Ruohan Zong
Orcid: 0000-0002-6499-3406
According to our database1,
Ruohan Zong
authored at least 28 papers
between 2019 and 2025.
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Bibliography
2025
CoRR, August, 2025
Empowering LLMs to Synthesize AI and Human Intelligence for Explainable Public Health Misinformation Detection on Social Media.
Proceedings of the Nineteenth International AAAI Conference on Web and Social Media, 2025
Component-Based Fairness in Face Attribute Classification with Bayesian Network-informed Meta Learning.
Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025
Learning Behaviors Mediate the Effect of AI-powered Support for Metacognitive Calibration on Learning Outcomes.
Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, 2025
SIDE: Socially Informed Drought Estimation Toward Understanding Societal Impact Dynamics of Environmental Crisis.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
2024
SymLearn: A Symbiotic Crowd-AI Collective Learning Framework to Web-based Healthcare Policy Adherence Assessment.
Proceedings of the ACM on Web Conference 2024, 2024
MMAdapt: A Knowledge-guided Multi-source Multi-class Domain Adaptive Framework for Early Health Misinformation Detection.
Proceedings of the ACM on Web Conference 2024, 2024
Mitigating Demographic Bias of Federated Learning Models via Robust-Fair Domain Smoothing: A Domain-Shifting Approach.
Proceedings of the 44th IEEE International Conference on Distributed Computing Systems, 2024
Tripartite Intelligence: Synergizing Deep Neural Network, Large Language Model, and Human Intelligence for Public Health Misinformation Detection (Archival Full Paper).
Proceedings of the ACM Collective Intelligence Conference, 2024
2023
A crowd-AI dynamic neural network hyperparameter optimization approach for image-driven social sensing applications.
Knowl. Based Syst., October, 2023
ContrastFaux: Sparse Semi-supervised Fauxtography Detection on the Web using Multi-view Contrastive Learning.
Proceedings of the ACM Web Conference 2023, 2023
CollabEquality: A Crowd-AI Collaborative Learning Framework to Address Class-wise Inequality in Web-based Disaster Response.
Proceedings of the ACM Web Conference 2023, 2023
A Crowdsourced Learning Framework to Optimize Cross-Event QoS in AI-powered Social Sensing.
Proceedings of the 20th Annual IEEE International Conference on Sensing, 2023
On Optimizing Model Generality in AI-based Disaster Damage Assessment: A Subjective Logic-driven Crowd-AI Hybrid Learning Approach.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
2022
On Coupling Classification and Super-Resolution in Remote Urban Sensing: An Integrated Deep Learning Approach.
IEEE Trans. Geosci. Remote. Sens., 2022
CollabLearn: An Uncertainty-Aware Crowd-AI Collaboration System for Cultural Heritage Damage Assessment.
IEEE Trans. Comput. Soc. Syst., 2022
CrowdOptim: A Crowd-driven Neural Network Hyperparameter Optimization Approach to AI-based Smart Urban Sensing.
Proc. ACM Hum. Comput. Interact., 2022
CrowdNAS: A Crowd-guided Neural Architecture Searching Approach to Disaster Damage Assessment.
Proc. ACM Hum. Comput. Interact., 2022
An active one-shot learning approach to recognizing land usage from class-wise sparse satellite imagery in smart urban sensing.
Knowl. Based Syst., 2022
On streaming disaster damage assessment in social sensing: A crowd-driven dynamic neural architecture searching approach.
Knowl. Based Syst., 2022
2021
SuperClass: A Deep Duo-Task Learning Approach to Improving QoS in Image-driven Smart Urban Sensing Applications.
Proceedings of the 29th IEEE/ACM International Symposium on Quality of Service, 2021
A Crowd-driven Dynamic Neural Architecture Searching Approach to Quality-aware Streaming Disaster Damage Assessment.
Proceedings of the 29th IEEE/ACM International Symposium on Quality of Service, 2021
StreamCollab: A Streaming Crowd-AI Collaborative System to Smart Urban Infrastructure Monitoring in Social Sensing.
Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, 2021
A deep contrastive learning approach to extremely-sparse disaster damage assessment in social sensing.
Proceedings of the ASONAM '21: International Conference on Advances in Social Networks Analysis and Mining, Virtual Event, The Netherlands, November 8, 2021
2020
TransRes: A Deep Transfer Learning Approach to Migratable Image Super-Resolution in Remote Urban Sensing.
Proceedings of the 17th Annual IEEE International Conference on Sensing, 2020
On Privileged Information Driven Robust Face Verification: A Siamese Convolutional Neural Network Approach.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020
A Hybrid Transfer Learning Approach to Migratable Disaster Assessment in Social Media Sensing.
Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2020
2019
TransLand: An Adversarial Transfer Learning Approach for Migratable Urban Land Usage Classification using Remote Sensing.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019