I am a fourth year PhD student in Information Systems at the Heinz College of Carnegie Mellon University. I am advised by Dokyun Lee and George Chen. My research is supported by a McKinsey & Company Ph.D. Fellowship.
Methodologically, I develop scalable machine-learning methods that operate on data with complex structure, such as networks and text. Substantively, I use such methods to examine causal questions pertaining to persuasion and its linguistic determinants.
- On the Persuasive Power of Reputation in Deliberation Online
- Emaad Manzoor, George Chen, Dokyun Lee, Michael D. Smith
- Under review at Management Science (first round)
- Resources: Website, Preprint
- Impact: Best paper (e-business cluster) finalist at INFORMS 2019
- Funding: CMU GuSH Grant / CMU GSA-Provost Grant
- Talks: Stanford/IRiSS Computational Sociology 2020 / NBER PhD Workshop on the Economics of AI / IC2S2 / SCECR / Marketing Science / INFORMS
- Fast Memory-Efficient Anomaly Detection in Streaming Heterogeneous Graphs
- Emaad Manzoor, Sadegh M. Milajerdi, Leman Akoglu
- Knowledge Discovery and Data Mining (KDD), 2016
- Resources: Website, Paper, Code, Data, Slides, Video, Poster
- Impact: Assigned course reading in UIUC’s Advanced Computer Security (Fall ‘20) and Advanced Data Mining (Winter ‘19)
- Funding: DARPA Transparent Computing
Work in Progress
- Identifying Linguistic Biases in Peer-Review
- Emaad Manzoor, Nihar B. Shah
Note on Publication Venues
Computer science research is disseminated primarily via conference proceedings. The WWW and KDD conference series comprise the highest tier of computer science conferences in the data mining subdomain (ranked A* by the CORE conference ranking system).
Academic business research is disseminated primarily via journal publications. Management Science, Marketing Science, Information Systems Research and Management Information Systems Quarterly comprise the highest tier of journals in the information systems and quantitative marketing subdomain (ranked by the Financial Times).