I am an associate professor at School of Computing and Information, University of Pittsburgh. I am interested in studying social and political networks, as well as computational and visualization methods for understanding network data. My work has focused on large-scale community dynamics, high-dimensional (rich-context) social information summarization and representation. I have been using massive social media data and anonymized cellphone records to understand the collective responses with respect to political events and under exogenous shocks such as emergencies. I lead the PITT Computational Social Dynamics Lab (PICSO LAB).
I am a computer scientist by training, and a computational social scientist working on questions like: "how would a society be informed?" "how do people share information, ideas and opinions in various contexts?" These questions have led me to explore analytical and computational techniques for mining heterogeneous, multi-relational, and semistructured data that can advance our understanding about structures in networked societies. I was a postdoctoral research fellow at the Institute for Quantitative Social Science, Harvard University and College of Computer and Information Science, Northeastern University.
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08/2019
I'm serving as a track chair of The Web Conference 2020 (formerly known as WWW): Web and Society Track. We welcome submissions in all areas that concern the interaction of Web and Societies; topics include Computational Social Science and more.
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08/2019
Paper accepted to appear in Applied Network Science: "Learning Embeddings for Multiplex Networks Using Triplet Loss."
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07/2019
Two papers accepted to appear at FairSight: Visual Analytics for Fairness in Decision Making" and "FacIt: Factorizing Tensors into Interpretable and Scrutinizable Patterns."
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06/2019
I'm pleased to introduce the Special Issue on AI for Disaster Management and Resilience for the IEEE Intelligent Systems.
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06/2019
Paper accepted to appear in ECML/PKDD 2019: "CASTNet: Community-Attentive Spatio-Temporal Networks for Opioid Overdose Forecasting."
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02/2019
Paper accepted to appear at EPJ Data Science Journal: "Activism via Attention: Interpretable Spatiotemporal Learning to Forecast Protest Activities."
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01/2019
Paper accepted to appear in WWW 2019: "Iterative Discriminant Tensor Factorization for Behavior Comparison in Massive Open Online Courses."
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11/2018
Grateful to receive gift fund from Adobe Research.
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10/2018
Honored to be included in the SAGE Ocean's list of "39 women doing amazing research in computational social science"
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09/2018
I am co-chairing 2019 International AAAI Conference on Weblogs and Social Media (ICWSM 2019). It will be held at Munich, Germany, June 11-14. We look forward to your participation!
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09/2018
I am co-chairing 2019 International AAAI Conference on Weblogs and Social Media (ICWSM 2019). It will be held at Munich, Germany, June 11-14. We look forward to your participation!
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09/2018
Call for papers: AI for Disaster Management and Resilience (Special Issue, IEEE Intelligent Systems). Look forward to your contribution!
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06/2018
Honored to join the PLOS ONE Editorial Board to serve as an Academic Editor in Complex Networks.
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06/2018
Selected for award on the DARPA Understanding Group Biases (UGB) program. This award aims to develop and advance reproducible approach in revealing biases of different groups or cultures by leveraging big data and scalable, interpretable methods. New postdocs and research assistant positions will be available soon!
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04/2018
Paper accepted to appear in IJCAI 2018: "Deep into Hypersphere: Robust and Unsupervised Anomaly Discovery in Dynamic Networks."
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03/2018
I am co-organizing International Workshop on Event Analytics using Social Media Data (EASM 2018), co-located with ICWSM 2018, at Stanford, CA, USA. We look forward to your participation!
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03/2018
Paper accepted to appear in Data Mining and Knowledge Discovery (DAMI): "Anomaly Detection in Spatial-Temporal Data via Regularized Non-Negative Tensor Analysis."
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02/2018
Paper accepted to appear in ACM TKDD: "Event Analytics via Discriminant Tensor Factorization."
» More on earlier updates.
