Demo Data from SIGIR 2026 / reviewers in the wild / expert
Kirill Varshavskiy
dblp:146/0082
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2
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.
| Computer networks
1 paper |
Wireless sensing and localization · 44% Internet of things and sensor networks · 44% Wireless networking · 13% | |
| Human-computer interaction and pervasive computing
1 paper |
Ubiquitous computing and smart environments · 100% |
Topics — the 4 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Ubiquitous computing and smart environments › mobile crowdsourcing
crowdsensing |
0.2 | 1 | 2014 | Demo: SaveAlert: design for a sensor-driven CrowdWatch danger detection system · MobiSys 2014 |
Wireless sensing and localization › human sensing › human activity sensing
crowd monitoring |
0.2 | 1 | 2014 | Poster: SaveAlert: an efficient and scalable sensor-driven danger detection system · MobiCom 2014 |
Internet of things and sensor networks › sensor data management
sensor data collection |
0.2 | 1 | 2014 | Poster: SaveAlert: an efficient and scalable sensor-driven danger detection system · MobiCom 2014 |
Ubiquitous computing and smart environments › mobile sensing
smartphone and smartwatch sensing |
0.1 | 1 | 2014 | Demo: SaveAlert: design for a sensor-driven CrowdWatch danger detection system · MobiSys 2014 |
Methods — techniques the papers use, named apart from their topics
sensor fusion · 0.2peer-to-peer aggregation · 0.2adaptive sensing · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Poster: SaveAlert: an efficient and scalable sensor-driven danger detection systemabstractSaveAlert is an adaptive framework for crowd-monitoring and danger-detection using off-the-shelf smartphones and other peripherals such as smartwatches. It is a system that provides users with an increased awareness of their surroundings by detecting and notifying them of impending danger, by relying only on sensor data collected from the users. Our framework's novelty is in how it performs efficient sensor data collection from potentially a large number of people by limiting the disturbance and stress on the existing Wi-Fi and cellular infrastructure. To the best of our knowledge, this is the first crowd-monitoring framework that takes advantage of peer-to-peer connections to perform local aggregation to alleviate the stress on existing infrastructures for better scalability and efficiency. Güliz Seray Tuncay, Kirill Varshavskiy, Robin Kravets, Klara Nahrstedt |
MobiCom | 2 |
| 2014 | Demo: SaveAlert: design for a sensor-driven CrowdWatch danger detection systemabstractSaveAlert is an adaptive framework for danger-detection using existing devices such as off-the-shelf smartphones and smartwatches. The framework can be extended to different sensors that could trigger distress signals to notify nearby users of potentially dangerous situations. Güliz Seray Tuncay, Kirill Varshavskiy, Robin Kravets |
MobiSys | 2 |