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07/17/2023
Disentangling Node Attributes from Graph Topology for Improved Generalizability in Link Prediction
Link prediction is a crucial task in graph machine learning with diverse...
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06/23/2023
Social AI and the Challenges of the Human-AI Ecosystem
The rise of large-scale socio-technical systems in which humans interact...
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06/05/2023
Using Sequences of Life-events to Predict Human Lives
Over the past decade, machine learning has revolutionized computers' abi...
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03/16/2023
Optimal Intervention on Weighted Networks via Edge Centrality
Suppose there is a spreading process such as an infectious disease propa...
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12/17/2022
Characterizing collective physical distancing in the U.S. during the first nine months of the COVID-19 pandemic
The COVID-19 pandemic offers an unprecedented natural experiment providi...
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10/12/2022
BiaScope: Visual Unfairness Diagnosis for Graph Embeddings
The issue of bias (i.e., systematic unfairness) in machine learning mode...
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08/05/2022
Modeling Self-Propagating Malware with Epidemiological Models
Self-propagating malware (SPM) has recently resulted in large financial ...
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06/27/2022
Cyber Network Resilience against Self-Propagating Malware Attacks
Self-propagating malware (SPM) has led to huge financial losses, major d...
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05/23/2022
CELEST: Federated Learning for Globally Coordinated Threat Detection
The cyber-threat landscape has evolved tremendously in recent years, wit...
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12/27/2021
PORTFILER: Port-Level Network Profiling for Self-Propagating Malware Detection
Recent self-propagating malware (SPM) campaigns compromised hundred of t...
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12/25/2021
AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands
Identifying novel drug-target interactions (DTI) is a critical and rate ...
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04/23/2021
Collaborative Information Sharing for ML-Based Threat Detection
Recently, coordinated attack campaigns started to become more widespread...
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03/16/2021
RAWLSNET: Altering Bayesian Networks to Encode Rawlsian Fair Equality of Opportunity
We present RAWLSNET, a system for altering Bayesian Network (BN) models ...
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08/12/2020
Optimizing Graph Structure for Targeted Diffusion
The problem of diffusion control on networks has been extensively studie...
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06/04/2020
The why, how, and when of representations for complex systems
Complex systems thinking is applied to a wide variety of domains, from n...
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03/12/2020
Topological Effects on Attacks Against Vertex Classification
Vertex classification is vulnerable to perturbations of both graph topol...
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01/09/2020
Understanding the Limitations of Network Online Learning
Studies of networked phenomena, such as interactions in online social me...
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09/16/2019
Deep Reinforcement Learning for Task-driven Discovery of Incomplete Networks
Complex networks are often either too large for full exploration, partia...
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08/13/2019
L2P: An Algorithm for Estimating Heavy-tailed Outcomes
Many real-world prediction tasks have outcome (a.k.a. target or response...
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07/10/2019
On Designing Machine Learning Models for Malicious Network Traffic Classification
Machine learning (ML) started to become widely deployed in cyber securit...
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05/23/2019
Geometric Laplacian Eigenmap Embedding
Graph embedding seeks to build a low-dimensional representation of a gra...
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09/09/2016