Shuvom Sadhuka — accepted AI-conference papers

2026

Urban Incident Prediction with Graph Neural Networks: Integrating Government Ratings and Crowdsourced Reports

Sidhika Balachandar, Shuvom Sadhuka, Bonnie Berger, Emma Pierson, Nikhil Garg

AAAI 2026technical

Graph neural networks (GNNs) are widely used in urban spatiotemporal forecasting, e.g., predicting infrastructure problems. In this setting, government officials aim to identify in which neighborhoods incidents like potholes or rodents occur. The true state of incidents is observed via government in

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2025

Evaluating multiple models using labeled and unlabeled data

Divya M Shanmugam, Shuvom Sadhuka, Manish Raghavan, John Guttag, Bonnie Berger, Emma Pierson

NeurIPS 2025poster

It is difficult to evaluate machine learning classifiers without large labeled datasets, which are often unavailable. In contrast, unlabeled data is plentiful, but not easily used for evaluation. Here, we introduce Semi-Supervised Model Evaluation (SSME), a method that uses both labeled and unlabel…

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