Demo Data from EDBT 2026 / reviewers in the wild / expert
Brad Solomon
dblp:198/4917
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2026
0000-0002-4293-1677ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 since 2021Applied, 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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › sequence analysis › sequence similarity search
sequence database search |
0.3 | 1 | 2017 | Improved Search of Large Transcriptomic Sequencing Databases Using Split Sequence Bloom Trees · RECOMB 2017 |
Bioinformatics and computational biology
transcriptomics |
0.3 | 1 | 2017 | Improved Search of Large Transcriptomic Sequencing Databases Using Split Sequence Bloom Trees · RECOMB 2017 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Measuring Students' Perceptions of an Autograded Scaffolding Tool for Students Performing at All Levels in an Algorithms ClassabstractAlgorithms courses are a foundational part of an undergraduate computer science degree that require abstract thinking and creativity and are known to be challenging for many students. Recently researchers have been developing auto-graded tools to scaffold students through the problem-solving process. We examine student's perceptions of such a tool in a required upper-division Algorithms course at a R1 University. The goal of the tool is to improve student experience in three ways: (1) help students break down the problem-solving process into clear steps; (2) increase students' self-efficacy by raising their confidence and understanding of the material; (3) have low ''cost'', by being easy to use, enjoyable, and a good use of students' time. The tool itself is designed to provide these benefits to students at every level of mastery through instantaneous feedback over increasingly challenging problems. It is designed as an addition to and not complete replacement of the written homework in the course. Based on a survey of almost 1000 students across four semesters, each with a different instructor, we examine whether student feedback is favorable over all four offerings, and for groups of students with different course outcomes. Using qualitative and quantitative methods, we found that across each of the four semesters and across letter grades A, B, C, and D students favored the tool as compared to written homework. Yael Gertner, Brad Solomon, Hongxuan Chen 0001, Eliot W. Robson, Carl Evans, Jeff Erickson 0001 |
SIGCSE (1) | 2 |
| 2017 | Improved Search of Large Transcriptomic Sequencing Databases Using Split Sequence Bloom Trees
Brad Solomon, Carl Kingsford |
RECOMB | 1 |