Journals

1. D. Deanda,  I. Alsmadi, J. Guerrero, and Gongbo Liang.  "Defending Mutation-Based Adversarial Text Perturbation: A Black-box Approach." Cluster Computing, 28, (2025):196. In press. (IF=3.6, SJR=Q1) 

2. L. Liu, J. Xie, J. Chang, Z. Liu, T. Sun, Gongbo Liang, and W. Gou. "H-Net: Heterogeneous neural network for multi-classification of neuropsychiatric disorders."  IEEE Journal of Biomedical and Health Informatics, 28, no.9 (2024):5509 - 5518. (IF=7.7, SJR=Q1)

3. Gongbo Liang}, J. Zulu, X.Xing, and N. Jacobs. "Unveiling Roadway Hazards: Enhancing Fatal Crash Risk Estimation through MultiScale Aerial Images and Self-Supervised Learning."  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17 (2024):535-546. (IF=5.5, SJR=Q1) 

4. L. Liu, P. Zhang, Gongbo Liang, S. Xiong, J. Wang, and G. Zhang. "A Spatiotemporal Correlation Deep Learning Network for Brain Penumbra Disease."  Neurocomputing, 520, no.1 (2023):274-283. (IF=6.0, SJR=Q1)

5. Gongbo Liang, C. Greenwell, Y. Zhang, X. Xing, X. Wang, R. Kavuluru, and N. Jacobs . "Contrastive Cross-Modal Pre-Training: A General Strategy for Small Sample Medical Imaging." IEEE Journal of Biomedical and Health Informatics, 26, no. 4 (2022):1640-1649. (IF=7.7, SJR=Q1)

6. S. Lin, Y. Su, Gongbo Liang, YY. Zhang, N. Jacobs, and Y. Zhang. "Estimating Cluster Masses from SDSS Multi-band Images with Transfer Learning." Monthly Notices of the Royal Astronomical Society, 512, no. 3 (2022):3885-3894. (IF=5.4, SJR=Q1)

7. X. Wang, Gongbo Liang, Y. Zhang, H. Blanton, Z. Bessinger, and N. Jacobs. "Inconsistent Performance of Deep Learning Models on Mammogram Classification." Journal of the American College of Radiology, 17, no. 6 (2020): 796-803.   (IF=6.3, SJR=Q1)

8. R. Mihail, Gongbo Liang, N. Jacobs. "Automatic Hand Skeletal Shape Estimation from Radiographs." IEEE Transactions on NanoBioscience, 18, no. 3 (2019): 296-305.   (IF=3.7, SJR=Q1)  

Conferences

1. D. Deanda, Y. Masupalli, J. Yang, Y. Lee, Z. Cao and \textbf{Gongbo Liang}. "Benchmarking Robustness of Contrastive Learning Models for Medical Image-Report Retrieval." In the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI) Workshop, 2025. Philadelphia, PA. USA. 

2. B. Han, Y. Masupalli, X. Xing, and Gongbo Liang. "Improving Medical Imaging Model Calibration through Probabilistic Embedding" In IEEE International Conference on Big Data (BigData), 2024. Washington DC, USA. (CORE Ranking: B, H5-index: 54)

3. E. Xing,  L. Liu, X. Xing, Y Qu, N. Jacobs, and Gongbo Liang. "Neural Network Decision-Making Criteria Consistency Analysis via Inputs Sensitivity." In the 26th International Conference on Pattern Recognition (ICPR), 2022. Montréal, Québec, Canada. (CORE Raking: B, H5-Index: 58)

4. X. Xing, Gongbo Liang, Y. Zhang, S. Khanal, A. Lin, and N. Jacobs. "ADViT:~Vision Transformer on Multi-modality PET Images for Alzheimer Disease Diagnosis." In IEEE International Symposium on Biomedical Imaging (ISBI), 2022. Kolkata, India. (ERA2010 Raking: A, H5-Index: 59)

5. Y. Zhang, Gongbo Liang, and N. Jacobs. "Dynamic Feature Alignment for Semi-Supervised Domain Adaptation." In 32nd British Machine Vision Conference (BMVC), 2021. Manchester, England. (CORE Ranking: A, H5-Index: 77, Acceptance Ratio: 434/1657=~26%)

6. Gongbo Liang, Y. Zhang, X. Wang, and N. Jacobs . "Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification." In 31st British Machine Vision Conference (BMVC), 2020. Manchester, England. (CORE Ranking: A, H5-Index: 77, Acceptance Ratio: 195/928=~21%)

7. Gongbo Liang, S. Lin, Y. Zhang, Y. Su, and N. Jacobs . ``Optical Wavelength Guided Feature Learning for Galaxy Group Richness Estimation." In 34th Conference on Neural Information Processing Systems (NeurIPS) Workshop, 2020. Vancouver, Canada.

8. X. Xing, Gongbo Liang, H. Blanton, M. Rafique, C. Wang, A. Lin, and N. Jacobs. "Dynamic Image for 3D MRI Image Alzheimer’s Disease Classification." In 2020 the European Conference on Computer Vision (ECCV) Workshop, 2020. Glasgow, United Kingdom. (Joint First Author)

9. Y. Zhang, Gongbo Liang, T. Salem, and N. Jacobs. "Defense-PointNet:~Protecting PointNet Against Adversarial Attacks." In IEEE International Conference on Big Data (Big Data), 2019. Los Angeles, USA. (CORE Ranking: B, H5-Index: 53, Acceptance Ratio: ~19%)

10. Gongbo Liang, Q. Li, and X. Kang. "Pedestrian detection via a leg-driven physiology framework." In IEEE International Conference on Image Processing (ICIP),  2016. Phoenix, USA. (CORE Raking: B, H5-Index: 61)