- Fang Chen and Jianlong Zhou. Humanity Driven AI: Productivity, Well-being,
Sustainability and Partnership. Springer, 2022. ISBN: 978-3-030-72187-9. (Springer
Link)
- Jianlong Zhou and Fang Chen. Human and Machine Learning: Visible, Explainable,
Trustworthy and Transparent. Springer, 2018. ISBN: 978-3-319-90403-0. (Springer Link)
- Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji, and Dan
Conway. Robust Multimodal Cognitive Load Measurement. Springer, 2016. ISBN:
978-3-319-31698-7. (Springer Link)
- Jianlong Zhou, Heimo Müller, Andreas Holzinger, and Fang Chen. "Ethical ChatGPT:
Concerns, Challenges, and Commandments", Electronics 13, no. 17: 3417, 2024.
- Simon Knight, Isabella Bowdler, Heather Ford, and Jianlong Zhou. "A visual scoping
review of how knowledge graphs and search engine results page designs represent
uncertainty and disagreement." Information and Learning Sciences 2024.
- B. Zheng, J. Zhou, C. Liu, Y. Li, and F. Chen, “Explaining Imitation Learning
Through Frames”, IEEE Intelligent Systems, 2024.
- Boyuan Zheng, Sunny Verma, Jianlong Zhou, Ivor Tsang, and Fang Chen, “Imitation
Learning: Progress, Taxonomies and Challenges", IEEE Transactions on Neural
Networks and Learning Systems, vol. 35, issue 5, pages 6322-6337, 2024.
- E. Wright, J. Zhou, D. Lindsay, L. Przhedetsky, F. Chen, and A. Davison, “SMEs and
Explainable AI: Australian Case Studies”, Computers & Law: Journal for the
Australian and New Zealand Societies of Computers and the Law, vol. 94, Article
4, 2022.
- Rongcheng Wu, Mingzhe Wang, Zhidong Li, Jianlong Zhou, Fang Chen, Xuan Wang and
Changming Sun, “Few-shot Stereo Matching with High Domain Adaptability Based on
Adaptive Recursive Network”, International Journal of Computer Vision, 2023.
- J. Zhou, S. Sheppard-Law, C. Xiao, J. Smith, A. Lamb, C. Axisa, and F. Chen,
“Leveraging Twitter Data to Understand Nurses' Emotion Dynamics During the
COVID-19 Pandemic”, Health Information Science and Systems, Vol. 11, no. 28,
page 1-14, 2023.
- Alessa Angerschmid, Jianlong Zhou, Kevin Theuermann, Fang Chen, and Andreas
Holzinger, "Fairness and Explanation in AI-Informed Decision Making", Machine
Learning and Knowledge Extraction. Vol 4, no. 2: 556-579, 2022. (Top 1 cited
paper in 2022 in MAKE)
- J. Zhou, A. H. Gandomi, F. Chen, and A. Holzinger, "Evaluating the Quality of
Machine Learning Explanations: A Survey on Methods and Metrics", Electronics,
Electronics, 10(5), pp. 1-19, article no. 593, 2021. (The Best Paper Award)
- Jianlong Zhou, H. Zogan, S. Yang, S. Jmeel, G. Xu, and F. Chen, “Detecting Community
Depression Dynamics Due to COVID-19 Pandemic in Australia”, IEEE Transactions on
Computational Social Systems, 8(4), pp. 958-967, 2021.
- Jianlong Zhou , Syed Z. Arshad, Xiuying Wang, Zhidong Li,
David Feng, and Fang Chen. End-User Development for Interactive Data
Analytics: Uncertainty, Correlation and User Confidence. IEEE
Transactions on Affective Computing, vol. 9, no. 3, pp. 383-395, 2018. (PDF)
- Sharon Oviatt, Kevin Hang, Jianlong Zhou, Kun Yu, and Fang Chen. Dynamic
Handwriting Signal Features Predict Domain Expertise. ACM Transactions on
Interactive Intelligent Systems, vol. 8, No. 3, article no. 18, 2018. (PDF)
- J. Zhou and F. Chen. DecisionMind: Revealing Human
Cognition States in Data Analytics-Driven Decision Making with a
Multimodal Interface. Journal on Multimodal User Interfaces, (Springer),
vol. 12, no. 2, pp.67-76, 2018. (PDF)
- Jianlong Zhou , Jinjun Sun, Yang Wang, and Fang Chen.
