Sep 23–26, 2019
Gerard de Melo

Gerard de Melo
Assistant Professor, Rutgers University

Website | @gdm3000

Gerard de Melo is an assistant professor of computer science at Rutgers University, where he heads a team of researchers working on big data analytics, natural language processing, and web mining. Gerard’s research projects include UWN/MENTA, one of the largest multilingual knowledge bases, and Lexvo.org, an important hub in the web of data. Previously, he was a faculty member at Tsinghua University, one of China’s most prestigious universities, where he headed the Web Mining and Language Technology Group, and a visiting scholar at UC Berkeley, where he worked in the ICSI AI Group. He serves as an editorial board member for Computational Intelligence, the Journal of Web Semantics, the Springer Language Resources and Evaluation journal, and the Language Science Press TMNLP book series. Gerard has published over 80 papers, with best paper or demo awards at WWW 2011, CIKM 2010, ICGL 2008, and the NAACL 2015 Workshop on Vector Space Modeling, as well as an ACL 2014 best paper honorable mention, a best student paper award nomination at ESWC 2015, and a thesis award for his work on graph algorithms for knowledge modeling. He holds a PhD in computer science from the Max Planck Institute for Informatics.

Sessions

2:55pm3:35pm Wednesday, September 25, 2019
Location: 3B - Expo Hall
Gerard de Melo (Rutgers University)
Gerard de Melo takes a deep dive into the kinds of sentiment and emotion consumers associate with a text. With new data-driven approaches, organizations can better pay attention to what's being said about them in different markets. And you can consider fonts and palettes best suited to convey specific emotions, so organizations can make informed choices when presenting information to consumers. Read more.

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