Demo Data from VLDB 2026 / reviewers in the wild / expert
Syed Shabih Hasan
dblp:14/9693
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorComputer networks · 1Human-computer interaction and ubiquitous computing · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 first-author
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 |
Internet of things and sensor networks · 50% Network measurement and analytics · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks
mobile sensing |
0.2 | 1 | 2014 | CSense: a stream-processing toolkit for robust and high-rate mobile sensing applications · IPSN 2014 |
Network measurement and analytics
stream processing |
0.2 | 1 | 2014 | CSense: a stream-processing toolkit for robust and high-rate mobile sensing applications · IPSN 2014 |
Methods — techniques the papers use, named apart from their topics
stream processing · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | CSense: a stream-processing toolkit for robust and high-rate mobile sensing applications
Farley Lai, Syed Shabih Hasan, Austin Laugesen, Octav Chipara |
IPSN | 2 |
| 2013 | AudioSense: Enabling real-time evaluation of hearing aid technology in-situabstractAudioSense integrates mobile phones and web technology to measure hearing aid performance in real-time and in-situ. Measuring the performance of hearing aids in the real world poses significant challenges as it depends on the patient's listening context. AudioSense uses Ecological Momentary Assessment methods to evaluate both the perceived hearing aid performance as well as to characterize the listening environment using electronic surveys. AudioSense further characterizes a patient's listening context by recording their GPS location and sound samples. By creating a time-synchronized record of listening performance and listening contexts, AudioSense will allow researchers to understand the relationship between listening context and hearing aid performance. Performance evaluation shows that AudioSense is reliable, energy-efficient, and can estimate Signal-to-Noise Ratio (SNR) levels from captured audio samples. Syed Shabih Hasan, Farley Lai, Octav Chipara, Yu-Hsiang Wu |
CBMS | 1 |