Wrapping Practical Problems into a Machine Learning Framework —Using
Water Pipe Failure Prediction as a Case Study.
International Journal of Intelligent Systems Technologies and
Applications, vol. 16, No. 3, pp.191-207, 2017. (PDF)
- Jianlong Zhou , M. Asif Khawaja, Zhidong Li, Jinjun Sun, Yang Wang, and Fang Chen.
Making Machine
Learning
Useable by Revealing Internal States Update — A Transparent Approach.
International Journal of
Computational Science and Engineering, Vo.13, No. 4, pp.378-389, 2016. (PDF)
- Yoshihiro Uemura, Yusuke Kajiwara, Jianlong Zhou , Fang
Chen, and Hiromitsu Shimakawa. Estimating Human Physical States
from Chronological Gait Features Acquired with RFID Technology.
Sensors & Transducers, vol. 194, no. 11, pp.76-83, 2015.
(PDF)
- Jianlong Zhouand Fang Chen. Making Machine Learning Useable. International Journal
of
Intelligent Systems Technologies and Applications,
vol. 14, no. 2, pp.91-109, 2015. (PDF)
- Jianlong Zhou , Jinjun Sun, Fang Chen, Yang Wang, Ronnie Taib, Ahmad Khawaji, and
Zhidong Li.
Measurable Decision Making with GSR and Pupillary Analysis for Intelligent User
Interface.
ACM Transactions on Computer-Human Interaction (ToCHI), vol. 21, no. 6, article
no. 33, 2015.
(PDF)
- Z. Zhu, Z. Jin, J. Zhang, N. Yang, J. Huang, J. Zhou, and F. Chen, “Narrowing
Information Bottleneck Theory for Multimodal Image-Text Representations
Interpretability”, In the Thirteenth International Conference on Learning
Representations (ICLR 2025), 2025.
- Regnier Avice, Bernhard Haslhofer, Zhidong Li, and Jianlong Zhou, “Linking
Cryptoasset Attribution Tags to Knowledge Graph Entities: An LLM-based
Approach”, Financial Cryptography and Data Security 2025 (FC’25), Miyakojima,
Japan, 2025.
- Shi Wu, Jianlong Zhou, Yifei Dong, and Fang Chen, “Enhancing Explainability of Deep
Learning-Based ECG Diagnosis Using Large Language Models”, Proceedings of the
8th International Conference on Advances in Artificial Intelligence (ICAAI
2024), London, UK, October 17-19, 2024.
- Jichao Kan, Zhidong Li, Jianlong Zhou, and Fang Chen, “Robust Weed Detection with
Evidential Neural Network-based Uncertainty Quantification”, AusDM 2024,
Melbourne, Australia, 2024. (Best Paper Award)
- Dalha Alotaibi, Jianlong Zhou, Yifei Dong, and Fang Chen, “GRADIOOD: A Framework for
Out-Of-Distribution Sample Identification Using Signed Gradients for Robust
Models”, AusDM 2024, Melbourne, Australia, 2024.
- Jianjiu Ou, Jianlong Zhou, Yifei Dong, and Fang Chen, “Chain of Thought Prompting in
Vision-Language Model for Vision Reasoning Tasks”, AJCAI 2024, 2024.
- Jichao Kan, Zhidong Li, Jianlong Zhou, Evan Webster, Ashley Rootsey, Peter
McHannigan, Lelin Zhang, and Fang Chen, “Multi-Task Deep Learning for Prediction
of Kiwifruit Yield in New Zealand with Uncertainty Quantification”, In ICONIP
2024, 2024.
