Tiehang Duan is an assistant professor and the principle investigator of Deep Brain Lab at Department of Computer Science, College of Computing, Grand Valley State University. He previously worked as a research scientist at Facebook, lecturer in computing with University of Dundee, and held visiting scholar roles at the Mayo Clinic and West Virginia University. He received his Bachelor degree in information and telecommunication engineering from Shanghai Jiao Tong University and Ph.D degree in computer science from SUNY Buffalo. His research interest is on machine learning, brain computer interfaces, medical informatics.

Recent Publications     Full List: Google Scholar

Release the Potential of Memory Buffer in Continual Learning: A Dynamic System Perspective

IEEE Transactions on Pattern Analysis and Machine Intelligence, Oct. Vol. 1 2025

Zhenyi Wang, Li Shen, Tiehang Duan, Yanjun Zhu, Tongliang Liu, Mingchen Gao, and Dacheng Tao

Leveraging Vulnerabilities in Temporal Graph Neural Networks via Strategic High-Impact Assaults

ACM International Conference on Information and Knowledge Management (CIKM), 2025

Dong Hyun Jeon et al.

Teleportation: Defense against Stealing Attacks of Data-Driven Healthcare APIs

IEEE Transactions on Artificial Intelligence, Aug. Vol. 1, 2025

Tiehang Duan et al.

ETT-CKGE: Efficient Task-driven Tokens for Continual Knowledge Graph Embedding

European Conference on Machine Learning (ECML-PKDD), 2025

Lijing Zhu et al.

Contrastive learning with transformer for adverse endpoint prediction in patients on DAPT post-coronary stent implantation

Frontiers in Cardiovascular Medicine, 2025

Fang Li et al.

Online continual decoding of streaming EEG signal with a balanced and informative memory buffer 

Neural Networks, vol. 176, 2024 

Tiehang Duan, Zhenyi Wang, Fang Li, Gianfranco Doretto, Donald Adjeroh, Yiyi Yin, Cui Tao 

Retain and Adapt: Online Sequential EEG Classification with Subject Shift 

IEEE Transactions on Artificial Intelligence, vol. 5, no. 6, 2024 

Tiehang Duan, Zhenyi Wang, Li Shen, Gianfranco Doretto, Donald Adjeroh, Fang Li, Cui Tao 

Training A Secure Model against Data-Free Model Extraction 

European Conference on Computer Vision (ECCV), 2024 

Zhenyi Wang, Li Shen, junfeng guo, Tiehang Duan, Siyu Luan, Tongliang Liu, Mingchen Gao 

RefAI: a GPT-powered retrieval-augmented generative tool for biomedical literature recommendation 

Journal of the American Medical Informatics Association, Vol. 31, 2024 

Yiming Li et al. 

Distributionally Robust Cross Subject EEG Decoding   

European Conference on Artificial Intelligence (ECAI), 2023

Tiehang Duan, Zhenyi Wang, Gianfranco Doretto, Fang Li, Cui Tao, Donald Adjeroh 

Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training

Neural Information Processing Systems（NeurIPS）2023

Zhenyi Wang, Li Shen, Tongliang Liu, Tiehang Duan, Yanjun Zhu, Donglin Zhan, David Doermann, Mingchen Gao

Distributionally Robust Memory Evolution with Generalized Divergence for Continual Learning

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023

Zhenyi Wang, Li Shen, Tiehang Duan, Qiuling Suo, Le Fang, Wei Liu, Mingchen Gao

UNCER: A Framework for Uncertainty Estimation and Reduction in Neural Decoding of EEG Signals

Neurocomputing, 2023

Tiehang Duan, Zhenyi Wang, Sheng Liu, Yiyi Yin, Sargur Srihari

Replay with Stochastic Neural Transformation for Online Continual EEG Classification

IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023

Tiehang Duan, Zhenyi Wang, Gianfranco Doretto, Fang Li, Cui Tao, Donald Adjeroh

MetaMix: Towards Corruption-Robust Continual Learning with Temporally Self-Adaptive Data Transformation

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023

Zhenyi Wang, Li Shen, Donglin Zhan, Qiuling Suo, Yanjun Zhu, Tiehang Duan, Mingchen Gao

Learning To Learn and Remember Super Long Multi-Domain Task Sequence

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022

Zhenyi Wang, Li Shen, Tiehang Duan, Donglin Zhan, Le Fang, Mingchen Gao

Improving Task-free Continual Learning by Distributionally Robust Memory Evolution

International Conference on Machine Learning(ICML), 2022

Zhenyi Wang, Li Shen, Le Fang, Qiuling Suo, Tiehang Duan, Mingchen Gao

Meta-Learning with Less Forgetting on Large-Scale Non-Stationary Task Distributions

European Conference on Computer Vision (ECCV), 2022

Zhenyi Wang, Li Shen, Le Fang, Qiuling Suo, Donglin Zhan, Tiehang Duan, Mingchen Gao

Ultra Efficient Transfer Learning with Meta Update for Cross Subject EEG Classification

Canadian Conference on Artificial Intelligence, 2021

Duan, T., Chauhan, M., Shaikh, M. A., Chu, J., & Srihari, S. N

Meta Learning on a Sequence of Imbalanced Domains with Difficulty Awareness

International Conference on Computer Vision (ICCV), 2021 

Z. Wang, T. Duan, L. Fang, Q. Suo and M. Gao

Meta Learn on Constrained Transfer Learning for Low Resource Cross Subject EEG Classification

IEEE Access 2020

Tiehang Duan, Mohammad Abuzar Shaikh, Mihir Chauhan, Jun Chu, Rohini K. Srihari, Archita Pathak, Sargur N. Srihari

Attention based Writer Independent Verification

International Conference on Frontiers in Handwriting Recognition (ICFHR), 2020

M. A. Shaikh, T. Duan, M. Chauhan and S. N. Srihari

Parallel Clustering of Single Cell Transcriptomic Data with Split Merge Sampling

Bioinformatics Oxford, 2019

Tiehang Duan, Jose P. Pinto, Xiaohui Xie

Sequential Embedding Induced Nonparametric Text Clustering

Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2019

Tiehang Duan, Qi Lou, Sargur N. Srihari, Xiaohui Xie

Teaching

Introduction to Artificial Intelligence, Fall 2025/Winter 2026/Fall 2026

Object Oriented Analysis and Design, Spring 2025

Data Structures and Algorithms (with Java), Spring 2025

Services

Journal Reviewer:

  IEEE Transactions on Medical Imaging, IEEE Transactions on Affective Computing, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Cybernetics, Pattern Recognition, Machine Learning, Neural Networks, npj Digital Medicine, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Computational Biology and Bioinformatics, Information Sciences, Advanced Engineering Informatics, Knowledge-based Systems, Information Fusion, Neural Computing and Applications, Expert Systems with Applications, Artificial Intelligence in Medicine

Conference Committee:

   International Conference on Machine Learning (ICML), Computer Vision and Pattern Recognition (CVPR), Neural Information Processing Systems (NeurIPS), International Conference on Computer Vision (ICCV), European Conference on Computer Vision (ECCV), International Conference on Learning Representations (ICLR), AAAI Conference on Artificial Intelligence (AAAI), ACM International Conference on Knowledge Discovery and Data Mining (KDD), International Conference on Artificial Intelligence and Statistics (AISTATS)