, Nihal D. Kodikara, K. D. Sandaruwan, G. K. A. Dias, Maheshya Weerasinghe |
ICONIP (3) | 5 |