- B. Zheng, J. Zhou, J. Ma, and F. Chen, “Genetic Imitation Learning by Reward
Extrapolation”, IJCNN 2024, 2024.
- Zecheng Liu, Jia Wei, Rui Li, and Jianlong Zhou, “SFusion: Self-attention based
N-to-One Multimodal Fusion Block”, MICCAI 2023, October 2023, Canada.
- Md R. Islam, Md. K. H. Sakib, A. Ulhaq, Shanjita Akter, J. Zhou, and D. Asirvatham,
“SIDVis: Designing Visual Interactive System for Analyzing Suicide Ideation
Detection”, In the 27th International Conference on Information Visualization
(IV2023), 25 – 28 July 2023, Finland. (The Best Paper Award)
- Yiqiao Li, Jianlong Zhou, Yifei Dong, Niusha Shafiabady, and Fang Chen,
“ACGAN-GNNExplainer: Auxiliary Conditional Generative Explainer for Graph Neural
Networks”, In the 32nd ACM International Conference on Information and Knowledge
Management (CIKM 2023), Birmingham, UK, October 2023.
- S. Luo, V. Chu, Z. Li, Y. Wang, J. Zhou, F. Chen, and R. Wong. Multitask learning
for sparse
failure prediction. PAKDD 2019.
- Jianlong Zhou, H. Hu, Z. Li, K. Yu, and F. Chen. Physiological Indicators for User
Trust in Machine Learning with Influence Enhanced Fact-Checking. International
IFIP Cross Domain Conference for Machine Learning & Knowledge Extraction
(CD-MAKE 2019), Canterbury, UK, August, 2019.
- Jianlong Zhou, Z. Li, H. Hu, K. Yu, F. Chen, Z. Li, and Y. Wang. Effects of
Influence on User Trust in Predictive Decision Making. CHI 2019 – LBW, 2019.
- K. Yu, S. Berkovsky, R. Taib, D. Conway, Jianlong Zhou, and F. Chen. Do I Trust My
Machine Teammate? An Investigation from Perception to Decision. IUI 2019, 2019.
- Jianlong Zhou , S. Z. Arshad S. Luo and F. Chen. Effects
of Uncertainty and Cognitive Load on User Trust in Predictive Decision
Making. the 16th IFIP TC.13 International Conference on Human-Computer
Interaction (INTERACT 2017), 2017.(Reviewer’s Choice Award), (“The Brian
Shackel Award” in recognition of the most outstanding contribution with
international impact in the field of human interaction with, and human
use of, computers and information technology). (PDF)
- Syed Z. Arshad, Jianlong Zhou , Shlomo Berkovsky, and Fang
Chen. Human-In-The-Loop Machine Learning with Intelligent Multimodal
Interfaces. ICML2017 Workshop on Human-In-The-Loop Machine Learning,
Sydney, 2017. (PDF)
- Z. Chen, Jianlong Zhou , X. Wang, J. Swanson, F. Chen, and
D. Feng. Neural Net-Based and Satety-Oriented Visual Analytics for
Time-Spatial Data. The 2017 International Joint Conference on Neural
Networks (IJCNN2017), pages 1133-1140, Anchorage, AK, USA, 14-19 May
2017. (PDF)
- S. Luo, V. W. Chu, Jianlong Zhou , F. Chen, and R. K.
Wong. A Multivariate Clustering Approach for Infrastructure Failure
Predictions. Proceedings of IEEE Big Data Congress (IEEEBigData 2017),
Honolulu, Hawaii, USA, June 25-30, 2017. (PDF)
- Jianlong Zhou , S. Z. Arshad S. Luo, K. Yu, S. Berkovsky,
and F. Chen. Indexing Cognitive Load Using Blood Volume Pulse Features.
Proceedings of the 2017 CHI Conference Extended Abstracts on Human
Factors in Computing Systems (CHI EA'17), Pages 2269-2275, Denver, USA,
2017. (PDF)
- S. Luo, Jianlong Zhou , H. Duh, and F. Chen. BVP Feature
Analysis for Intelligent User Interface.
