Dongliang Guo

I am currently a PhD student at the University of Virginia, advised by Dr. Sheng Li. Prior to that, I received my bachelor's degree in Software Engineering from University of Eletronic Science and Technology of China (UESTC).

Email: dongliang.guo at virginia.edu

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Research

My research interests are including multi-modal learning, computer vision and Trustworthy learning (explainable AI, fairness).

Education

Ph.D., 2021 - now, University of Virginia

B.Eng., 2016 - 2020, University of Electronic Science and Technology of China

Working Experience

Amazon
Applied Scientist Intern
Seattle, WA
May, 2024 - Aug, 2024
Amazon, Multi-modal fraud detection
Applied Scientist Intern
Seattle, WA
May, 2023 - Aug, 2023

Selected Publication
blind-date Fair attribute completion on graph with missing attributes
Dongliang Guo, Zhixuan Chu, Sheng Li
International Conference on Learning Representations (ICLR) 2023
code

It aims to generate fair node embeddings for some realistic networks with some nodes with missing attributes, by completing the node embeddings and jointly mitigating the feature and topological unfairness.

blind-date Ada-VAD: Domain Adaptable Video Anomaly Detection
Dongliang Guo, Yun Fu, Sheng Li
SIAM International Conference on Data Mining (SDM) 2024
code

It adapts the proposed multi-modal VAD model from scene to scene by data augmentation and mutual information optimization.

blind-date Explainable Anomaly Detection in Images and Videos: A Survey
Yizhou Wang*, Dongliang Guo*, Sheng Li, Octavia Camps, Yun Fu
code

We collect and conclude the existing explainable anomaly detection methods, introduce useful datasets and metrics, and propose some promising future directions.

blind-date A Survey of Trustworthy Representation Learning Across Domains
Ronghang Zhu, Dongliang Guo, Daiqing Qi, Zhixuan Chu, Xiang Yu, Sheng Li
ACM Transactions on Knowledge Discovery from Data (TKDD) 2024

Services

Program Committee Member / Reviewer: ICLR 2024, NeurIPS 2023-24, ICML 2024, CVPR 2024, IEEE CIM, IEEE Big Data, IEEE TKDD, IEEE TNNLS, IEEE TPAMI.

Teaching

CS 5012: Foundations of Computer Science (Spring 2023)