Semantic Scholar is a search engine that leverages AI expertise to help researchers find the most relevant information efficiently. This new service for scientific literature search and discovery focuses on semantics and textual understanding. It utilizes methods from data mining, natural-language processing, and computer vision to create powerful new search and discovery experiences.
•Developed and launched (under experimentation) a trending feed of popular research papers on the homepage of Semantic Scholar
•Improved social media scraper, increasing yield of social content referencing research papers by 510% (Python, AWS RDS & S3)
•Designed and created trending ranking algorithm and integrated it into data pipeline (Scala, Spark, Elasticsearch)
•Implemented the front-end for the trending feed on the homepage of Semantic Scholar (React, HTML/LESS)