About Me

Dr. Giselle Zeno is an Artificial Intelligence Researcher at MIT Lincoln Lab. Her research interests lie in the fields of machine learning and data mining, particularly focusing on graphs, temporal processes, and generative models. Her primary work involves developing and analyzing algorithms for relational domains, including social, information, and communication networks, with applications to real-world tasks.

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Interests
  • Artificial Intelligence
  • (Vision) Large Language Models
  • Graph Machine Learning
  • Generative Models
  • Natural Language Processing
  • Data Mining
Education

  • PhD in Computer Science

    Purdue University

  • MSc in Computer Science

    Purdue University

  • BSc in Computer Science

    University of Puerto Rico, Bayamón

Featured Publications
DYANE: DYnamic Attributed Node rolEs Generative Model
Publications
Giselle Zeno, Jennifer Neville (2023). DYANE: DYnamic Attributed Node rolEs Generative Model. In CIKM ‘23.
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Giselle Zeno, Timothy La Fond, Jennifer Neville (2021). DYMOND: DYnamic MOtif-NoDes Network Generative Model. In WWW ‘21.
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Giselle Zeno, Timothy La Fond, Jennifer Neville (2020). Dynamic Network Modeling from Motif-Activity. In WWW ‘20 Companion.
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Giselle Zeno, Jennifer Neville (2016). Investigating the Impact of Graph Structure and Attribute Correlation on Collective Classification Performance. In MLG ‘16.
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Richard P. Lippmann, William M. Campbell, David J. Weller-Fahy, Alyssa C. Mensch, Giselle M. Zeno, Joseph P. Campbell (2016). Finding Malicious Cyber Discussions in Social Media. In MIT Lincoln Laboratory Journal 22, 1.
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