VLDB 2026 Research / reviewers in the wild / expert
Leslie Smith
dblp:08/6195
· DBLP profile ↗
5ranked-venue papers
1as first author
3since 2021 · last 2026
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 3 · 3 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Touchable Sound: Exploring Spatial Ocean Data Through Tangible and Auditory DisplaysabstractMuseum exhibits often rely on visualizations or graphics to communicate scientific data to the general public. These visual representations render the benefits of these exhibits inaccessible to blind and low vision (BLV) learners. While both tactile and auditory representations of data can serve as accessible alternatives to visualizations for BLV learners, there is little work exploring how the unique affordances and drawbacks of these modalities affect learning about data in informal learning environments (ILEs). Our work seeks to further this understanding through the design and evaluation of an accessible and interactive display for learning about ocean data. We prototyped three versions of our display, each with a different modality for representing habitat data (sound, texture, sound and texture). By prototyping multiple versions, we investigate how auditory and tactile feedback can be leveraged to support informal learning about scientific data. Emily Amspoker, Solyane Berge, Rhoney Lee, Jon P. Bellona, Leslie Smith, Amy Bower |
TEI | 5 |
| 2025 | Bootstrapping Human-Like Planning via LLMsabstractRobot end users increasingly require accessible means of specifying tasks for robots to perform. Two common end-user programming paradigms include drag-and-drop interfaces and natural language programming. Although natural language interfaces harness an intuitive form of human communication, drag-and-drop interfaces enable users to meticulously and precisely dictate the key actions of the robot’s task. In this paper, we investigate the degree to which both approaches can be combined. Specifically, we construct a large language model (LLM)-based pipeline that accepts natural language as input and produces human-like action sequences as output, specified at a level of granularity that a human would produce. We then compare these generated action sequences to another dataset of hand-specified action sequences. Although our results reveal that larger models tend to outperform smaller ones in the production of human-like action sequences, smaller models nonetheless achieve satisfactory performance. David Porfirio, Vincent Hsiao, Morgan Fine-Morris, Leslie Smith, Laura M. Hiatt |
RO-MAN | 4 |
| 2023 | "Let the Volcano Erupt!": Designing Sonification to Make Oceanography Accessible for Blind and Low Vision Students in Museum EnvironmentabstractExploring the potential of data sonification, our study focuses on enhancing accessibility to oceanographic data for blind and low vision (BLV) students in museums. Five auditory display prototypes with accompanying data sonifications were designed, and two prototypes underwent evaluation by testing with blind and low vision students from two schools for the blind. Through interviews and qualitative analysis, the study assessed the students' learning outcomes and their experience on the auditory display prototypes. The results demonstrate the effective conveyance of oceanography concepts and data through the developed audio display prototypes. Additionally, the study derived several design implications for future oceanographic data sonification design in museums. This research contributes to advancing the accessibility of oceanography education for visually impaired students while providing valuable insights for the design of future auditory displays in informal learning environments (ILE). Huaigu Li, Jon Bellona, Leslie Smith, Amy Bower |
ASSETS | 3 |
| 2013 | Putting Intelligence into Computational Intelligence
Leslie Smith |
IJCCI | 1 |
| 2008 | Neural network based pattern matching and spike detection tools and services - in the CARMEN neuroinformatics project
Martyn Fletcher, Bojian Liang, Leslie Smith, Alastair Knowles, Thomas W. Jackson, Mark Jessop, Jim Austin |
Neural Networks | 3 |