Selected Journal Papers

(See Google Scholar for full list)
  1. Shi M, Sun, J.A., Lokhande, A., Tian, Y., Luo, Y., Elze, T., Shen, L.Q. and Wang, M., Artifact Correction in Retinal Nerve Fiber Layer Thickness Maps Using Deep Learning and Its Clinical Utility in Glaucoma. Translational Vision Science & Technology (TVST). 2023, 12(11), pp.12-12. (IF=3.3)
  2. Shi M, Lokhande, A., Fazli, M.S., Sharma, V., Tian, Y., Luo, Y., Pasquale, L.R., Elze, T., Boland, M.V., Zebardast, N. and Friedman, D.S, Artifact-Tolerant Clustering-Guided Contrastive Embedding Learning for Ophthalmic Images in Glaucoma. IEEE Journal of Biomedical and Health Informatics (JBHI). 2023. (IF=7.7)
  3. Shi M, Y Tang, X Zhu, Zhuang Y, Lin M, J Liu, Feature-attention graph convolutional networks for noise resilient learning. IEEE Transactions on Cybernetics. 2022. (IF=11.78).
  4. Shi M, Wilson DA, Zhu X, Huang Y, Zhuang Y, Liu J, Tang Y, Evolutionary Architecture Search for Graph Neural Networks. Knowledge Based Systems. 2022. (IF=8.66).
  5. Shi M, Tang Y, Zhu X, Topology and Content Co-Alignment Graph Convolutional Learning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS). 2021. (IF=10.45)
  6. Xiang J, Shi M, Fiala, M.A., Gao, F., Rettig, M.P., Uy, G.L., Schroeder, M.A., Weilbaecher, K.N., Stockerl-Goldstein, K.E., Mollah, S. and DiPersio, J.F., Machine Learning-Based Scoring Models to Predict Hematopoietic Stem Cell Mobilization in Allogeneic Donors. (Blood Advances). 2022. (IF=6.69)
  7. Xiang J, Lu M Shi M, Cheng, X., Kwakwa, K.A., Davis, J.L., Su, X., Bakewell, S.J., Zhang, Y., Fontana, F. and Xu, Y, Machine Learning-Based Scoring Models to Predict Hematopoietic Stem Cell Mobilization in Allogeneic Donors. (Journal of Virology). 2022. (IF=5.4)
  8. Shi M, Tang Y, Zhu X, MLNE: Multi-label network embedding. IEEE Transactions on Neural Networks and Learning Systems (TNNLS). 2019, 31(9), pp.3682-3695. (IF=11.68)
  9. Shi M, Liu J, Tang Y, Zhuang Y, Zhu X, Web Service Embedding with Link Prediction and Convolutional Learning. IEEE Transactions on Services Computing (TSC). 2021. (IF=8.22)
  10. Shi M, Liu J, Zhou D, Tang Y, A Topic-Sensitive Method for Mashup Tag Recommendation Utilizing Multi-Relational Service Data. IEEE Transactions on Services Computing (TSC). 2021. (IF=8.22)
  11. Shi M, Liu J, Zhou D, Tang Y, Functional and Contextual Attention-Based LSTM for Service Recommendation in Mashup Creation. IEEE Transactions on Parallel and Distributed Systems (TPDS). 2018, 30(5), pp.1077-90. (IF=3.97)
  12. Shi M, Tang Y, Zhu X, Liu J, Topic-Aware Web Service Representation Learning. ACM Transactions on the Web (TWEB). 2020, 14 (2), pp.1-23. (IF=2.29)
  13. Shi M, Tang Y, Zhu X, Liu J, Multi-Label Graph Convolutional Network Representation Learning. IEEE Transactions on Big Data (TBD). 2020. (IF=3.34)
  14. Shi M, Tang Y, Zhu X, Liu J, He H, Topical network embedding. Data Mining and Knowledge Discovery (DMKD). 2020, 34(1), pp.75-100. (IF=3.16)
  15. Shi M, Tang Y, Huang Y, Lin M, Mashup tag completion with attention-based topic model. Service Oriented Computing and Applications (SOCA). 2020, 11, pp.1-2. (IF=1.8)
  16. Zhuang Y, Wang Q, Shi M, Cao P, Qi L, Yang J, Low-Power Centimeter-Level Localization for Indoor Mobile Robots Based on Ensemble Kalman Smoother Using Received Signal Strength. IEEE Internet of Things Journal (IOT). 2019, 6(4). pp.6513-22. (IF=9.93)

Selected Conference Papers

(* indicates co-first author. See Google Scholar for full list)
  1. Luo*, Y., Shi* M, Tian*, Y., Elze, T. and Wang, M, Harvard Glaucoma Detection and Progression: A Multimodal Multitask Dataset and Generalization-Reinforced Semi-Supervised Learning . International Conference on Computer Vision (ICCV-23). 2023.
  2. Shi M, Huang Y, Zhu X, Tang Y, Y Zhuang, Liu J, GAEN: Graph Attention Evolving Networks . International Joint Conference on Artificial Intelligence (IJCAI-21). 2021.
  3. Shi M, Tang Y, Zhu X, Wilson D, Liu J, Multi-Class Imbalanced Graph Convolutional Network Learning . International Joint Conference on Artificial Intelligence (IJCAI-20). 2020.
  4. J Huai, Y Lin, Y Zhuang, Shi M, Consistent Right-Invariant Fixed-Lag Smoother with Application to Visual Inertial SLAM . AAAI Conference on Artificial Intelligence (AAAI-21). 2020.
  5. Shi M, Liu J, Zhou D, Tang M, Cao B, WE-LDA: A Word Embeddings Augmented LDA Model for Web Services Clustering . International Conference on Web Services (ICWS). 2017.
  6. Shi M, Liu J, Zhou D, Tang M, Xie F, Zhang T, A Probabilistic Topic Model for Mashup Tag Recommendation . International Conference on Web Services (ICWS). 2016.
  7. Shi M, Tang Y, Liu J, TA-BLSTM: Tag Attention-based Bidirectional Long Short-Term Memory for Service Recommendation in Mashup Creation. International Joint Conference on Neural Networks (IJCNN). 2019.
  8. Shi M, Liu J, Cao B, Wen Y, Zhang X, A Prior Knowledge Based Approach to Improving Accuracy of Web Services Clustering. International Conference on Services Computing (SCC). 2018.