Giselle Zeno

Graduate Student

Graduate Research Assistant

Joined department: Fall 2014

Education

Bachelor of Science, University of Puerto Rico at Bayamon, Computer Science (2010)

Master of Science, Purdue University, Computer Science (2020)

I am a PhD candidate in Computer Science at Purdue University. My research interests are in the areas of data mining and machine learning. In particular, I have worked on collective inference and dynamic graph generative models.

Selected Publications

Richard P. Lippmann, William M. Campbell, David J. Weller-Fahy, Alyssa C. Mensch, Giselle M. Zeno, and Joseph P. Campbell. 2016. Finding Malicious Cyber Discussions in Social Media. MIT Lincoln Laboratory Journal 22, 1, (2016), 46-49.

Giselle Zeno and Jennifer Neville. 2016. Investigating the Impact of Graph Structure and Attribute Correlation on Collective Classification Performance. In Proceedings of the 12th International Workshop on Mining and Learning with Graphs (MLG), August 14, 2016, San Francisco, CA, USA.

Giselle Zeno, Timothy La Fond, and Jennifer Neville. 2020. Dynamic Network Modeling from Motif-Activity. In Companion Proceedings of the Web Conference 2020 (WWW '20 Companion), April 20-24, 2020, Taipei, Taiwan.

Giselle Zeno, Timothy La Fond, and Jennifer Neville. 2021. DYMOND: DYnamic MOtif-NoDes Network Generative Model. In Proceedings of the Web Conference 2021 (WWW '21), April 19-23, 2021, Ljubljana, Slovenia.

Last Updated: Dec 4, 2020 2:03 PM