Daniel E. Acuna’s portfolio
Peer review suffers a number of biases that go against its goals. In this project, we develop software to match reviewers to manuscript solely based on the authors’ and reviewers’ expertise. The system can also process the received scores for each manuscript and correct systematic harshness or softness of a reviewer.
This visualization won the 2nd place in the Data Visualization Challenge at Northwestern University. We analyzed all articles in the PubMed Open Access Subset to understand their expertise, how they collaborate, and how they get funded.2nd place Data Visualization Challenge
Automated poster scheduler for large conferences
Discovering new research topics is one of the major goals while attending large conferences. However, this is difficult because a human curated understanding of the topics being presented is scarce. In Scholarfy, we created a data science-based website that can learn the preferences of attendees and automatically build poster schedules that maximally match the attendees’ interests.
Effect of suggested reviewers on manuscript acceptance
In this research, we examined the peer review outcomes thanks to a unique collaboration between my lab and the largest journal in the world, PLoS ONE. Specifically, we examined the effect of suggested reviewers in review timing, score, acceptance rates and quality. Please email me if you want to read our manuscript.