Proceedings of the 2017 CHI Conference Extended Abstracts on Human
Factors in Computing Systems (CHI EA'17), Pages 1861-1868, Denver, USA,
2017. (PDF)
- K. Yu, S. Berkovsky, R. Taib, D. Conway, Jianlong Zhou ,
and F. Chen. User Trust Dynamics:
An Investigation Driven by Differences in System Performance.
Proceedings of the 22nd International Conference on Intelligent User
Interfaces (IUI2017), Pages 307-317, Limassol, Cyprus, 2017. (PDF)
- Jianlong Zhou , Syed Z. Arshad, Kun Yu and Fang Chen. Correlation for User
Confidence in
Predictive Decision Making,
OzCHI2016, 2016. (PDF)
- Syed Z. Arshad, Jianlong Zhou , Constant Bridon, Fang Chen, and Yang Wang.
Investigating User
Confidence for Uncertainty Presentation in Predictive Decision Making. pages
352-360, OzCHI2015,
Melbourne, Australia, 2015.
(PDF)
- Jianlong Zhou , Ju Young Jung, and Fang Chen. Dynamic Workload Adjustments in
Human-Machine
Systems
Based on GSR Features. J. Abascal et al. Eds., Human-Computer Interaction -
INTERACT 2015, Part
I,
LNCS 9296, pp. 550–558, 2015. (PDF)
- Jianlong Zhou , Constant Bridon, Fang Chen, Ahmad Khawaji, and Yang Wang. Be
Informed and Be
Involved:
Effects of Uncertainty and Correlation on User’s Confidence in Decision Making.
Proceedings of
the
33rd Annual
ACM Conference Extended Abstracts on Human Factors in Computing Systems
(CHI'15), Pages 923-928,
2015.
(PDF)
- Ahmad Khawaji, Jianlong Zhou , Fang Chen, and Nadine Marcus. Using Galvanic Skin
Response (GSR) to
Measure Trust and Cognitive Load in the Text-Chat Environment. Proceedings of
the 33rd Annual
ACM Conference Extended Abstracts on Human Factors in Computing Systems
(CHI'15), Pages
1989-1994,
2015.
(PDF)
- Sharon Oviatt, Kevin Hang, Jianlong Zhou , and Fang Chen.
Spoken Interruptions Signal Productive Problem Solving and Domain
Expertise in Mathematics.
Proceedings of the 17th ACM International Conference on Multimodal
Interaction (ICMI2015), Seattle, USA, pages 311-318, November 2015.
- Jianlong Zhou , Kevin Hang, Sharon Oviatt, Kun Yu, and
Fang Chen. Combining Empirical and Machine Learning Techniques to
Predict Math Expertise using Pen Signal Features.
Proceedings of the 2014 ACM workshop on Multimodal Learning
Analytics Workshop and Grand Challenge(MLA 2014), pages 29-36, 2014.
(PDF)
- Ahmad Khawaji, Fang Chen, Jianlong Zhou , and Nadine Marcus. Trust and Cognitive
Load in
the Text-Chat Environment :
The Role of Mouse Movement. Proceedings of the 26th Australian Computer-Human
Interaction
Conference on Designing
Futures (OzCHI 2014), Pages 324-327, 2014. (PDF)
- Ahmad Khawaji, Fang Chen, Nadine Marcus, and Jianlong Zhou . Trust and Cooperation
in
Text-Based Computer-Mediated Communication (CMC).
Proceedings of the 25th Australian Computer-Human Interaction Conference:
Augmentation,
Application, Innovation,
CollaborationOz (CHI 2013), Pages 37-40, 2013. (PDF)
- Jianlong Zhou , Zhidong Li, Yang Wang, and Fang Chen.
Transparent Machine Learning --- Revealing Internal States of Machine
Learning.
In Proceedings of International Conference on Intelligent
User Interfaces 2013 Workshop on Interactive Machine Learning, Santa
Monica, CA USA
March 2013. (PDF)