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

Dogaç Eldenk

dblp:407/9027 · DBLP profile ↗
← Back
3ranked-venue papers
1as first author
3since 2021 · last 2026
0009-0004-0628-9156ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Computer networks · 1 · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021

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.

Human-computer interaction and pervasive computing
1 paper
Wearable and physiological sensing · 67% Health and well-being technologies · 33%
Computer graphics and multimedia
1 paper
Visual content generation and editing · 100%
Artificial intelligence
1 paper
Segmentation and scene understanding · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Health and well-being technologies › health monitoring
cardiac monitoring
1.012026
Short Paper: EarSleeve: Transforming Everyday Earphones into a 12-Lead ECG Sensing Platform · SenSys 2026
Wearable and physiological sensing › earable sensing
earphone-based sensing
1.012026
Short Paper: EarSleeve: Transforming Everyday Earphones into a 12-Lead ECG Sensing Platform · SenSys 2026
Wearable and physiological sensing › vital sign monitoring
ECG monitoring
1.012026
Short Paper: EarSleeve: Transforming Everyday Earphones into a 12-Lead ECG Sensing Platform · SenSys 2026
Visual content generation and editing › sketch generation
portrait line drawing generation
0.812024
Learning Portrait Drawing with Unsupervised Parts · Int. J. Comput. Vis. 2024
Computer vision › Segmentation and scene understanding
part segmentation
0.212024
Learning Portrait Drawing with Unsupervised Parts · Int. J. Comput. Vis. 2024

Methods — techniques the papers use, named apart from their topics

unsupervised learning · 1.5human-in-the-loop design · 1.0dual-electrode eartip · 1.0
YearPublicationVenuePosition
2026 Short Paper: EarSleeve: Transforming Everyday Earphones into a 12-Lead ECG Sensing Platform
abstract
Achieving multi-lead electrocardiography (ECG) in consumer-grade wearables remains challenging, as most devices provide only a few electrodes and cannot capture spatially diverse cardiac signals. Conventional 12-lead ECG, while clinically standard, requires ten electrodes across the body, confining its use to medical environments. We present EarSleeve, a modular dual-electrode eartip sleeve that transforms off-the-shelf earphones into a 12-lead ECG sensing platform through a human-in-the-loop design. Each sleeve embeds two conductive electrodes and electrically links both sides to form a four-electrode configuration. EarSleeve simultaneously records six limb leads and reconstructs 12-lead–equivalent ECG signals by sequentially contacting standard chest locations. In a 12-user study, EarSleeve captures clear ECG waveforms across all leads and is evaluated against an FDA-cleared reference. Results demonstrate the feasibility of reconstructing 12-lead–equivalent ECG signals using a minimum-electrode configuration under controlled conditions. To our knowledge, EarSleeve is the first system to achieve this with off-the-shelf earphones.
Junxi Xia, Dogaç Eldenk, Yang Liu 0101, Stephen Xia
SenSys2
2025 Incidents During Microservice Decomposition: A Case Study
abstract
Software errors and incidents are inevitable in web-based applications. Scalability challenges, increasing demand, and ongoing code changes can contribute to such failures. As software architectures evolve rapidly, understanding how and why incidents occur is crucial for enhancing system reliability. In this study, we introduce Carbon Health’s software stack, share our microservices journey, and analyze 107 incidents. Based on these incidents, we share insights and lessons learned on microservice decomposition. Finally, we suggest that starting with monolithic modularization as an initial step toward microservice decomposition may help reduce incidents and contribute to building more resilient software.
Dogaç Eldenk, H. Alperen Çetin
EASE1
2024 Learning Portrait Drawing with Unsupervised Parts
Burak Tasdemir, Mustafa Goktan Gudukbay, Dogaç Eldenk, Adil Meric, Aysegul Dundar
Int. J. Comput. Vis.3