BZPEERReading, trust and collaboration for researchResearcher profile
Works on literature-scale retrieval and scientific representation learning.
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Postdoctoral Researcher
Published work
We combine publication metadata, author neighborhoods and dataset signals to improve retrieval quality for computational biology teams working across papers, code and experiments.
We curate paper, code and dataset benchmarks for biology-focused language models under provenance and reproducibility constraints.
We trace dataset reuse across scholarly graphs to improve auditability, discovery and replication planning.
This work formalizes a claim workflow that separates platform users, researcher profiles and author entities, improving identity resolution without degrading product usability.
We study open-weight assistants that combine paper summaries, dataset cards and experiment context for biology teams.
We compare dense and sparse retrieval strategies for scholarly search when operators need interpretable reasons and controllable ranking.