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Fengchun Qiao
I am a Ph.D. student in Computer & Information Sciences at University of Delaware, supervised by Prof. Xi Peng.
My research focuses on trustworthy machine learning, with a particular emphasis on Out-of-Distribution (OOD) generalization.
I develop principled optimization methods to ensure AI systems perform reliably in unseen environments—for example, enabling a flood predictor trained on historical U.S. flood events (2000–2020) to handle an unseen catastrophe like Hurricane Ida in 2021.
Email /
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LinkedIn /
GitHub /
Google Scholar
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SeafloorAI: A Large-scale Vision-Language Dataset for Seafloor Geological Survey
Kien Nguyen, Fengchun Qiao, Arthur Trembanis and Xi Peng
Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2024.
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Ensemble Pruning for Out-of-distribution Generalization
Fengchun Qiao and Xi Peng
International Conference on Machine Learning (ICML), 2024.
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Adaptive Cascading Network for Continual Test-Time Adaptation
Kien Nguyen*, Fengchun Qiao* and Xi Peng (* denotes equal contribution)
Conference on Information and Knowledge Management (CIKM), 2024.
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Calibrating Probabilistic Embeddings for Cross-Modal Retrieval
Fengchun Qiao and Xi Peng
International Conference on Computational Data and Social Networks (CSoNet), 2024.
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Are Data-driven Explanations Robust against Out-of-distribution Data?
Tang Li, Fengchun Qiao, Mengmeng Ma and Xi Peng
In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
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Topology-aware Robust Optimization for Out-of-Distribution Generalization
Fengchun Qiao and Xi Peng
International Conference on Learning Representations (ICLR), 2023.
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Graph-Relational Distributionally Robust Optimization
Fengchun Qiao and Xi Peng
NeurIPS Workshop on Distribution Shift, 2022.
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Out-of-Domain Generalization from a Single Source: An Uncertainty Quantification Approach
Xi Peng, Fengchun Qiao, and Long Zhao
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
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Uncertainty-guided Model Generalization to Unseen Domains
Fengchun Qiao and Xi Peng
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
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Learning to Learn Single Domain Generalization
Fengchun Qiao, Long Zhao, and Xi Peng
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
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Geometry-Contrastive GAN for Facial ExpressionTransfer
Fengchun Qiao, Naiming Yao, Zirui Jiao, Zhihao Li, Hui Chen, and Hongan Wang
arXiv,2018.
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Emotional facial expression transfer from a single image via generative adversarial nets
Fengchun Qiao, Naiming Yao, Zirui Jiao, Zhihao Li, Hui Chen, and Hongan Wang.
The 31st International Conference on Computer Animation and Social Agents (CASA), 2018.
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An Ensemble of VGG Networks for Video-Based Facial Expression Recognition
Zirui Jiao, Fengchun Qiao, Naiming Yao, Zhihao Li, Hui Chen, and Hongan Wang.
The First Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia), 2018.
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- Applied Scientist Intern, Amazon Web Services AI Lab
Time: Summer 2021. Mentor: Dr. Gukyeong Kwon and Dr. Zhiguo Wang
Topics: Probabilistic Models for Cross-Modal Retrieval.
- Research Assistant, Institute of Software, Chinese Academy of Sciences
Time: 2016 - 2019. Advisor: Prof. Hui Chen
Topics: GAN-based Facial Expression Synthesis.
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- Frank A. Pehrson Award for Outstanding Computer Science Research, University of Delaware, 2024
- Graduate Student Travel Award, University of Delaware, 2023
- NeurIPS 2022 Top Reviewer Award, 2022
- Outstanding Graduate Student Award, University of Delaware, 2022
- Distinguished Graduate Student Award, University of Delaware, 2021
- National Scholarship for Graduate Students, 2018
- CIKM AnalytiCup 2017 (Ranking: 4/1395), 2017
- KDD CUP 2017 (Ranking: 16/3582), 2017
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- Spring 2025: Instructor for CISC 484 (Machine Learning)
- Summer 2024: Instructor for CISC 484/684 (Machine Learning)
- Fall 2021: Teaching Assistant for CISC 484 (Machine Learning), CISC 621 (Algorithm Design and Analysis).
- Spring 2021: Teaching Assistant for CISC 484/684 (Machine Learning).
- Fall 2020: TA for CISC 481 (Artificial Intelligence), CISC 482 (Introduction to Human-Computer Interaction).
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- Conference reviewer/Program committee: ICML 2022-2025, ICLR 2024-2025, NeurIPS 2022-2025, AISTATS 2025, AAAI 2023-2025, IJCAI 2024-2025, CVPR 2024-2025, ICCV 2023, ECCV 2024, BMVC 2024, CoLLAs 2023-2024
- Journal reviewer: TPAMI/TNNLS/TIP/TMM/CVIU/TCSVT/TIM
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