Package Identifier
Built an image-based package identification system that automates item tracking and retrieval through unique identifiers, improving the efficiency and security of shared storage.
Built an image-based package identification system that automates item tracking and retrieval through unique identifiers, improving the efficiency and security of shared storage.
Developed a full-stack mapping application that leverages Dijkstra’s algorithm and geocoding services to optimize multi-stop routes across Brown University’s campus.
Created a web-based visualization platform that parses K9db schemas into Data Ownership Graphs with automatic validation and privacy annotation analysis.
Published in Finding the Frame: An RLC Workshop for Examining Conceptual Frameworks, 2024
Explored how decision-time planning costs influence reinforcement learning performance, highlighting when additional computation is worth the tradeoff.
Recommended citation: Wang, K. A., Xia, J., Chung, S., Wang, J., Piedrahita Velez, F., Wang, H.-J., & Greenwald, A. (2024). "Time is of the Essence: Why Decision-Time Planning Costs Matter." Finding the Frame: An RLC Workshop for Examining Conceptual Frameworks.
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Published in Journal of Statistical Theory and Applications, 2025
BetaExplainer is a probabilistic GNN explanation framework that provides uncertainty estimates for edge importance and improves interpretability on complex graph datasets.
Recommended citation: Sloneker, W., Patel, S., Wang, H.-J., Crawford, L., & Singh, R. (2025). "BetaExplainer: A Probabilistic Method to Explain Graph Neural Networks." Journal of Statistical Theory and Applications, 24, 469–488.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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