Bang An

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Hi, I'm Bang!

I am a fourth-year PhD student in Computer Science at University of Maryland. I'm very fortunate to be advised by Prof. Furong Huang and work on Machine Learning as a member of UMIACS. Before coming to UMD, I was a research staff member at IBM Research China. I received my bachelor’s degree from Northeastern University (China) and my master’s degree from Tsinghua University.

My research focuses on Reliable Machine Learning. I am particularly interested in understanding and improving the algorithmic fairness, generalization, robustness, and interpretability of deep learning models. I believe that reliable machine learning is a critical element in enabling AI to better serve and support humanity.

Preprints
Benchmarking the Robustness of Image Watermarks
Bang An*, Mucong Ding*, Tahseen Rabbani*, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang
[website] [code]
AutoDAN: Automatic and Interpretable Adversarial Attacks on Large Language Models
Sicheng Zhu, Ruiyi Zhang, Bang An, Gang Wu, Joe Barrow, Zichao Wang, Furong Huang, Ani Nenkova, Tong Sun
[website] [code]
On the Possibilities of AI-Generated Text Detection
Souradip Chakraborty*, Amrit Singh Bedi*, Sicheng Zhu, Bang An, Dinesh Manocha, Furong Huang
Selected Publications
More Context, Less Distraction: Zero-shot Visual Classification by Inferring and Conditioning on Contextual Attributes
Bang An*, Sicheng Zhu*, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang
ICLR 2024.
[code]
SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation
Mucong Ding, Bang An, Yuancheng Xu, Anirudh Satheesh, Furong Huang
ICLR 2024.
C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder
Xiaoyu Liu, Jiaxin Yuan, Bang An, Yuancheng Xu, Yifan Yang, Furong Huang .
NeurIPS 2023.
Learning Unforeseen Robustness from Out-of-distribution Data Using Equivariant Domain Translator
Sicheng Zhu, Bang An, Furong Huang, Sanghyun Hong.
ICML 2023.
[code]
Transferring Fairness under Distribution Shifts via Fair Consistency Regularization
Bang An, Zora Che, Mucong Ding, Furong Huang.
NeurIPS 2022.
[code]
Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity
Mucong Ding, Tahseen Rabbani, Bang An, Evan Z Wang, Furong Huang.
NeurIPS 2022.
[Code]
Understanding the Generalization Benefit of Model Invariance from a Data Perspective
Sicheng Zhu*, Bang An*, Furong Huang.
NeurIPS 2021.
[Code]
Adaptive Transfer Learning on Graph Neural Networks
Xueting Han, Zhenhuan Huang, Bang An, Jing Bai.
KDD 2021.
[Code]
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference
Bang An, Jie Lyu, Zhenyi Wang, Chunyuan Li, Changwei Hu, Fei Tan, Ruiyi Zhang, Yifan Hu and Changyou Chen
EMNLP 2020.
[Code]
Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints
Zhenyi Wang, Xiaoyang Wang, Bang An, Dong Yu, Changyou Chen
ACL 2020.
Workshops
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint
Paiheng Xu*, Yuhang Zhou*, Bang An, Wei Ai, Furong Huang
Trustworthy and Socially Responsible Machine Learning (NeurIPS Workshop), 2022.
Awards
  • Outstanding Graduate Assistant Award of UMD (top 2%), 2023.
  • NeurIPS 2022 Travel Award
Services
  • Reviewer: ICML 2022, NeurIPS 2022, ICML 2023, NeurIPS 2023, ICLR 2024, NAACL 2024