First-author work on generative-AI video streaming and semantic compression at the University of Klagenfurt
2
papers here
2
reviewed by Evolve
2
first-author
0
corresponding
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works · OpenAlex
3
h-index · OpenAlex
Bibliometric figures come from OpenAlex (2026-10-14) and cover the author's entire public record, not just the papers listed here. Reproducibility signal comes from Evolve's own reviews.
Research profile
Output—
Insufficient data: this axis measures total publication volume and productivity trajectory across venues and years. The snapshot provides only per-year work counts (3, 4, 3 for 2024-2026) and no aggregate output metric, so it cannot yet be scored.
Impact—
Insufficient data: this axis measures citation accumulation and scholarly influence over time. The record shows an early h-index of 3 with i10-index of 0, too sparse a citation base to score; influence cannot yet be meaningfully assessed.
Focus0/100
The radar focus score is 0, derived from an even 50/50 split of the record between "multimedia computing (video streaming and generative computer vision)" and "multimedia systems / video coding". Read literally the score flags low field-label concentration; substantively the two halves are adjacent sub-areas of one streaming-plus-generative-media agenda, and the topic list is topped by image and video quality assessment (7 topic-tagged works).
Collaboration32/100
The collaboration score is 32, consistent with a compact network: 4 distinct coauthors over the last three years, with recurring partners Farzad Tashtarian, Christian Timmerer, Daniele Lorenzi and Shivi Vats. Both catalogued 2026 papers are first-author works rather than corresponding-author ones, suggesting a leading-contributor role inside a small, dense, single-institution group rather than a wide collaboration web.
Activity70/100
Activity scores 70, supported by 10 works in the last three years and a steady counts-by-year profile of 3 (2024), 4 (2025) and 3 (2026). The cadence shows uninterrupted production since 2024, and 2026 further includes two first-author arXiv preprints catalogued by Evolve, indicating an actively running research line in generative video streaming.
Reproducibility60/100
Reproducibility scores 60 as a mean across 2 assessed papers, and the two pull in opposite directions: PRESLEY is rated high — rigorous statistics, honestly stated limits — while GenStream is rated low, being partially built with unquantified claims. The split suggests the score tracks Evolve's paper-level evidence quality rather than a uniform research practice.
Research summary
Emanuele Artioli is a researcher at the University of Klagenfurt (Austria) whose work sits at the intersection of video streaming, perceptual quality assessment, and generative AI reconstruction. His OpenAlex record, resolved from public bibliographic data, shows an early-career footprint: h-index 3, i10-index 0, and 10 works in the last three years, distributed as 3 (2024), 4 (2025) and 3 (2026). Topic tags on that record are dominated by image and video quality assessment (7), followed by network traffic and congestion control, video coding and compression, and generative adversarial networks and image synthesis (3 each), plus computer graphics and visualization (2). His fields split evenly between multimedia computing (video streaming and generative computer vision) and multimedia systems / video coding. Evolve catalogues him as a full-tier profile on the strength of two first-author 2026 arXiv papers. GenStream proposes replacing transmitted video with pose and viewpoint metadata for generative reconstruction, claiming over 99.9% bandwidth savings versus HEVC — promising, Evolve judges, but partially built and unquantified. PRESLEY refines an end-to-end streaming pipeline with generative AI layers, degrading blocks in place and restoring them with conditioned super-resolution to beat ELVIS at matched rate, with rigorous statistics and honestly stated limits. He publishes within a small, dense, Klagenfurt-centered collaboration network.
Collaboration pattern
Artioli's recorded collaboration footprint is compact: 4 distinct coauthors in the last three years, all recurring — Farzad Tashtarian, Christian Timmerer, Daniele Lorenzi and Shivi Vats — consistent with a single Klagenfurt-based streaming and multimedia systems group. Both catalogued 2026 papers list him as first author but not corresponding, indicating he drives the writing and experiments while senior collaborators anchor the projects. The radar collaboration score of 32 reflects this small, dense, single-institution pattern.
Research keywords
Highlights
PRESLEY: generative refinement beats ELVIS at matched rate
GenStream claims >99.9% bandwidth savings via semantic streaming
Timeline
- 2024First works appear in the OpenAlex record, with 3 outputs in the counts-by-year data.
- 2025Output rises to 4 works, the highest yearly count in the available record.
- 20263 works recorded so far, including two first-author arXiv preprints catalogued by Evolve: GenStream and PRESLEY.
Papers in the Evolve catalog
Frequent co-authors
About this profile
This profile is AI-structured by Evolve.Pub from public bibliographic data (OpenAlex) and Evolve's own paper reviews. It is not written or endorsed by the researcher unless the profile is claimed. Radar dimensions are computed from real bibliometrics with fixed formulas — raw figures are shown alongside; missing dimensions mean insufficient data, never zero. Errors? Claim the profile to correct or hide it.
- Bibliometrics are sourced from OpenAlex only; output and impact dimensions lack sufficient underlying data and are deliberately unscored.
- Both catalogued works are 2026 arXiv preprints; peer-reviewed venues are not represented in this snapshot.
- Identity is name-resolved from public bibliographic data (OpenAlex); residual name ambiguity cannot be fully excluded.
- The reproducibility mean (60) rests on only 2 reviewed papers, so the score has thin coverage.