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publications
Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks
Published in AAAI Conf on Artificial Intelligence, Special Track on Social Impact, 2024
This work introduces a novel graph neural networks (GNNs)-based method to predict stream water temperature and reduce model bias across locations of different income and education levels.
Recommended citation: Erhu He, Declan Kutscher, Yiqun Xie, Jacob Zwart, Zhe Jiang, Huaxiu Yao, Xiaowei Jia. (2024). "Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks." AAAI Conf on Artificial Intelligence, Special Track on Social Impact..
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talks
Talk 1 on Relevant Topic in Your Field
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teaching
CS 0007 INTRODUCTION TO COMPUTER PROGRAMMING (FALL ‘22)
Undergraduate course, University of Pittsburgh, School of Computing and Information, 2022
Role: Undergraduate Teaching Assistant
CMPINF 0401 INTERMEDIATE PROGRAMMING (Spring ‘23)
Undergraduate course, University of Pittsburgh, School of Computing and Information, 2023
Role: Undergraduate Teaching Assistant
CS 0011 INTRODUCTION TO COMPUTING FOR SCIENTISTS (FALL ‘23)
Undergraduate course, University of Pittsburgh, School of Computing and Information, 2023
Role: Undergraduate Teaching Assistant