I am a fourth year PhD student in Information Systems at the Heinz College of Carnegie Mellon University.
I develop scalable machine-learning methods that operate on data with complex structure, such as networks and text. I use these methods to study persuasion in argumentative dialogue.
Email: emaad@cmu.edu
Publications
CORE computer science conference rankings: WWW, KDD = A*.
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- Expanding Taxonomies with Implicit Edge Semantics
- Emaad Manzoor, Dhananjay Shrouty, Rui Li, Jure Leskovec
- WWW 2020 [paper][project website] (coming soon)
- Press: VentureBeat, Pinterest Engineering Blog
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- xStream: Outlier Detection in Feature-Evolving Data Streams
- Emaad Manzoor, Hemank Lamba, Leman Akoglu
- KDD 2018 [paper][project website]
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- Fast Memory-efficient Anomaly Detection in Streaming Heterogenous Graphs
- Emaad Manzoor, Sadegh M. Milajerdi, Leman Akoglu
- KDD 2016 [paper][project website]
Working Papers
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- Focused Concept Miner (FCM): Interpretable Deep Learning for Text Exploration
- Dokyun Lee*, Emaad Manzoor*, Zhaoqi Cheng*
- Under second-round review at Marketing Science [preprint]
Work in Progress
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- Persuasion via Credibility Signals in Argumentative Dialogue
- Emaad Manzoor, George Chen, Dokyun Lee, Michael D. Smith
Patents Filed
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- Expanding Taxonomies with Implicit Edge Semantics
- Emaad Manzoor, Dhananjay Shrouty, Rui Li, Jure Leskovec
- Patent filed October 2019 [Google Patents]
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- Scheduling Broadcasts in a Network of Timelines
- Emaad Ahmed Manzoor, Panos Kalnis
- Patent filed February 2015 [manuscript][Google Patents]
(*equal contribution)