Individual Files
Presentations
Day One
- Opening Remarks – Bob Bond
- Keynote – Social Network Interventions – Nicholas A. Christakis
- Discovering Relationships in Text: NLP informs SNA – James Keiser
- Information-Theoretic Limits of Network Inference Problems – Galen Reeves
- Understanding Regularized Spectral Clustering via Graph Conductance – Karl Rohe
- Finding the Way for Graph Matching – Daniel Sussman
- Diffusion Games – Evan Sadler
- Stochastic Seeding Strategies in Networks – Dean Eckles
- A Graph Theoretic Approach to Causal Inference under General Interference – Panos Toulis
Day Two
- Keynote – Theory and Practice in Cybersecurity Operations – Josiah Dykstra
- SECURE: Science and Engineering for Cybersecurity by Uncertainty Quantification and Rigorous Experimentation – Ali Pinar
- How Much Structure Exists in my Transactional Data? – Richard Darling
- Uncovering Human Trafficing Networks through Text Analysis – Olga Simek
- Active Graph Mining Algorithmic Problems on Team Formationand Engineering – Evimaria Terzi
- Inference for Network Regressions with Exchangeable Errors – Bailey Fosdick
- Simplicial Closure and Higher-Order Link Prediction – Austin Benson
Posters 2019
- Crawling the Community Structure of Multiplex Networks – Ricky Laishram
- Detecting Self-Propagating Attacks in Cyber Networks – Timothy Sakharov, Tina Eliassi-Rad
- Latent Community Adaptive Network Regression – Heather Mathews, Alexander Volfovsky
- Polarization on Social Media – Kiran Garimella
- The Geometry of Community Detection – Vaishakhi Mayya, Alexander Volfovsky
- Applying Interdiction Optimization to Cybersecurity Problems in Energy Infrastructure – Bill Hart
- Causal Impact Estimation of Influence Operations on Social Networks – Steven Smith
- Evaluating Attacks on Vertex Classification – Benjamin A. Miller, Mustafa Çamurcu, Tina Eliassi-Rad
- GLEE: Geometric Laplacian Eigenmap Embedding – Leo Torres, Tina Eliassi-Rad
- Mining Tours and Paths in Activity Networks – Sofia Nikolakaki
- Observational Causal Inference Using Network Information – Yan Leng
- Representation Learning of Random Graphs with Deep autocoders – Peter Morales, Rajmonda Caceres
- Scalable Graph Matching – Lin Li