Demo Data from VLDB 2026 / reviewers in the wild / expert
Anastasiia Dudkovskaia
dblp:421/2884
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Databases, data management, data science and information retrieval · 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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
epigenetics |
0.9 | 1 | 2025 | ComputAgeBench: Epigenetic Aging Clocks Benchmark · KDD (2) 2025 |
Bioinformatics and computational biology › epigenetics
epigenetic clock |
0.9 | 1 | 2025 | ComputAgeBench: Epigenetic Aging Clocks Benchmark · KDD (2) 2025 |
Information retrieval › evaluation
benchmark |
0.9 | 1 | 2025 | ComputAgeBench: Epigenetic Aging Clocks Benchmark · KDD (2) 2025 |
Methods — techniques the papers use, named apart from their topics
DNA methylation profiling · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | ComputAgeBench: Epigenetic Aging Clocks BenchmarkabstractAge accelerating condition Healthy control p-value Age acceleration Blood data C h r o n o lo g ic a l A g e CpG site Dataset Averaging across cells ... ... ... ... ... CpG N CpG ...Figure 1: ComputAgeBench: the first comprehensive framework for benchmarking various epigenetic aging clock models.For a dataset 𝑋 , obtained by profiling DNA methylation at CpG sites in bulk blood samples, an aging clock model 𝑓 is trained to distinguish healthy individuals from those with pre-defined aging-accelerating conditions. Dmitrii Kriukov, Evgeny Efimov, Ekaterina Kuzmina, Anastasiia Dudkovskaia, Ekaterina Khrameeva, Dmitry V. Dylov |
KDD (2) | 4 |