Demo Data from EDBT 2026 / reviewers in the wild / expert
Michael He
dblp:244/9144
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 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.
| Software engineering, system software, and programming languages
1 paper |
Empirical software engineering · 77% Software maintenance and evolution · 23% | |
| Human-computer interaction and pervasive computing
1 paper |
Human-AI interaction · 100% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering
developer studies |
0.9 | 1 | 2025 | How Scientists Use Jupyter Notebooks: Goals, Quality Attributes, and Opportunities · ICSE 2025 |
Methods — techniques the papers use, named apart from their topics
qualitative analysis · 1.7observational study · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | How Scientists Use Jupyter Notebooks: Goals, Quality Attributes, and OpportunitiesabstractComputational notebooks are intended to prioritize the needs of scientists, but little is known about how scientists interact with notebooks, what requirements drive scientists' software development processes, or what tactics scientists use to meet their requirements. We conducted an observational study of 20 scientists using Jupyter notebooks for their day-to-day tasks, finding that scientists prioritize different quality attributes depending on their goals. A qualitative analysis of their usage shows (1) a collection of goals scientists pursue with Jupyter notebooks, (2) a set of quality attributes that scientists value when they write software, and (3) tactics that scientists leverage to promote quality. In addition, we identify ways scientists incorporated AI tools into their notebook work. From our observations, we derive design recommendations for improving computational notebooks and future programming systems for scientists. Key opportunities pertain to helping scientists create and manage state, dependencies, and abstractions in their software, enabling more effective reuse of clearly-defined components. Ruanqianqian (Lisa) Huang, Savitha Ravi, Michael He, Boyu Tian, Sorin Lerner, Michael J. Coblenz |
ICSE | 3 |
| 2024 | A License to Prey: Investigating the Impact of Digital Loan App Regulations on Permission Requests and Privacy Policies in the Kenyan MarketabstractThe availability of mobile money in Kenya has positively impacted commerce, financial transaction efforts, and the ability of individuals to receive and save their money. The addition of mobile loan applications provides access to loans without the hassle of going to a physical bank and, in some cases, completing paperwork. While it has its benefits, limited protection of user data has been a cause for concern. User complaints prompted a change in the mobile loan industry, requiring applications to be licensed and banning the use of specific permissions for Android versions of the apps placed in the Google Play Store. We investigate the impact of this change and explore ways to improve regulation by reviewing 30 licensed (n=15) and unlicensed (n=15) Kenyan-targeted digital lender apps. The results suggest that regulation has not yet had a significant impact on digital lender app development and thus encourages government-supported development guidelines and audits. Alexis Morales Flores, Michael He, William Wu, Imani N. S. Munyaka |
ISTAS | 2 |