Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Syed Shabih Hasan

dblp:14/9693 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks
mobile sensing
0.212014
CSense: a stream-processing toolkit for robust and high-rate mobile sensing applications · IPSN 2014
Network measurement and analytics
stream processing
0.212014
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
YearPublicationVenuePosition
2014 CSense: a stream-processing toolkit for robust and high-rate mobile sensing applications
Farley Lai, Syed Shabih Hasan, Austin Laugesen, Octav Chipara
IPSN2
2013 AudioSense: Enabling real-time evaluation of hearing aid technology in-situ
abstract
AudioSense 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
CBMS1