Demo Data from EDBT 2026 / reviewers in the wild / expert
Damilola Alao
dblp:193/3880
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0003-5641-6195ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1
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 · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Services computing and microservices · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks › iot resource management
iot device management |
0.9 | 1 | 2025 | Extending IoT Devices Network Lifetime Using IoT Service Prediction and Recommendation · IEEE Trans. Serv. Comput. 2025 |
Internet of things and sensor networks › wireless sensor network › network lifetime
network lifetime maximization |
0.9 | 1 | 2025 | Extending IoT Devices Network Lifetime Using IoT Service Prediction and Recommendation · IEEE Trans. Serv. Comput. 2025 |
Methods — techniques the papers use, named apart from their topics
service prediction · 1.7recommendation · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Extending IoT Devices Network Lifetime Using IoT Service Prediction and Recommendation
Damilola Alao, Victorine Clotilde Wakam Younang, Amartya Sen |
IEEE Trans. Serv. Comput. | 1 |
| 2014 | Evaluating effectiveness of active learning in computer science using metacognitionabstractActive learning refers to instruction where the learners play an active role in learning and has been found to increase student retention, improve acquisition of higher order thinking and reasoning skills, and improve performance in STEM courses. Two main active learning techniques: student response systems (aka. clickers) and flipped classroom assignments, were incorporated in University of Michigan-Flint computer science (CS) courses. This paper describes how clickers have been incorporated in CS courses and their impact on student learning. There are several ways of evaluating student learning, and tests have traditionally been considered an incomplete and limited reflection of the students' knowledge. In our prior work [11], students' metacognitive knowledge has been used as an effective measure of students' learning. Metacognitive knowledge can be considered to include knowledge of the person, the task, and the available strategies. In this work, we want our students to be aware of their level of understanding of the topics in a course. A student can use this knowledge along with knowledge of the task and available strategies to achieve the cognitive goals. This paper studies how clickers participation impacts student learning as measured by metacognitive knowledge. Murali Mani, Nuha Alkabour, Damilola Alao |
FIE | 3 |