Dongping Zhang


I am a Ph.D. candidate in Technology and Social Behavior, a joint Ph.D. program in Computer Science and Communication at Northwestern. I work with Prof. Jessica Hullman at Midwest Uncertainty Collective (MU Collective).

My research investigates effective means to communicate uncertainty in model predictions related to social networks and strategic settings. Specifically, how can we better understand probabilistic graphs where the occurrences of relational events generated from the data or predicted by graph models are subject to uncertainty, and how to communicate model predictions to help people make more informed strategic decisions in networks where an agent's ability to best respond to predictions depend on the agent's ability to anticipate how other agents will act based on their understandings. I tackle problems using a data-driven approach, modeling network events, designing effective information displays, and conducting large-scale online experiments.

Before starting my doctoral study at Northwestern, I received a B.A. in Economics and a B.A. in Statistics from UC Berkeley and later an M.A. in Computational Social Science from UChicago. You can find my CV here.


Peer-reviewed Conference Journal Paper

Conference Presentation

  • Antone, B., Zhang, D., Li, H., Zhang, T., Kudaravalli, A., Xu, Y., DeChurch, L.A., Leonardi, P.M., & Contractor, N.S. (2019, October). Predictive Extensions to ERGMs and Applications in Real-time Monitoring of Organizational Social Networks. Presented at the Seventh International Workshop on Social Network Analysis (ARS'19), Vietre sul Mare, Italy.


  • Zhang, D., & Wilensky, U. (2018). NetLogo Taxi Cabs Model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

Research Experience

Compass Lexecon

Economic Research Assistant
Summer 2017


Economic Research Assistant
Summer 2016



Programming Languages
  • Social Network Analysis
  • Agent-based Simulation
  • Geospatial Analysis
  • Bayesian Statistics & Modeling
  • Data and Uncertainty Visualizations
  • Web-based Prototyping
  • Survey & Experiment Design
  • Big Data
  • Machine Learning

Fellowship & Scholarship

Segal Design Institute Research Cluster Fellowship

Northwestern University

Selected as an interdisciplinary design research fellow to advance knowledge of design innovation.


Regents' and Chancellor's Scholarship

University of California, Berkeley

The most prestigious scholarship awarded to the top 2% of undergraduates.


Berkeley Club of Hong Kong Undergraduate Scholarship

University of California, Berkeley

Scholarship awarded based on academic merit and extra-curricular achievements.



Northwestern University
Department of Computer Science
Mudd Hall 3538
2233 Tech Drive
Evanston, IL 60208